Journal articles on the topic 'Utility dependencies'
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Russell, Richard, and Sean Holden. "Handling Goal Utility Dependencies in a Satisfiability Framework." Proceedings of the International Conference on Automated Planning and Scheduling 20 (May 25, 2021): 145–52. http://dx.doi.org/10.1609/icaps.v20i1.13401.
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Goal utility dependencies arise when the utility of achieving a goal depends on the other goals that are achieved with it. This complicates the planning procedure because achieving a new goal can potentially alter the utilities of all the other goals currently achieved. In this paper, we present an encoding procedure that enables general-purpose Max-SAT solvers to be used to solve planning problems with goal utility dependencies. We compare this approach to one using integer programming via an empirical evaluation using benchmark problems from past international planning competitions. Our results indicate that this approach is competitive and sometimes more successful than an integer programming one -- solving two to three times more subproblems in some domains, while being outperformed by only a significantly smaller margin in others.
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Pastore, Richard E., and Edward J. Crawley. "Locus equation: Assumption and dependencies." Behavioral and Brain Sciences 21, no. 2 (April 1998): 278–79. http://dx.doi.org/10.1017/s0140525x98441177.
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Evaluating the current locus equation under ideal conditions identifies important and unexpected parameter dependencies. Locus equation (LE) utility, either as a valid laboratory tool or possible invariant cue, depends on stringent specification of critical parameters and rigorous empirical testing.
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Batzilla, Alina, Junyan Lu, Jarno Kivioja, Kerstin Putzker, Joe Lewis, Thorsten Zenz, and Wolfgang Huber. "Inferring tumor-specific cancer dependencies through integrating ex vivo drug response assays and drug-protein profiling." PLOS Computational Biology 18, no. 8 (August 22, 2022): e1010438. http://dx.doi.org/10.1371/journal.pcbi.1010438.
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The development of cancer therapies may be improved by the discovery of tumor-specific molecular dependencies. The requisite tools include genetic and chemical perturbations, each with its strengths and limitations. Chemical perturbations can be readily applied to primary cancer samples at large scale, but mechanistic understanding of hits and further pharmaceutical development is often complicated by the fact that a chemical compound has affinities to multiple proteins. To computationally infer specific molecular dependencies of individual cancers from their ex vivo drug sensitivity profiles, we developed a mathematical model that deconvolutes these data using measurements of protein-drug affinity profiles. Through integrating a drug-kinase profiling dataset and several drug response datasets, our method, DepInfeR, correctly identified known protein kinase dependencies, including the EGFR dependence of HER2+ breast cancer cell lines, the FLT3 dependence of acute myeloid leukemia (AML) with FLT3-ITD mutations and the differential dependencies on the B-cell receptor pathway in the two major subtypes of chronic lymphocytic leukemia (CLL). Furthermore, our method uncovered new subgroup-specific dependencies, including a previously unreported dependence of high-risk CLL on Checkpoint kinase 1 (CHEK1). The method also produced a detailed map of the kinase dependencies in a heterogeneous set of 117 CLL samples. The ability to deconvolute polypharmacological phenotypes into underlying causal molecular dependencies should increase the utility of high-throughput drug response assays for functional precision oncology.
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Beisbart, Claus, and Stephan Hartmann. "Welfarist evaluations of decision rules under interstate utility dependencies." Social Choice and Welfare 34, no. 2 (June 9, 2009): 315–44. http://dx.doi.org/10.1007/s00355-009-0399-z.
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Wettergren, Thomas A., and John G. Baylog. "Modeling Sequential Searches with Ancillary Target Dependencies." Advances in Decision Sciences 2010 (February 28, 2010): 1–26. http://dx.doi.org/10.1155/2010/472809.
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We develop a mathematical modeling approach to evaluate the effectiveness of a Bayesian search for objects in cases where the target exhibits ancillary dependencies. These dependencies occur in situations where there are multiple search passes of the same region, and they represent a change in search probability from that predicted using an assumption of independent scans. This variation from independent scans is typically found in situations of advanced detection processing due to fusion and/or collaboration between searchers. The framework developed is based upon the evaluation of a recursion process over spatial search cells, and the dependencies appear as additive utility components within the recursion. We derive expressions for evaluating this utility and illustrate in detail some specific instantiations of the dependency. Computational examples are provided to demonstrate the capabilities of the method.
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Ortega, Eva–María, and Laureano F. Escudero. "On expected utility for financial insurance portfolios with stochastic dependencies." European Journal of Operational Research 200, no. 1 (January 2010): 181–86. http://dx.doi.org/10.1016/j.ejor.2008.11.042.
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Paetz, Friederike, and Winfried J. Steiner. "The benefits of incorporating utility dependencies in finite mixture probit models." OR Spectrum 39, no. 3 (May 6, 2017): 793–819. http://dx.doi.org/10.1007/s00291-017-0478-y.
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Grau, Jan, Martin Nettling, and Jens Keilwagen. "DepLogo: visualizing sequence dependencies in R." Bioinformatics 35, no. 22 (June 21, 2019): 4812–14. http://dx.doi.org/10.1093/bioinformatics/btz507.
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Abstract Summary Statistical dependencies are present in a variety of sequence data, but are not discernible from traditional sequence logos. Here, we present the R package DepLogo for visualizing inter-position dependencies in aligned sequence data as dependency logos. Dependency logos make dependency structures, which correspond to regular co-occurrences of symbols at dependent positions, visually perceptible. To this end, sequences are partitioned based on their symbols at highly dependent positions as measured by mutual information, and each partition obtains its own visual representation. We illustrate the utility of the DepLogo package in several use cases generating dependency logos from DNA, RNA and protein sequences. Availability and implementation The DepLogo R package is available from CRAN and its source code is available at https://github.com/Jstacs/DepLogo. Supplementary information Supplementary data are available at Bioinformatics online.
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JIANG, Zhi-Hua, Dong-Ning RAO, Yun-Fei JIANG, and Jian WENG. "Handling Goal Utility Dependencies in OSP Problems with Derived Predicates and Preferences." Journal of Software 23, no. 3 (April 28, 2012): 439–50. http://dx.doi.org/10.3724/sp.j.1001.2012.03985.
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Zhai, Jian, Robert James, and Artem Prokhorov. "Technical and allocative inefficiency in production systems: a vine copula approach." Dependence Modeling 10, no. 1 (January 1, 2022): 145–58. http://dx.doi.org/10.1515/demo-2022-0108.
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Abstract Modeling the error terms in stochastic frontier models of production systems requires multivariate distributions with certain characteristics. We argue that canonical vine copulas offer a natural way to model the pairwise dependence between the two main error types that arise in production systems with multiple inputs. We introduce a vine copula construction that permits dependence between the magnitude (but not the sign) of the errors. By using a recently proposed family of copulas, we show how to construct a simulated likelihood based on C-vines. We discuss issues that arise in the estimation of such models and outline why such models better reflect the dependencies that arise in practice. Monte Carlo simulations and a classic empirical application to electricity generation plants illustrate the utility of the proposed approach.
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Long, Elizabeth C., Radka Kaneva, Georgi Vasilev, F. Gerard Moeller, and Jasmin Vassileva. "Neurocognitive and Psychiatric Markers for Addiction: Common vs. Specific Endophenotypes for Heroin and Amphetamine Dependence." Current Topics in Medicinal Chemistry 20, no. 7 (April 23, 2020): 585–97. http://dx.doi.org/10.2174/1568026620666200131124608.
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Background: The differential utility of neurocognitive impulsivity and externalizing/ internalizing traits as putative endophenotypes for dependence on heroin vs. amphetamine is unclear. Objective: This exploratory study aims to determine: (1) whether neurocognitive impulsivity dimensions and externalizing/internalizing traits are correlated between siblings discordant for heroin and amphetamine dependence; and (2) which of these associations are common across substances and which are substance- specific. Methods: Pearson correlations between individuals with ‘pure’ heroin and amphetamine dependence and their unaffected biological siblings (n = 37 heroin sibling pairs; n = 30 amphetamine sibling pairs) were run on 10 neurocognitive measures, 6 externalizing measures, and 5 internalizing measures. Sibling pair effects were further examined using regression. Results: Siblings discordant for heroin dependence were significantly correlated on delay aversion on the Cambridge Gambling Task, risk-taking on the Balloon Analogue Risk Task, sensation seeking, and hopelessness. Siblings discordant for amphetamine dependence were significantly correlated on the quality of decision-making on the Cambridge Gambling Task, discriminability on the Immediate Memory Task, commission errors on the Go/No Go Task, trait impulsivity, ADHD and anxiety sensitivity. Conclusion: Dimensions of impulsivity and externalizing/internalizing traits appear to aggregate among siblings discordant for substance dependence. Risk-taking propensity, sensation seeking and hopelessness were specific for heroin sibling pairs. Motor/action impulsivity, trait impulsivity, and anxiety sensitivity were specific to amphetamine sibling pairs. Decisional/choice impulsivity was common across both heroin and amphetamine sibling pairs. These findings provide preliminary evidence for the utility of neurocognitive impulsivity and externalizing/ internalizing traits as candidate endophenotypes for substance dependence in general and for substance-specific dependencies.
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Allen, Benjamin, Blake Stacey, and Yaneer Bar-Yam. "Multiscale Information Theory and the Marginal Utility of Information." Entropy 19, no. 6 (June 13, 2017): 273. http://dx.doi.org/10.3390/e19060273.
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Complex systems display behavior at a range of scales. Large-scale behaviors can emerge from the correlated or dependent behavior of individual small-scale components. To capture this observation in a rigorous and general way, we introduce a formalism for multiscale information theory. Dependent behavior among system components results in overlapping or shared information. A system’s structure is revealed in the sharing of information across the system’s dependencies, each of which has an associated scale. Counting information according to its scale yields the quantity of scale-weighted information, which is conserved when a system is reorganized. In the interest of flexibility we allow information to be quantified using any function that satisfies two basic axioms. Shannon information and vector space dimension are examples. We discuss two quantitative indices that summarize system structure: an existing index, the complexity profile, and a new index, the marginal utility of information. Using simple examples, we show how these indices capture the multiscale structure of complex systems in a quantitative way.
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Yu, Jia, and Rajkumar Buyya. "Scheduling Scientific Workflow Applications with Deadline and Budget Constraints Using Genetic Algorithms." Scientific Programming 14, no. 3-4 (2006): 217–30. http://dx.doi.org/10.1155/2006/271608.
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Grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models, which are capable of supporting diverse computing services. It facilitates scientific applications to take advantage of computing resources distributed world wide to enhance the capability and performance. Many scientific applications in areas such as bioinformatics and astronomy require workflow processing in which tasks are executed based on their control or data dependencies. Scheduling such interdependent tasks on utility Grid environments need to consider users' QoS requirements. In this paper, we present a genetic algorithm approach to address scheduling optimization problems in workflow applications, based on two QoS constraints, deadline and budget.
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den Duijn, X., G. Agugiaro, and S. Zlatanova. "MODELLING BELOW- AND ABOVE-GROUND UTILITY NETWORK FEATURES WITH THE CITYGML UTILITY NETWORK ADE: EXPERIENCES FROM ROTTERDAM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W7 (September 20, 2018): 43–50. http://dx.doi.org/10.5194/isprs-annals-iv-4-w7-43-2018.
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<p><strong>Abstract.</strong> Precise and comprehensive knowledge about 3D urban space is required for simulation and analysis in the fields of urban and environmental planning, city administration and disaster management. In order to facilitate these applications, geo-information about functional, semantic, and topographic aspects of urban features, their mutual dependencies and relations is needed. Substantial work has been done in the modelling and representation of above-ground features in the context of 3D city modelling. However, the belowground part of the real world, of which utility networks form a big part, is often neglected. Existing data models for utility networks are generally very domain-specific and, therefore, not suitable either. This paper describes a 3D data modelling approach for integrated management of below-ground utility networks and related above-ground city objects. This approach consists of manipulating first the structure of existing utility data in the commonly used Feature Manipulation Engine ETL software in order to make the data compliant to the CityGML Utility Network ADE data model. Subsequently, workspaces are created that take care of storing the CityGML data into the free and open-source 3D City Database, which has been extended in order to manage utility network data, too. Moreover, the research shows the suitability of the extended 3DCityDB to perform graph-based topological operations by means of the PostgreSQL pgRouting extension. Lastly, the results are visualized in typical GIS applications, e.g. QGIS and ArcGIS.</p>
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Belyaev, Alexander, Alina Markovnina, Vladimir Belyakov, and Vladimir Makarov. "Study of deformation properties of road foundations of the mixed type intended for the movement of mobile complexes for monitoring and transporting raw materials." E3S Web of Conferences 326 (2021): 00010. http://dx.doi.org/10.1051/e3sconf/202132600010.
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Analysis of the conditions of movement of mobile robotic complexes showed that about 70% of the time of movement is made up of sand, gravel and sandy areas. In winter, it is covered with snow. An unsolved problem is the traffic conditions during the transition period, namely, movement on snow-sandy support bases. This paper is devoted to the study of road and soil foundations, i.e. mixed surfaces consisting of sand and snow. A method for obtaining mixed surfaces (mixtures) with different percentages is described. It is shown how the measurements of the density and fractional composition of the sand were carried out. It also shows how the snow density was measured. Examples of test fragments are given. A test procedure for measurement of deformation properties is presented. “Load-deformation” curves are provided. The study reveals how the sand and snow percentage affects the curve behaviour. Dependencies are given to describe the process “load deformation” for sand and snow. The dependence of the mixtures is proposed. The generalized dependence includes the dependences of Goryachkin - Letoshnev and Malygin. This paper also specifies the curve behaviour for an undisturbed road and soil foundation, and a surface exposed to an operating mover or a utility vehicle. It is shown that for mixtures of various compositions for an intact surface and under repeated loading, the difference in stresses is from 1.25 to 5 times.
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Shah, Nauman, and Stephen J. Roberts. "Dynamically Measuring Statistical Dependencies in Multivariate Financial Time Series Using Independent Component Analysis." ISRN Signal Processing 2013 (June 2, 2013): 1–14. http://dx.doi.org/10.1155/2013/434832.
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We present a computationally tractable approach to dynamically measure statistical dependencies in multivariate non-Gaussian signals. The approach makes use of extensions of independent component analysis to calculate information coupling, as a proxy measure for mutual information, between multiple signals and can be used to estimate uncertainty associated with the information coupling measure in a straightforward way. We empirically validate relative accuracy of the information coupling measure using a set of synthetic data examples and showcase practical utility of using the measure when analysing multivariate financial time series.
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Lachlan, PhD, Kenneth A., Christine Gilbert, MA, Emily Hutter, PhD, Adam Rainear, PhD, and Patric R. Spence, PhD. "Sex differences in informational needs and media dependencies during the 2018 California wildfires." Journal of Emergency Management 20, no. 4 (July 1, 2022): 341–50. http://dx.doi.org/10.5055/jem.0588.
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Previous research has suggested that men and women differ in a number of crisis-related behaviors including information-seeking behavior and media dependencies. The 2018 California wildfires provided a context where demographic differences are largely unexplored, as most prior emergency communication research has focused on slower moving events such as hurricanes and storm surges. Participants were identified based on their residence in areas affected by the Camp and Woolsey fires (N = 363). Sex differences were discovered for how people found out about the fires, perceptions of medium utility, and informational needs. Implications for emergency management practitioners are discussed.
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Hosseini, Hadi, Jesse Hoey, and Robin Cohen. "A Market-Based Coordination Mechanism for Resource Planning Under Uncertainty." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 2427–28. http://dx.doi.org/10.1609/aaai.v26i1.8428.
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Multiagent Resource Allocation (MARA) distributes a set of resources among a set of intelligent agents in order to respect the preferences of the agents and to maximize some measure of global utility, which may include minimizing total costs or maximizing total return. We are interested in MARA solutions that provide optimal or close-to-optimal allocation of resources in terms of maximizing a global welfare function with low communication and computation cost, with respect to the priority of agents, and temporal dependencies between resources. We propose an MDP approach for resource planning in multiagent environments. Our approach formulates internal preference modeling and success of each individual agent as a single MDP and then to optimize global utility, we apply a market-based solution to coordinate these decentralized MDPs.
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Lim, Huat Chye, Rigney Turnham, Katherine Lo, Yeonjoo Hwang, and John Gordan. "Abstract PR01: Computational identification of targetable dependencies in hepatocellular carcinoma (HCC) associated with hepatitis B virus (HBV) replication." Clinical Cancer Research 28, no. 17_Supplement (September 1, 2022): PR01. http://dx.doi.org/10.1158/1557-3265.liverca22-pr01.
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Abstract Background: HBV-associated HCC has distinct molecular characteristics and worse outcomes compared to non-HBV HCC. We hypothesized that HBV infection might introduce targetable dependencies specific to HBV-associated HCC. Here, we demonstrate the utility of a computational strategy integrating genomic, network and survival analysis for identifying potential therapeutic targets in HBV-associated HCC. Methods: RNA-Seq and CRISPR dependency screening data for 22 HCC cell lines were obtained from the Cancer Dependency Map (DepMap). Cell lines were classified as HBV RNA+ if they harbored more than 40 HBV RNA reads, measured using GATK PathSeq software. Separately, whole genome CRISPRi dependency screening was performed in Hep3B and SNU-368 cells with doxycycline (dox)- inducible HBx expression. Genes where HBV RNA+ status (for DepMap) or HBx expression (for dox-inducible Hep3B/SNU-368) were significantly associated with negative dependency score were classified as HBV differential dependencies. To identify shared targets across datasets, these dependencies were evaluated using two network analysis techniques: the MCODE graph clustering algorithm and network propagation. Finally, RNA-Seq and survival data for 371 HCC cases were obtained from TCGA, and for each gene, a Cox multivariate model was used to evaluate whether the combination of decreased RNA-Seq expression and HBV RNA+ status was associated with increased survival. Results: 10 of 22 DepMap HCC cell lines were HBV RNA+. From DepMap and dox-inducible Hep3B/SNU-368 dependency screening data, 674 HBV differential dependencies were identified (Wilcoxon p < 0.05 for all). MCODE analysis identified enriched gene networks harboring multiple dependencies, including clusters associated with chromatin remodeling, the DNA damage response, and MAPK/ERK and Wnt signaling. Network propagation identified 236 enriched genes (empiric p < 0.005 for all), including the histone deacetylase HDAC1 and transcription factors ELK1, HNF4A and NRF1. Notably, HDAC1 was significant in both the MCODE and network propagation analyses, and in multivariate analysis of TCGA clinical data, decreased HDAC1 expression was associated with increased survival in HBV RNA+ HCC cases (HR for death 0.10, 95% CI 0.03-0.40, p = 0.0009). Conclusions: Measurement of HBV RNA in HCC cell lines identified a set of HBV- associated differential gene dependencies for which network analysis showed enrichment of several genes/gene clusters, including HDAC1, ELK1, HNF4A and NRF1. Survival analysis highlighted HDAC1 as a potential target where decreased expression was associated with increased survival in HBV RNA+ HCC cases in TCGA. Beyond nominating HDAC1, this study demonstrates the utility of a computational strategy integrating genomic, network and survival analysis for evaluating therapeutic targets in a virus-associated cancer. Citation Format: Huat Chye Lim, Rigney Turnham, Katherine Lo, Yeonjoo Hwang, John Gordan. Computational identification of targetable dependencies in hepatocellular carcinoma (HCC) associated with hepatitis B virus (HBV) replication [abstract]. In: Proceedings of the AACR Special Conference: Advances in the Pathogenesis and Molecular Therapies of Liver Cancer; 2022 May 5-8; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(17_Suppl):Abstract nr PR01.
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Qin, Rui, Huchang Liao, and Lisheng Jiang. "A CRITERION UTILITY CONVERSION TECHNIQUE FOR PROBABILISTIC LINGUISTIC MULTIPLE CRITERIA ANALYSIS IN EMERGENCY MANAGEMENT." Technological and Economic Development of Economy 27, no. 5 (July 5, 2021): 1207–26. http://dx.doi.org/10.3846/tede.2021.15051.
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In multiple criteria decision making (MCDM), the even swaps method uses the relationships of criteria to make trade-offs but the burdens of experts are heavy; the linear programming technique for multidimensional analysis of preference (LINMAP) method cannot deal with the inter-dependencies among criteria but the cognitive burdens of experts are low. Taking the advantages of both these methods, this study proposes a criterion utility conversion (CUC) technique to solve probabilistic linguistic MCDM problems given that the probabilistic linguistic term set (PLTS) can reflect the psychology of experts when making evaluations. The utility conversion process is first proposed based on the marginal utilities of criteria. Then, the criterion preference ratios of experts are refined from the utility conversion process. Based on the criterion preference ratios and the operations of PLTSs, the adjusted probabilistic linguistic expected values of alternatives are calculated. The consistency and inconsistency indexes of alternatives and criteria are defined to set up the linear programming used to work out the criterion preference ratios. An illustration about the selection of emergency logistics supplier is given to validate the proposed method. The comparative analysis indicates the low cognitive burden, high stability, and strong applicability of the proposed method.
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Jha, Ashwani, Rute Teotonio, April-Louise Smith, Jamshed Bomanji, John Dickson, Beate Diehl, John S. Duncan, and Parashkev Nachev. "Metabolic lesion-deficit mapping of human cognition." Brain 143, no. 3 (March 1, 2020): 877–90. http://dx.doi.org/10.1093/brain/awaa032.
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Abstract In theory the most powerful technique for functional localization in cognitive neuroscience, lesion-deficit mapping is in practice distorted by unmodelled network disconnections and strong ‘parasitic’ dependencies between collaterally damaged ischaemic areas. High-dimensional multivariate modelling can overcome these defects, but only at the cost of commonly impracticable data scales. Here we develop lesion-deficit mapping with metabolic lesions—discrete areas of hypometabolism typically seen on interictal 18F-fluorodeoxyglucose PET imaging in patients with focal epilepsy—that inherently capture disconnection effects, and whose structural dependence patterns are sufficiently benign to allow the derivation of robust functional anatomical maps with modest data. In this cross-sectional study of 159 patients with widely distributed focal cortical impairments, we derive lesion-deficit maps of a broad range of psychological subdomains underlying affect and cognition. We demonstrate the potential clinical utility of the approach in guiding therapeutic resection for focal epilepsy or other neurosurgical indications by applying high-dimensional modelling to predict out-of-sample verbal IQ and depression from cortical metabolism alone.
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Cardone, Michael H., Sae Rin Jean, Bahriye Karakas, Sonia Kumar, Max Narovlyansky, and Bora Lim. "Identifying Mcl-1 protein dependencies using dimerization-specific antibody biomarker for predicting response to targeted apoptosis inducing therapies." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): 7038. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.7038.
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7038 Background: The anti-apoptotic Bcl-2 family proteins facilitate pro-survival and resistance to anti-cancer therapies. Measuring the function of these proteins has shown utility in predicting response to therapy. A method that expands the principle of BH3 profiling to solid tumors is presented. Measuring the occurrence of heterodimers of Myeloid Leukemia Cell Differentiation Protein (Mcl-1), and pro-apoptotic binding protein Bim is an indicator of cancer cell apoptotic priming state. The readout of Mcl-1 containing complex-specific biomarkers can identify survival dependencies in cancer cells potentially providing clinical utility in guiding cancer treatments. Methods: Engineered immunogens that recapitulate conformation-specific epitopes induced during binding of the Mcl-1/Bim protein complex were used to generate. monoclonal antibodies. One Heterodimer Specific Mcl-1 Bim (HsMcB) was chosen. The selective binding was confirmed using ELISA, fluorescence polarization, immunofluorescence microscopy and flow cytometry in Bim or Mcl-1 knockdown cells, and by immunohistochemistry in formalin-fixed paraffin-embedded patient tissue. Correlation of HsMcB measurements to BH3 profiling readouts from the Mcl-1 restricted Noxa peptide was explored. Results: HsMcB signal depends on both Mcl-1 and Bim protein levels. The ratio of the HsMcB to unbound protein (Mcl-1) signal ([HsMcB]/[Mcl-1]) was measured. Disruption of the complexes by BH3 mimetics targeted to Mcl-1 and depletion of Mcl-1 level using CDK9 inhibitors diminished the [HsMcB]/[Mcl-1] readout. We see correlations between these readouts and BH3 mimetic peptides readouts from the Mcl-1 specific Noxa and MS1 BH3 mimetic peptides in AML patient samples that have been treated with Mcl-1 inhibitors. Conclusions: Mcl-1 dependence is a predictive biomarker for venetoclax resistance and for response to Mcl-1 targeted therapies. Flow cytometric and IHC based measurements of a heterodimer complex offer a direct and simpler approach that harbors potential for use in clinical settings. Additional antibodies targeting Mcl-1/Bak and Mcl-1 Noxa complexes are being tested.
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Shi, Yu Qing, and Yue Long Zhu. "Constructe a Hierarchical and Architecture of Cloud Computing Frameworks." Applied Mechanics and Materials 496-500 (January 2014): 2003–6. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2003.
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The concept of Cloud Computing dates from the 1960s, when computer scientist John McCarthy proposed the idea of computation being delivered as a public utility. Infrastructure as a Service is one of the most important modules of Cloud Computing. In this paper, we propose a hierarchical and architecture of Cloud Computing Infrastructure as a Service frameworks. Our hierarchical and architecture consists of five main layers: resource layer, service layer, middleware layer, management layer, control layer. We study various Cloud Computing systems. Then we provide a Cloud Computing Infrastructure as a Service architectural framework that bases on the hierarchical architecture. Finally, we introduce a detailed description of each layer and define dependencies between the layers and components.
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Babak, Tomas, Michael Vermeulen, Doris Coto Villa, and Andrew Craig. "Abstract 4035: Driver-gene dependencies reveal clinically actionable drug repositioning opportunities." Cancer Research 82, no. 12_Supplement (June 15, 2022): 4035. http://dx.doi.org/10.1158/1538-7445.am2022-4035.
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Abstract Cancer cell lines have numerous characteristics that make them favorable pre-clinical research models, yet they are notoriously poor at predicting drug response in the clinic. Here we sought to investigate the utility of synthetic lethality (SL) interactions discovered from large-scale CRISPR functional screens (i.e. the BROAD and Sanger Cancer Dependency Maps or "DepMap") as predictors of targets that validate in patients. Mutual exclusivity, the phenomenon where two genes are rarely mutated together in the same tumor, is a powerful clinical-stage readout that can be caused by synthetic lethality. We found that SL interactions discovered in DepMap are significantly more likely to be mutually exclusive in TCGA when they include a driver (tumor-suppressor/oncogene). These SL interactions represent high-value targeting opportunities with the advantage of clear patient selection criteria based on their driver mutation status. In an effort to identify drugs that target these proteins as potential repurposing opportunities, we found that pharmacogenomic inhibition rarely invokes the same target dependencies as a genetic deletion of the drug target. Nonetheless, we identified several dozen "clean" drugs with potential for repositioning and validated the top candidates in PDx. Although tumours are more heterogenous than cancer cell lines, we show that cell line viability readouts linked to single-gene/drug perturbations can yield accurate predictions of clinical efficacy when tied to tumor-driver biology. Citation Format: Tomas Babak, Michael Vermeulen, Doris Coto Villa, Andrew Craig. Driver-gene dependencies reveal clinically actionable drug repositioning opportunities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4035.
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Engel, Y., and M. P. Wellman. "Multiattribute Auctions Based on Generalized Additive Independence." Journal of Artificial Intelligence Research 37 (March 30, 2010): 479–525. http://dx.doi.org/10.1613/jair.3002.
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We develop multiattribute auctions that accommodate generalized additive independent (GAI) preferences. We propose an iterative auction mechanism that maintains prices on potentially overlapping GAI clusters of attributes, thus decreases elicitation and computational burden, and creates an open competition among suppliers over a multidimensional domain. Most significantly, the auction is guaranteed to achieve surplus which approximates optimal welfare up to a small additive factor, under reasonable equilibrium strategies of traders. The main departure of GAI auctions from previous literature is to accommodate non-additive trader preferences, hence allowing traders to condition their evaluation of specific attributes on the value of other attributes. At the same time, the GAI structure supports a compact representation of prices, enabling a tractable auction process. We perform a simulation study, demonstrating and quantifying the significant efficiency advantage of more expressive preference modeling. We draw random GAI-structured utility functions with various internal structures, generate additive functions that approximate the GAI utility, and compare the performance of the auctions using the two representations. We find that allowing traders to express existing dependencies among attributes improves the economic efficiency of multiattribute auctions.
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Parackal, Sarah, Wai Chin Chong, Gabrielle Bradshaw, Claire Sun, Paul Daniel, Enola Roussel, Samantha Jayasekara, Duncan Crombie, Ron Firestein, and Jason Cain. "DIPG-18. IDENTIFICATION OF TARGETABLE PATHWAY DEPENDENCIES IN DIFFUSE INTRINSIC PONTINE GLIOMA." Neuro-Oncology 22, Supplement_3 (December 1, 2020): iii290. http://dx.doi.org/10.1093/neuonc/noaa222.068.
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Abstract Diffuse Intrinsic Pontine Glioma (DIPG) is a highly aggressive paediatric brainstem tumour with a dismal prognosis. Recurrent heterozygous mutations (p.K27M) in Histone H3 variant genes have been identified in the majority of DIPG cases. While the exact mechanism of H3K27M’s function is poorly understood, evidence suggests a role for epigenetic dysregulation in disease pathogenesis. This study aims to use functional genomics to identify novel therapeutic dependencies in H3K27M DIPG. DIPG drug sensitivity screening was carried out in twelve established and validated patient derived cell lines (10 H3.3K27M and 2 Wt) using an FDA approved drug library containing 1480 compounds. Highly prevalent targets identified from this screen include HDAC, microtubule, proteasome and CDK inhibitors. Additionally, a custom pooled CRISPR knockout library of druggable targets (300 genes, 1200 guide RNAs) was used to identify key DIPG cell survival pathways. To date five DIPG cell lines (1 Wt; 1 H3.1; 3 H3.3) have undergone screening. Knockdown of known DIPG driver genes (TP53; PDGFRA; PIK3CA and PIK3CR1) resulted in reduced cell viability, consistent with their proposed function and validating knockout screen utility. Preliminary data demonstrates Wt and H3K27M DIPGs cluster independently based on genes required for survival, suggesting differing tumorigenesis mechanisms and the potential for therapeutically targeting genotype specific pathways. Correlation of parallel drug screen and RNA-seq data will potentially reveal H3-dependent pathways for therapeutic exploitation. Collectively, we show a functional genomics approach is able to identify genotype-specific pathway dependencies in DIPG, paving the way for molecularly informed personalized therapies for patients.
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Kuzniar, Arnold, Jason Maassen, Stefan Verhoeven, Luca Santuari, Carl Shneider, Wigard P. Kloosterman, and Jeroen de Ridder. "sv-callers: a highly portable parallel workflow for structural variant detection in whole-genome sequence data." PeerJ 8 (January 6, 2020): e8214. http://dx.doi.org/10.7717/peerj.8214.
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Structural variants (SVs) are an important class of genetic variation implicated in a wide array of genetic diseases including cancer. Despite the advances in whole genome sequencing, comprehensive and accurate detection of SVs in short-read data still poses some practical and computational challenges. We present sv-callers, a highly portable workflow that enables parallel execution of multiple SV detection tools, as well as provide users with example analyses of detected SV callsets in a Jupyter Notebook. This workflow supports easy deployment of software dependencies, configuration and addition of new analysis tools. Moreover, porting it to different computing systems requires minimal effort. Finally, we demonstrate the utility of the workflow by performing both somatic and germline SV analyses on different high-performance computing systems.
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Schnute, Jon T., and Laura J. Richards. "Analytical models for fishery reference points." Canadian Journal of Fisheries and Aquatic Sciences 55, no. 2 (February 1, 1998): 515–28. http://dx.doi.org/10.1139/f97-212.
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Fishery reference points are widely applied in formulating harvest management policies. We supply precise mathematical definitions for several reference points in common use. We then derive analytical expressions for these quantities from age-structured population models. In particular, we explain how the maximum sustainable harvest rate and catch (h*, C*), two quantities of management importance, can replace the classical recruitment parameters ( alpha , beta ) in the Beverton-Holt and Ricker recruitment curves. We also demonstrate dependencies of various reference points on subsets of model parameters. Although our analysis is restricted to special cases, our models still have general utility. For example, simple calculations from analytical formulas enable checks on the output from more complex models and guide the choice of reference points for fishery management.
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Elia, Gianluca, Alessandro Margherita, Alessandro Massaro, and Angelo Vacca. "Adoption of open innovation in the COVID-19 emergency: developing a process-based information coordination system." Business Process Management Journal 28, no. 2 (February 10, 2022): 419–41. http://dx.doi.org/10.1108/bpmj-11-2020-0507.
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PurposeThe COVID-19 pandemic has stimulated a global movement of open innovation initiatives aimed to provide knowledge and tools to support policy decisions and actions in the emergency scenario. The authors describe an open innovation process aimed to build an information coordination system to reduce the infection diffusion within the population.Design/methodology/approachThe authors use coordination theory principles to elaborate a framework of activities, resources and dependencies among information resources and producers in the COVID-19 emergency. The framework was applied to develop a case study aimed at describing a health emergency system implemented by Dyrecta Lab (a research laboratory on computer science) and CITEL (a medical research center).FindingsThe authors describe the existence of relevant “flow,” “fit” and “share” dependencies within the activities of infection containment and medical treatment. The authors identify eight key resources and a number of actors involved in those activities, and describe a platform able to gather a multitude of epidemic-related metrics with the purpose to address dependencies and support decision making.Research limitations/implicationsThe authors provide insights for advancing the academic discussion on process coordination principles in time-constrained, volatile and highly demanding scenarios.Practical implicationsThe value of the authors’ research can be identified for practitioners engaged to develop innovative development projects for public utility. The authors provide a contribution also for first responders and health operators involved in management of the current and future emergencies.Originality/valueThe adoption of process coordination principles is a relatively new and powerful approach to analyze and optimize the processes that characterize the management of emergency scenarios. Besides, the study and application of open innovation in healthcare are partially limited.
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Corces-Zimmerman, Michael Ryan, Matthew Eaton, Jeremy Lopez, Nan Ke, Christian Fritz, Eric Olson, Ravi Majeti, and Jakob Loven. "Discovery and Characterization of Super-Enhancer-Associated Dependencies in Acute Myeloid Leukemia." Blood 124, no. 21 (December 6, 2014): 3539. http://dx.doi.org/10.1182/blood.v124.21.3539.3539.
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Abstract Misregulation of genes that play an important role in transcription and chromatin biology is a salient feature of many hematological cancers, including acute myeloid leukemia (AML). Numerous genome-wide analyses in AML have provided evidence linking recurring genetic mutations to epigenomic alterations and disease-specific gene expression programs but the prognostic value and clinical utility of these findings remain unclear. Recently, a novel class of densely clustered cis-regulatory elements termed super-enhancers have emerged as key effectors initiating and maintaining cell type-specific gene expression in a variety of physiological and disease settings, including cancer. Tumor-specific super-enhancers regulate key oncogenes and other cancer-essential genes, providing a novel target discovery strategy for detecting both known and unrecognized cancer dependencies of high diagnostic and therapeutic value. Here we describe the discovery and characterization of super-enhancer domains across a cohort of nearly 50 AML patients and relevant normal hematopoietic stem and progenitor cell controls. We identified unique, clone-specific cancer targets encoding protein kinases, chromatin regulators, and lineage-specific transcription factors, including key drivers of AML such as FLT3, CDK6, and MYB. In addition, we have identified clusters of AML cases with shared super-enhancer domains suggesting convergence on common key drivers of AML. We provide the biological and disease relevance of super-enhancer-associated genes in the context of tumor cell state and drug-target discovery and establish a molecular rationale for developing therapies based on these new insights. Disclosures Eaton: Syros Pharmaceuticals: Employment, Equity Ownership. Lopez:Syros Pharmaceuticals: Employment, Equity Ownership. Ke:Syros Pharmaceuticals: Employment, Equity Ownership. Fritz:Syros Pharmaceuticals: Employment, Equity Ownership. Olson:Syros Pharmaceuticals: Employment, Equity Ownership. Loven:Syros Pharmaceuticals: Employment, Equity Ownership.
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McArthur, Bruce A., and Anthony W. Isenor. "Applying spatial mutual information to AIS data." Journal of Navigation 75, no. 1 (October 1, 2021): 95–105. http://dx.doi.org/10.1017/s0373463321000734.
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AbstractThis paper examines a new interpretation for spatial mutual information based on the mutual information between an attribute value and a spatial random variable. This new interpretation permits the measurement of variations in spatial mutual information over the domain, not only answering the question of whether a spatial dependency exists and the strength of that dependency, but also allowing the identification of where such dependencies exist. Using simulated and real vessel reporting data, the properties of this new interpretation of spatial mutual information are explored. The utility of the technique in detecting spatial boundaries between regions of data having different statistical properties is examined. The technique is shown to successfully identify vessel traffic boundaries, crossing points between traffic lanes, and transitions between regions having differing vessel movement patterns.
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Oh, Sunghee, Seongho Song, Gregory Grabowski, Hongyu Zhao, and James P. Noonan. "Time Series Expression Analyses Using RNA-seq: A Statistical Approach." BioMed Research International 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/203681.
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RNA-seq is becoming thede factostandard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.
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Zhang, Yao, and Fei Zuo. "Selection of risk response actions considering risk dependency." Kybernetes 45, no. 10 (November 7, 2016): 1652–67. http://dx.doi.org/10.1108/k-05-2016-0096.
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Purpose The purpose of this paper is to propose a method to address the problem of selecting risk response actions (RRAs) considering the risk dependency that is seldom considered in the existing studies. Design/methodology/approach First, a method based on the Measuring Attractiveness by a Categorical-Based Evaluation Technique (MACBETH) is proposed to measure the dependencies between the risks, and then a preference coefficient denoting the relative importance of the risk dependency is introduced. Besides, an exponential utility function is used to describe the project manager’s (PM) risk-averse behaviour. Finally, a mathematical model that incorporates the risk dependency and risk preference of the PM is constructed for selecting the RRAs. Findings Risk dependency plays an important role in the process of RRA selection. First, more expected utility can be obtained when the risk dependency is considered. Second, more attention should be paid to the risk dependency for coping with critical risks when the budget is tight. Practical implications This method can be applied to determine the RRAs when the risk dependency exists between the project risks. Originality/value This paper proposes a model to select RRAs with consideration of the risk dependency, which is an important issue from a theoretical as well as a practical perspective in project risk management.
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Daniel, Paul, Claire Sun, Mateusz Koptyra, Caroline Drinkwater, Nicole Chew, Gabrielle Bradshaw, Melissa Loi, et al. "MODL-17. The Childhood Brain Cancer Cell Line Atlas: A Resource for Biomarker Identification and Therapeutic Development." Neuro-Oncology 24, Supplement_1 (June 1, 2022): i172. http://dx.doi.org/10.1093/neuonc/noac079.640.
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Abstract Cell lines represent the most versatile and widely used models of cancer and, as such, are critical for identifying and advancing new therapies. Strikingly, there is a significant gap in both the number of childhood brain cancer cell lines and their characterisation compared to their adult counterparts. To address this inequity, we established a childhood brain cancer cell line atlas (publicly available at vicpcc.org.au/dashboard) encompassing over 180 childhood CNS-derived cell lines, representing 20 tumour types and 11 molecular subtypes. Cell lines are characterized by whole genome, RNA-sequencing, phospho- and total proteomics, DNA methylation and ATAC-seq analyses. Multi-omic factor analysis revealed distinct lineage-specified classification of our cell line cohort. In parallel, high throughput drug and CRISPR/Cas9 screens were conducted to map the functional dependencies in over 70 childhood CNS cell lines, including 47 paediatric high grade glioma models. These screens identified both lineage and molecular-subtype specific genetic and drug dependencies, underscoring the utility of this wide-scale approach. Machine based learning approaches to predict genotype-phenotype correlations uncovered distinct paediatric-specific biomarkers of growth dependency, highlighting the unique genetic wiring underlying paediatric CNS tumours. Finally, by integrating functional, molecular and drug profiles of paediatric CNS cell lines, we construct a system to prioritize investigation of novel therapeutic target-biomarkers pairs in specific CNS tumour types.
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Ulmer, J. D. "Strain Dependence of Dynamic Mechanical Properties of Carbon Black-Filled Rubber Compounds." Rubber Chemistry and Technology 69, no. 1 (March 1, 1996): 15–47. http://dx.doi.org/10.5254/1.3538354.
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Abstract The strain dependencies of dynamic mechanical properties of carbon black-filled rubber compounds have been modeled by Kraus. Evaluation of the Kraus model with carbon black loadings up to 110 phr shows that it provides a fairly good overall description of elastic modulus, G′, as a function of strain, γ. The model description of G′ strain dependence improves with decreased carbon black loading, and is very good with carbon black loadings of 50 phr and less. The model description of viscous modulus strain dependence, G″(γ), is less successful than the G′(γ) description. Several empirical modifications of the viscous modulus model are examined. The most improved model is a very good approximation to viscous modulus over a wide experimental strain-range. Its utility, and that of the Kraus G′(γ) model, are illustrated through calculation of simple shear dynamic properties from torsion property measurements on a solid cylinder, where the strain amplitude varies across the specimen radius. The models allow transformation of the apparent moduli, reported as functions of strain amplitude at the cylinder's outer edge, to their true counterparts, G′(γ) and G″(γ), as functions of uniform strain amplitude. Although the G′(γ) and modified G″(γ) models apply to a wide range of experimental strains, some uncertainties associated with each model's accuracy remain, and there are inconsistencies in the relation of one model to the other. Reservations associated with the models might be resolved through refined treatments of the test specimen geometries.
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Pont Martínez, Pepa, Cristina Santamaría Navarro, María Teófila Vicente Herrero, Montserrat Piñaga Solé, María Victoria Ramírez Iniguez de la Torre, and Ángel Arturo López González. "Valoración del impacto de género en la salud de mujeres y hombres." Cuestiones de género: de la igualdad y la diferencia, no. 5 (December 15, 2010): 51. http://dx.doi.org/10.18002/cg.v0i5.3780.
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<p>El objetivo es ensayar la utilidad de incorporar variables sensibles al género, fundamentalmente, las relacionadas con la desigual distribución del trabajo productivo y reproductivo, para identificar posibles desigualdades de salud asociadas al género como determinante de salud. Se han realizado entrevistas clínicas, que incluyen exploraciones y un cuestionario complementario con los que se han recogido variables sobre el estado de salud y variables sociodemográficas, incluidas variables sensibles al género. Los datos del cuestionario y la entrevista clínica se han registrado en una base diseñada ad hoc y se ha analizado con el programa SPSS v. 14, aplicando un análisis descriptivo y un análisis de dependencias bivariante.</p><p>The target is to test the utility of incorporating gender sensitive variables, fundamentally the ones related to the unequal distribution of productive and reproductive work, to identify possible health inequalities associated with the gender as determinant of health.<br />Clinical interviews have been carried out, which include explorations and a complementary questionnaire, gathering health state, sociodemographic, and even gender sensitive variables. The questionnaire data and the clinical interview have been registered in a data base designed ad hoc and have been analyzed by the program SPSS v. 14, applying a descriptive analysis and a bivariant analysis of dependencies.<br /><br /><br /></p>
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Ait Mokhtar, El Hassene, Alaa Chateauneuf, and Radouane Laggoune. "Condition based opportunistic preventive maintenance policy for utility systems with both economic and structural dependencies − application to a gas supply network." International Journal of Pressure Vessels and Piping 165 (August 2018): 214–23. http://dx.doi.org/10.1016/j.ijpvp.2018.07.001.
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BOVSH, Liudmіla, Larysa HOPKALO, Inna LEVYTSKA, Igor KOMARNITSKYI, and Alla RASULOVA. "Simulation of Behavior of Hotel and Restaurant Business Staff in the Conditions of COVID-19 Viral Pandemic." Journal of Environmental Management and Tourism 12, no. 1 (February 21, 2021): 186. http://dx.doi.org/10.14505/jemt.12.1(49).16.
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The research views staff behavior as a complex mechanism of motivators through the lens of rationality, which obeys the principles of the transitivity axiom and the law of declining marginal utility in times of crisis, including the quarantine COVID-19 pandemic, budget constraints. The factors which affect the behavior of hotel and restaurant staff form a field for understanding behavioral responses. The interests and motives that regulate the behavior of the staff, in this case, reflect the map of utility, which allows modeling the usefulness of employment in an enterprise. It is substantiated that the behavior of the staff should be correlated with the influence of leadership and agile management methods (Scrum, Kanban). The Agile determinants in the pandemic client-oriented management of the hotel and restaurant business provide an algorithmic explanation for the application of the approaches in practice. Flexible management methods allow you to create organizational values for staff, which allows you to build value dependencies within cross-functional team management. The result is the consideration of motivational types of staff and methods for choosing the right Agile approach. It also suggested ways to reformat the hotel and restaurant business in the pandemic and change the professional roles of workers to survive and create conditions for rapid rehabilitation and recovery in the post-quarantine period.
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Kaklauskas, Arturas, Edmundas Kazimieras Zavadskas, Arune Binkyte-Veliene, Agne Kuzminske, Justas Cerkauskas, Alma Cerkauskiene, and Rita Valaitiene. "Multiple Criteria Evaluation of the EU Country Sustainable Construction Industry Lifecycles." Applied Sciences 10, no. 11 (May 28, 2020): 3733. http://dx.doi.org/10.3390/app10113733.
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This article looks at the trends and success of the sustainable construction industries in the EU member states, the UK and Norway. The research, covering the past three decades, revealed that different quality of life, macroeconomic, human development, construction and well-being factors define the sustainable construction industries in the EU member states, the UK and Norway. A multiple criteria decision matrix was created and analysed to look at the EU member countries, the UK and Norway from the perspective of their macro level environment and construction industries. Assessments of the sustainable construction industries were completed by using the COmplex PRoportional Assessment (COPRAS) and Degree of Project Utility and Investment Value Assessments (INVAR), two analysis methods. A look was taken at the dependencies linking the indicators related to the construction industries and macro level in the EU member countries, the UK and Norway. Then, the multiple criteria analysis of the construction industry’s utility degree and performances were completed, and recommendations were generated. A country’s perceived image and success can influence the economic behaviour of consumers. By and large, advanced and successful countries rarely become associated with a negative national image and their products and services rarely suffer negative consequences due to such association. This research, then, offers findings that can assist potential buyers in more rational decision-making when choosing of products and services based on a country of origin.
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Zhang, Yue, and Stephen Clark. "Discriminative Syntax-Based Word Ordering for Text Generation." Computational Linguistics 41, no. 3 (September 2015): 503–38. http://dx.doi.org/10.1162/coli_a_00229.
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Word ordering is a fundamental problem in text generation. In this article, we study word ordering using a syntax-based approach and a discriminative model. Two grammar formalisms are considered: Combinatory Categorial Grammar (CCG) and dependency grammar. Given the search for a likely string and syntactic analysis, the search space is massive, making discriminative training challenging. We develop a learning-guided search framework, based on best-first search, and investigate several alternative training algorithms. The framework we present is flexible in that it allows constraints to be imposed on output word orders. To demonstrate this flexibility, a variety of input conditions are considered. First, we investigate a “pure” word-ordering task in which the input is a multi-set of words, and the task is to order them into a grammatical and fluent sentence. This task has been tackled previously, and we report improved performance over existing systems on a standard Wall Street Journal test set. Second, we tackle the same reordering problem, but with a variety of input conditions, from the bare case with no dependencies or POS tags specified, to the extreme case where all POS tags and unordered, unlabeled dependencies are provided as input (and various conditions in between). When applied to the NLG 2011 shared task, our system gives competitive results compared with the best-performing systems, which provide a further demonstration of the practical utility of our system.
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Joughin, Brian A., Chengcheng Liu, Douglas A. Lauffenburger, Christopher W. V. Hogue, and Michael B. Yaffe. "Protein kinases display minimal interpositional dependence on substrate sequence: potential implications for the evolution of signalling networks." Philosophical Transactions of the Royal Society B: Biological Sciences 367, no. 1602 (September 19, 2012): 2574–83. http://dx.doi.org/10.1098/rstb.2012.0010.
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Characterization of in vitro substrates of protein kinases by peptide library screening provides a wealth of information on the substrate specificity of kinases for amino acids at particular positions relative to the site of phosphorylation, but provides no information concerning interdependence among positions. High-throughput techniques have recently made it feasible to identify large numbers of in vivo kinase substrates. We used data from experiments on the kinases ATM/ATR and CDK1, and curated CK2 substrates to evaluate the prevalence of interactions between substrate positions within a motif and the utility of these interactions in predicting kinase substrates. Among these data, evidence of interpositional sequence dependencies is strikingly rare, and what dependency exists does little to aid in the prediction of novel kinase substrates. Significant increases in the ability of models to predict kinase–substrate specificity beyond position-independent models must come largely from inclusion of elements of biological and cellular context, rather than further analysis of substrate sequences alone. Our results suggest that, evolutionarily, kinase substrate fitness exists in a smooth energetic landscape. Taken with results from others indicating that phosphopeptide-binding domains do exhibit interpositional dependence, our data suggest that incorporation of new substrate molecules into phospho-signalling networks may be rate-limited by the evolution of suitability for binding by phosphopeptide-binding domains.
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Dickinson, Quinn, and Jesse G. Meyer. "Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences." PLOS Computational Biology 18, no. 1 (January 28, 2022): e1009736. http://dx.doi.org/10.1371/journal.pcbi.1009736.
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Machine learning with multi-layered artificial neural networks, also known as “deep learning,” is effective for making biological predictions. However, model interpretation is challenging, especially for sequential input data used with recurrent neural network architectures. Here, we introduce a framework called “Positional SHAP” (PoSHAP) to interpret models trained from biological sequences by utilizing SHapely Additive exPlanations (SHAP) to generate positional model interpretations. We demonstrate this using three long short-term memory (LSTM) regression models that predict peptide properties, including binding affinity to major histocompatibility complexes (MHC), and collisional cross section (CCS) measured by ion mobility spectrometry. Interpretation of these models with PoSHAP reproduced MHC class I (rhesus macaque Mamu-A1*001 and human A*11:01) peptide binding motifs, reflected known properties of peptide CCS, and provided new insights into interpositional dependencies of amino acid interactions. PoSHAP should have widespread utility for interpreting a variety of models trained from biological sequences.
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George, Mathew, and Alexandra Smith. "Use of an Abbreviated Geriatric Screening Tool in the Assessment of Older Cancer Patients’ Functional Status, Dependency, and Comorbidities: Cross-Sectional Audit and Observations From a Regional Cancer Center in Australia." JMIR Cancer 6, no. 1 (April 7, 2020): e16408. http://dx.doi.org/10.2196/16408.
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Background Malignancies are the leading cause of disease burden in Australia, comprising 19% of total diseases. Approximately 1 in 4 men and 1 in 6 women die from malignancies by 85 years of age, with patients aged 65 years and older contributing to 58% of diagnoses and 76% of cancer mortality. In the context of malignancy-related disease and age-related degeneration, there is a need for comprehensive assessment of older patients to plan for appropriate management and predict prognosis. The utility of available comprehensive geriatric assessment tools has been limited in routine practice because of their time-consuming nature, despite their informing clearer understanding of patients’ functional status, better clinical decision making, prevention of unpredictable admissions and emergency department overload, and support services planning. Though there are several promising tools available, there is a lack of literature on tools that can comprehensively assess functional status in an expedited fashion. Objective This study aimed to document functional status and comorbidities among a geriatric oncology patient cohort attending a regionally located, dedicated cancer care facility, using the completed Adelaide tool assessments. This study documents cohort characteristics, including sociodemographics, malignancy type, and comorbidities. Secondarily, we observed the utility of an abridged functional assessment in the multidisciplinary team (MDT) management of older cancer patients. Methods The study comprised a facility-based cross-sectional audit of results obtained from a screening tool administered to patients aged 65 years and older and attending an outpatient medical oncology clinic for management of cancer from late 2015 to 2017. Data relating to five domains were collected, including instrumental activities of daily living, activities of daily living, performance status, unintended weight loss, and exhaustion. Sociodemographic and disease-related factors were summarized as frequencies with percentages or mean with SD. Distribution of functional status based on sociodemographic characteristics, living status, disease-related factors, and comorbidities was analyzed using a chi-square test. Cumulative dependencies in the five domains were identified, and patients were classified as fit, vulnerable, or frail. Supplementary review of presentation notes for cases discussed at MDT meetings was undertaken to identify discrepancies. Results A majority of the study population showed poor functional status, with 88.7% (243/274) categorized as vulnerable and 8.4% (23/274) as frail. Exhaustion and unintended weight loss were identified as the most common contributors to dependency. Polypharmacy was strongly associated with decreased functional status. Conclusions The outcomes of this study are congruent with the existence of dependency in various domains, and with similar research in geriatric oncology. The Adelaide tool provided a useful basis for MDT discussion and management, where cases were referred to the MDT. We recommend further examination of the tool’s utility and impact in clinical decision making, and the distribution of dependencies in a rural cohort compared with metropolitan patients.
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Sabnis, Amit J., Christopher J. Guerriero, Victor Olivas, Anin Sayana, Jonathan Shue, Jennifer Flanagan, Saurabh Asthana, et al. "Combined chemical–genetic approach identifies cytosolic HSP70 dependence in rhabdomyosarcoma." Proceedings of the National Academy of Sciences 113, no. 32 (July 22, 2016): 9015–20. http://dx.doi.org/10.1073/pnas.1603883113.
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Cytosolic and organelle-based heat-shock protein (HSP) chaperones ensure proper folding and function of nascent and injured polypeptides to support cell growth. Under conditions of cellular stress, including oncogenic transformation, proteostasis components maintain homeostasis and prevent apoptosis. Although this cancer-relevant function has provided a rationale for therapeutically targeting proteostasis regulators (e.g., HSP90), cancer-subtype dependencies upon particular proteostasis components are relatively undefined. Here, we show that human rhabdomyosarcoma (RMS) cells, but not several other cancer cell types, depend upon heat-shock protein 70 kDA (HSP70) for survival. HSP70-targeted therapy (but not chemotherapeutic agents) promoted apoptosis in RMS cells by triggering an unfolded protein response (UPR) that induced PRKR-like endoplasmic reticulum kinase (PERK)–eukaryotic translation initiation factor α (eIF2α)–CEBP homologous protein (CHOP) signaling and CHOP-mediated cell death. Intriguingly, inhibition of only cytosolic HSP70 induced the UPR, suggesting that the essential activity of HSP70 in RMS cells lies at the endoplasmic reticulum–cytosol interface. We also found that increased CHOP mRNA in clinical specimens was a biomarker for poor outcomes in chemotherapy-treated RMS patients. The data suggest that, like human epidermal growth factor receptor 2 (HER2) amplification in breast cancer, increased CHOP in RMS is a biomarker of decreased response to chemotherapy but enhanced response to targeted therapy. Our findings identify the cytosolic HSP70–UPR axis as an unexpected regulator of RMS pathogenesis, revealing HSP70-targeted therapy as a promising strategy to engage CHOP-mediated apoptosis and improve RMS treatment. Our study highlights the utility of dissecting cancer subtype-specific dependencies on proteostasis networks to uncover unanticipated cancer vulnerabilities.
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Shin, Kayoung, Hyemi Shin, Hee Jin Cho, Hyunju Kang, Jin-Ku Lee, Yun Jee Seo, Yong Jae Shin, et al. "Sphere-Forming Culture for Expanding Genetically Distinct Patient-Derived Glioma Stem Cells by Cellular Growth Rate Screening." Cancers 12, no. 3 (February 27, 2020): 549. http://dx.doi.org/10.3390/cancers12030549.
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Diffusely infiltrating gliomas (DIGs) are difficult to completely resect and are associated with a high rate of tumor relapse and progression from low- to high-grade glioma. In particular, optimized short-term culture-enriching patient-derived glioma stem cells (GSCs) are essential for customizing the therapeutic strategy based on clinically feasible in vitro drug screening for a wide range of DIGs, owing to the high inter-tumoral heterogeneity. Herein, we constructed a novel high-throughput culture condition screening platform called ‘GFSCAN’, which evaluated the cellular growth rates of GSCs for each DIG sample in 132 serum-free combinations, using 13 previously reported growth factors closely associated with glioma aggressiveness. In total, 72 patient-derived GSCs with available genomic profiles were tested in GFSCAN to explore the association between cellular growth rates in specific growth factor combinations and genomic/molecular backgrounds, including isocitrate dehydrogenase 1 (IDH1) mutation, chromosome arm 1p and 19q co-deletion, ATRX chromatin remodeler alteration, and transcriptional subtype. GSCs were clustered according to the dependency on epidermal growth factor and basic fibroblast growth factor (E&F), and isocitrate dehydrogenase 1 (IDH1) wild-type GSCs showed higher E&F dependencies than IDH1 mutant GSCs. More importantly, we elucidated optimal combinations for IDH1 mutant glioblastoma and lower grade glioma GSCs with low dependencies on E&F, which could be an aid in clinical decision-making for these DIGs. Thus, we demonstrated the utility of GFSCAN in personalizing in vitro cultivation to nominate personalized therapeutic options, in a clinically relevant time frame, for individual DIG patients, where standard clinical options have been exhausted.
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Koopmans, Matthijs. "Estimating Perturbation and Meta-Stability in the Daily Attendance Rates of Six Small High Schools." Fluctuation and Noise Letters 16, no. 03 (August 21, 2017): 1750021. http://dx.doi.org/10.1142/s0219477517500213.
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This paper discusses the daily attendance rates in six small high schools over a ten-year period and evaluates how stable those rates are. “Stability” is approached from two vantage points: pulse models are fitted to estimate the impact of sudden perturbations and their reverberation through the series, and Autoregressive Fractionally Integrated Moving Average (ARFIMA) techniques are used to detect dependencies over the long range of the series. The analyses are meant to (1) exemplify the utility of time series approaches in educational research, which lacks a time series tradition, (2) discuss some time series features that seem to be particular to daily attendance rate trajectories such as the distinct downward pull coming from extreme observations, and (3) present an analytical approach to handle the important yet distinct patterns of variability that can be found in these data. The analysis also illustrates why the assumption of stability that underlies the habitual reporting of weekly, monthly and yearly averages in the educational literature is questionable, as it reveals dynamical processes (perturbation, meta-stability) that remain hidden in such summaries.
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Baum, Eric B., and Warren D. Smith. "Propagating Distributions Up Directed Acyclic Graphs." Neural Computation 11, no. 1 (January 1, 1999): 215–27. http://dx.doi.org/10.1162/089976699300016881.
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In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding on a move after search was completed. In some games, such as chess and Othello, the same position can occur more than once, collapsing the game tree to a directed acyclic graph (DAG). This induces correlations among the distributions at sibling nodes. This article discusses some issues that arise in extending our algorithms to a DAG. We give a simply described algorithm for correctly propagating distributions up a game DAG, taking account of dependencies induced by the DAG structure. This algorithm is exponential time in the worst case. We prove that it is #P complete to propagate distributions up a game DAG correctly. We suggest how our exact propagation algorithm can yield a fast but inexact heuristic.
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Benini, Sergio, Pierangelo Migliorati, and Riccardo Leonardi. "Statistical Skimming of Feature Films." International Journal of Digital Multimedia Broadcasting 2010 (2010): 1–11. http://dx.doi.org/10.1155/2010/709161.
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We present a statistical framework based on Hidden Markov Models(HMMs)for skimming feature films. A chain ofHMMsis used to model subsequent story units:HMMstates represent different visual-concepts, transitions model the temporal dependencies in each story unit, and stochastic observations are given by single shots. The skim is generated as an observation sequence, where, in order to privilege more informative segments for entering the skim, shots are assigned higher probability of observation if endowed with salient features related to specific film genres. The effectiveness of the method is demonstrated by skimming the first thirty minutes of a wide set of action and dramatic movies, in order to create previews for users useful for assessing whether they would like to see that movie or not, but without revealing the movie central part and plot details. Results are evaluated and compared through extensive user tests in terms of metrics that estimate the content representational value of the obtained video skims and their utility for assessing the user's interest in the observed movie.
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De Conti, Giulia, Alicja M. Gruszka, Debora Valli, Andrea Umberto Cammarata, Matteo Righi, Massimiliano Mazza, and Pier Giuseppe Pelicci. "A Novel Platform to Test In Vivo Single Gene Dependencies in t(8,21) and t(15,17) AML Confirms Zeb2 as Leukemia Target." Cancers 12, no. 12 (December 14, 2020): 3768. http://dx.doi.org/10.3390/cancers12123768.
Full textAbstract:
The increased usage of high-throughput technologies in cancer research, including genetic and drug screens, generates large sets of candidate targets that need to be functionally validated for their roles in tumor development. Thus, reliable and robust in vivo model systems are needed to perform reverse genetic experiments. Ideally, these models should allow for a conditional silencing of the target and an unambiguous identification of engineered cancer cells. Here, we present a platform consisting of: (i) t(8;21) and t(15;17) driven acute myeloid leukemia (AML) transgenic mice with constitutive expression of green fluorescent protein (GFP) and inducible expression of Cre recombinase, and (ii) REX, a modified pSico lentiviral vector for inducible shRNA expression and red fluorescent protein (RFP) as a selection marker. In this system, leukemic cells from transgenic mice are transduced with REX, flow sorted, and transplanted into syngeneic hosts. Gene interference is induced in established tumors by tamoxifen treatment. Dual-color cell fluorescence guides the in vivo identification of shRNA interfered AML cells, monitoring engraftment and disease progression. We tested the platform by inducing knockdown of Zeb2, a gene upregulated by AML1-ETO and PML-RARα oncogenes in pre-leukemic hematopoietic stem cell compartment, and observed a significant delay in leukemia onset. This proves the power and utility of the platform and confirms Zeb2 contribution to the pathogenesis of AML.
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Husain, Benafsh, Allison R. Hickman, Yuqing Hang, Benjamin T. Shealy, Karan Sapra, and F. Alex Feltus. "NetExtractor: Extracting a Cerebellar Tissue Gene Regulatory Network Using Differentially Expressed High Mutual Information Binary RNA Profiles." G3 Genes|Genomes|Genetics 10, no. 9 (September 1, 2020): 2953–63. http://dx.doi.org/10.1534/g3.120.401067.
Full textAbstract:
Abstract Bigenic expression relationships are conventionally defined based on metrics such as Pearson or Spearman correlation that cannot typically detect latent, non-linear dependencies or require the relationship to be monotonic. Further, the combination of intrinsic and extrinsic noise as well as embedded relationships between sample sub-populations reduces the probability of extracting biologically relevant edges during the construction of gene co-expression networks (GCNs). In this report, we address these problems via our NetExtractor algorithm. NetExtractor examines all pairwise gene expression profiles first with Gaussian mixture models (GMMs) to identify sample sub-populations followed by mutual information (MI) analysis that is capable of detecting non-linear differential bigenic expression relationships. We applied NetExtractor to brain tissue RNA profiles from the Genotype-Tissue Expression (GTEx) project to obtain a brain tissue specific gene expression relationship network centered on cerebellar and cerebellar hemisphere enriched edges. We leveraged the PsychENCODE pre-frontal cortex (PFC) gene regulatory network (GRN) to construct a cerebellar cortex (cerebellar) GRN associated with transcriptionally active regions in cerebellar tissue. Thus, we demonstrate the utility of our NetExtractor approach to detect biologically relevant and novel non-linear binary gene relationships.