Journal articles: 'MAPS pathway'

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Nersisyan, Lilit, Ruben Samsonyan, and Arsen Arakelyan. "CyKEGGParser: tailoring KEGG pathways to fit into systems biology analysis workflows." F1000Research 3 (August 14, 2014): 145. http://dx.doi.org/10.12688/f1000research.4410.2.

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The KEGG pathway database is a widely accepted source for biomolecular pathway maps. In this paper we present the CyKEGGParser app (http://apps.cytoscape.org/apps/cykeggparser) for Cytoscape 3 that allows manipulation with KEGG pathway maps. Along with basic functionalities for pathway retrieval, visualization and export in KGML and BioPAX formats, the app provides unique features for computer-assisted adjustment of inconsistencies in KEGG pathway KGML files and generation of tissue- and protein-protein interaction specific pathways. We demonstrate that using biological context-specific KEGG pathways created with CyKEGGParser makes systems biology analysis more sensitive and appropriate compared to original pathways.

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Koblitz, Julia, Dietmar Schomburg, and Meina Neumann-Schaal. "MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context." F1000Research 9 (April 24, 2020): 288. http://dx.doi.org/10.12688/f1000research.23427.1.

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Metabolic pathways are an important part of systems biology research since they illustrate complex interactions between metabolites, enzymes, and regulators. Pathway maps are drawn to elucidate metabolism or to set data in a metabolic context. We present MetaboMAPS, a web-based platform to visualize numerical data on individual metabolic pathway maps. Metabolic maps can be stored, distributed and downloaded in SVG-format. MetaboMAPS was designed for users without computational background and supports pathway sharing without strict conventions. In addition to existing applications that established standards for well-studied pathways, MetaboMAPS offers a niche for individual, customized pathways beyond common knowledge, supporting ongoing research by creating publication-ready visualizations of experimental data.

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Koblitz, Julia, Dietmar Schomburg, and Meina Neumann-Schaal. "MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context." F1000Research 9 (July 17, 2020): 288. http://dx.doi.org/10.12688/f1000research.23427.2.

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Metabolic pathways are an important part of systems biology research since they illustrate complex interactions between metabolites, enzymes, and regulators. Pathway maps are drawn to elucidate metabolism or to set data in a metabolic context. We present MetaboMAPS, a web-based platform to visualize numerical data on individual metabolic pathway maps. Metabolic maps can be stored, distributed and downloaded in SVG-format. MetaboMAPS was designed for users without computational background and supports pathway sharing without strict conventions. In addition to existing applications that established standards for well-studied pathways, MetaboMAPS offers a niche for individual, customized pathways beyond common knowledge, supporting ongoing research by creating publication-ready visualizations of experimental data.

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Mantoro, Teddy, Adamu I. Abubakar, and Media A. Ayu. "3D Maps in Mobile Devices." International Journal of Mobile Computing and Multimedia Communications 5, no. 3 (July 2013): 88–106. http://dx.doi.org/10.4018/jmcmc.2013070106.

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Pathway analysis provided by current 3D maps in mobile devices that are intended for an interactive navigation aid, is simulated for what-if experiments against task and functional analysis, based on the problems faced from both technical and user-practices views. The aim of a navigation aid, in general, is to provide an optimal route from the current position to the destination. Unfortunately, the problem of most mobile device’s GPS signal accuracy and the display of pathways on 3D maps in the small screen of mobile devices affects the pathway architectural design from generating accurate initial positions to destinations. This paper presents both conceptual and experimental analysis of pathway determination designed for 3D maps in mobile devices for an interactive navigation aid, which is going to be added to an existing individual cognitive map. The analytical outcomes are aimed at providing how environmental conditions come to be detected and how problems are resolved in helping people to navigate in unfamiliar locations by having positions and paths corrected to a reasonable degree of accuracy in order to overcome the problems of generating in-accurate locations and the weaknesses of conventional 2D maps, which requires users to interpret its various symbols and legends. Bent functions and fuzzy logic type 2 are used for simulating signal deviations from the precise values and Voronoi diagram/Delaunay triangulation are used for establishing experimental paths and locations. Finally, this technique will contribute to a well-defined positioning and pathway establishment of 3D maps in mobile devices for navigation aid.

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Walke, Daniel, Kay Schallert, Prasanna Ramesh, Dirk Benndorf, Emanuel Lange, Udo Reichl, and Robert Heyer. "MPA_Pathway_Tool: User-Friendly, Automatic Assignment of Microbial Community Data on Metabolic Pathways." International Journal of Molecular Sciences 22, no. 20 (October 12, 2021): 10992. http://dx.doi.org/10.3390/ijms222010992.

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Taxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versality of microbial metabolism and a still-increasing number of newly biological pathways, linkage to standard pathway maps such as the KEGG central carbon metabolism is often problematic. We successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called ‘Pathway-Creator’ and ‘Pathway-Calculator’. The ‘Pathway-Creator’ enables an easy set-up of user-defined pathways with specific taxonomic constraints. The ‘Pathway-Calculator’ automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. The MPA_Pathway_Tool is implemented in Java and ReactJS.

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Szachniuk, Marta, Maria Cristina De Cola, Giovanni Felici, Dominique de Werra, and Jacek Błażewicz. "Optimal pathway reconstruction on 3D NMR maps." Discrete Applied Mathematics 182 (February 2015): 134–49. http://dx.doi.org/10.1016/j.dam.2014.04.010.

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Ghedira, Kais, Soumaya Kouidhi, Yosr Hamdi, Houcemeddine Othman, Sonia Kechaou, Sadri Znaidi, Sghaier Haïtham, and Imen Rabhi. "Pathway Maps of Orphan and Complex Diseases Using an Integrative Computational Approach." BioMed Research International 2020 (November 27, 2020): 1–11. http://dx.doi.org/10.1155/2020/4280467.

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Orphan diseases (ODs) are progressive genetic disorders, which affect a small number of people. The principal fundamental aspects related to these diseases include insufficient knowledge of mechanisms involved in the physiopathology necessary to access correct diagnosis and to develop appropriate healthcare. Unlike ODs, complex diseases (CDs) have been widely studied due to their high incidence and prevalence allowing to understand the underlying mechanisms controlling their physiopathology. Few studies have focused on the relationship between ODs and CDs to identify potential shared pathways and related molecular mechanisms which would allow improving disease diagnosis, prognosis, and treatment. We have performed a computational approach to studying CDs and ODs relationships through (1) connecting diseases to genes based on genes-diseases associations from public databases, (2) connecting ODs and CDs through binary associations based on common associated genes, and (3) linking ODs and CDs to common enriched pathways. Among the most shared significant pathways between ODs and CDs, we found pathways in cancer, p53 signaling, mismatch repair, mTOR signaling, B cell receptor signaling, and apoptosis pathways. Our findings represent a reliable resource that will contribute to identify the relationships between drugs and disease-pathway networks, enabling to optimise patient diagnosis and disease treatment.

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Hu, Chenyu W., Amina A. Qutub, Yihua Qiu, Suk Young Yoo, Nianxiang Zhang, Naveen Pammaraju, Courtney D. DiNardo, Kevin R. Coombes, and Steven M. Kornblau. "A Global Proteomic Pathway Map In Acute Myeloid Leukemia (AML)." Blood 122, no. 21 (November 15, 2013): 1302. http://dx.doi.org/10.1182/blood.v122.21.1302.1302.

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Abstract Background AML has been extensively studied in a gene-to-gene and pathway-to-pathway fashion over the years, unraveling insightful local patterns that capture heterogeneity in patients and identify potential drug targets. However, our understanding of AML from a global and systems perspective is still lacking. A global proteomic pathway map is yet to be drawn to integrate local activity patterns and to translate patient classifications across pathways. This will not only improve our scientific understanding of how different functional pathways are inter-related, but will also enable us to develop more robust and effective therapeutic regimens based on pathway cross-talks. Methods A proteomic profile, containing the expression pattern of 231 proteins in each of the 415 newly diagnosed AML patients at UT MD Anderson Cancer Center, was generated using the Reverse Phase Protein Array (RPPA) technology. We grouped these proteins into 23 functional pathways based on protein association known in literature and correlation shown in the proteomic profile. Principal component analysis and scree plot were used to refine the pathway construction. The AML patients were clustered by their protein expression patterns within each individual pathway, and were then compared across pathways. The association of patient clusters between different pathways was measured by Goodman-Kruskal's (GK) tau method, indicating the predictability of patient clustering in one pathway given that in the other. This association between pathways and interchangeability of patient groupings were visualized in a circos plot (Figure 1), depicting a global proteomic pathway map. Results The global proteomic pathway map illustrates how strongly protein expression patterns of different pathways are associated, and how patient classifications under different pathways could be translated from one to another. Here, we highlight some of the key insights surfaced from this analysis. First, we identified ‘social' pathways that have intensive cross-talks with multiple other pathways, including some of the cell signal transduction pathways (MEK, PI3K, mTOR), genetic information processing pathways (transcription, histone methylation), and cell survival/death pathways (apoptosis, autophagy). We also identified ‘orphan' pathways that are more independent and are poorly associated with others. These include a subset of signal transduction pathways (pkc, tp53, S6rp, Src, Creb, Wnt), cytoskeleton and differentiation. As the association is directional, each pathway could be further characterized as either a ‘sender' or a ‘receiver' pathway based on whether it is acting more as the origin or the target of the link. The patient clusters from the ‘sender' pathways (e.g. Apoptosis, mTOR, Fli), could be easily translated to other pathways, while the patient clusters in ‘receiver' pathways (e.g. Hippo and Transcription), are highly predictable by patient clusters from multiple other pathways. We further constructed and compared the global pathway maps for patients in different cytogenetic groups. Comparison of pathway maps from patients with favorable, intermediate and unfavorable cytogenetics shows the power of this methodology to discern differences in the degree of correlation between protein functional groups. Favorable cytogenetics (T8;21) and inversion 16, because they are more similar have less patient to patient variation and thus have a more consistent and highly correlated pathway map with a higher number of connections. Conclusions Based on the RPPA data in AML patients, we built a global proteomic pathway map that captures the association between protein expression patterns in defined protein functional groups. We identified intensive interacting pathways as well as independent pathways, which indicate potential hubs and modulators of leukemic cell behavior. We further compared maps of different cytogenetic groups and revealed different correlation mappings. We are further refining the algorithms in order to study more focused changes within lower population subsets. Ultimately we believe that this will enable the matching of targeted agents to specific settings where the target is expressed and highly interactive based on proteomic data. Disclosures: No relevant conflicts of interest to declare.

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Kuenzi, Brent M., and Trey Ideker. "A census of pathway maps in cancer systems biology." Nature Reviews Cancer 20, no. 4 (February 17, 2020): 233–46. http://dx.doi.org/10.1038/s41568-020-0240-7.

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Ortigosa, Nuria, Samuel Morillas, and Guillermo Peris-Fajarnés. "Obstacle-Free Pathway Detection by Means of Depth Maps." Journal of Intelligent & Robotic Systems 63, no. 1 (November 3, 2010): 115–29. http://dx.doi.org/10.1007/s10846-010-9498-4.

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Arakelyan, Arsen, and Lilit Nersisyan. "KEGGParser: parsing and editing KEGG pathway maps in Matlab." Bioinformatics 29, no. 4 (January 3, 2013): 518–19. http://dx.doi.org/10.1093/bioinformatics/bts730.

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Balci, Hasan, Ugur Dogrusoz, Yusuf Ziya Ozgul, and Perman Atayev. "SyBLaRS: A web service for laying out, rendering and mining biological maps in SBGN, SBML and more." PLOS Computational Biology 18, no. 11 (November 14, 2022): e1010635. http://dx.doi.org/10.1371/journal.pcbi.1010635.

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Visualization is a key recurring requirement for effective analysis of relational data. Biology is no exception. It is imperative to annotate and render biological models in standard, widely accepted formats. Finding graph-theoretical properties of pathways as well as identifying certain paths or subgraphs of interest in a pathway are also essential for effective analysis of pathway data. Given the size of available biological pathway data nowadays, automatic layout is crucial in understanding the graphical representations of such data. Even though there are many available software tools that support graphical display of biological pathways in various formats, there is none available as a service for on-demand or batch processing of biological pathways for automatic layout, customized rendering and mining paths or subgraphs of interest. In addition, there are many tools with fine rendering capabilities lacking decent automatic layout support. To fill this void, we developed a web service named SyBLaRS (Systems Biology Layout and Rendering Service) for automatic layout of biological data in various standard formats as well as construction of customized images in both raster image and scalable vector formats of these maps. Some of the supported standards are more generic such as GraphML and JSON, whereas others are specialized to biology such as SBGNML (The Systems Biology Graphical Notation Markup Language) and SBML (The Systems Biology Markup Language). In addition, SyBLaRS supports calculation and highlighting of a number of well-known graph-theoretical properties as well as some novel graph algorithms turning a specified set of objects of interest to a minimal pathway of interest. We demonstrate that SyBLaRS can be used both as an offline layout and rendering service to construct customized and annotated pictures of pathway models and as an online service to provide layout and rendering capabilities for systems biology software tools. SyBLaRS is open source and publicly available on GitHub and freely distributed under the MIT license. In addition, a sample deployment is available here for public consumption.

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Kono, Nobuaki, Kazuharu Arakawa, Ryu Ogawa, Nobuhiro Kido, Kazuki Oshita, Keita Ikegami, Satoshi Tamaki, and Masaru Tomita. "Pathway Projector: Web-Based Zoomable Pathway Browser Using KEGG Atlas and Google Maps API." PLoS ONE 4, no. 11 (November 11, 2009): e7710. http://dx.doi.org/10.1371/journal.pone.0007710.

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Pine, Alexander B., Ayesha Butt, Rolando Garcia-Milian, Sean X. Gu, Valentina Restrepo, Yu Pei Chock, John Hwa, et al. "Proteomic Profiling of Different Antiphospholipid Antibody-Positive Phenotypes: Results from Antiphospholipid Syndrome Alliance for Clinical Trials and International Networking (APS ACTION) Registry." Blood 142, Supplement 1 (November 28, 2023): 2575. http://dx.doi.org/10.1182/blood-2023-185232.

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Background. Antiphospholipid syndrome (APS) is an autoimmune disease with thrombotic and obstetric complications arising via a model of immunothrombosis. Patients may present with a spectrum of phenotypes, including thrombotic (tAPS), obstetric (oAPS), or catastrophic/microvascular APS (C/MAPS), while others may have antiphospholipid antibodies (aPL) without disease manifestations. The mechanisms underlying the development of these diverse phenotypes remain uncertain. Proteomic profiling was used in other thrombotic and microvascular disorders to highlight potential mechanisms of disease pathogenesis and may have a role in understanding the pathophysiology of APS. We performed multiplex plasma proteomic profiling in aPL-positive patients with different clinical phenotypes to gain a greater understanding of potential immunothrombotic mechanisms in the pathogenesis of APS. Methods. We utilized samples from APS ACTION Registry. The inclusion criteria were positive aPL per Updated Sapporo Classification Criteria tested within one year prior to the enrollment. Multiplex proteomic profiling measuring approximately 7,000 unique proteins (SomaLogic; Boulder, CO, USA) was performed on 40 primary aPL-positive patient plasma samples (10 each of tAPS with/without oAPS, oAPS only, C/MAPS, and positive aPL without APS classification), and 10 of healthy controls. Differentially abundant proteins among all phenotypic groups and in pairwise comparisons were determined by applying ANOVA and t-tests to log-normalized data, respectively, with p-values <0.05 considered statistically significant (Qlucore Omics Explorer, Lund, Sweden). Tests were adjusted for false discovery (q<0.1) to minimize the likelihood of false positives. Pathway enrichment analysis was performed using Metascape (https://metascape.org) and Ingenuity IPA (Qiagen, Venlo, Netherlands) platforms. Results. The median age of patients was 48 years; 30% were men, 70% had triple aPL-positivity, and no one had a concurrent diagnosis of lupus. A set of concordant and differentially abundant proteins clustered patients with 4 APS clinical phenotypes and controls (Figure A) with a high statistical significance (p<0.0007) and a high false discovery confidence (q<0.05). Proteins in the identified set belonged to several highly enriched pathways such as neutrophil degranulation (p<10 -10), humoral immune response (p<10 -9), coagulation (p<10 -6), and alternative complement (p<10 -5) [data not shown]. Pathway enrichment analysis of protein sets identified in pairwise comparisons of APS phenotypes (aPL vs C/MAPS, aPL vs tAPS, tAPS vs C/MAPS) revealed involvement of several common pathways associated with inflammation, collagen and fibroblast signaling, cellular and cytoskeletal activation, humoral immune response, myeloid and effector cell differentiation and recruitment, and immunothrombosis such as Pathogen-Induced Cytokine Storm, Neutrophil Extracellular Trap (NET), and collagen-induced platelet-activating GP6 signaling (Figure B). For several pathways, the measure of activation related to increased or predicted to be increased proteins annotated within a particular pathway positively correlated with the clinical “distance” between APS subtypes, from the most clinically related C/MAPS vs tAPS to the most distant aPL vs C/MAPS suggesting an “evolution” from one phenotype to a more severe in terms of activation of specific pathways. Specifically notable is the higher activation of the NET signaling pathway in the aPL than in C/MAPS phenotype suggesting that the presence of aPL antibodies activates this immunothrombotic pathway. Conclusions. Plasma proteome of APS subtypes is characterized by alteration in several cellular processes, particularly receptor signaling, signal transduction, regulation of cellular differentiation, neutrophil, complement, coagulation and cytokine activation notable in all individuals with aPL-positivity. Pathways activated in the non-thrombotic (aPL) phenotype and escalating activation of several pathways from non-thrombotic to the most thrombotic (C/MAPS) phenotype provide important data for the understanding of APS pathogenesis and informing the model of APS-related immunothrombosis.

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OLSSON, BJÖRN, BARBARA GAWRONSKA, and BJÖRN ERLENDSSON. "DERIVING PATHWAY MAPS FROM AUTOMATED TEXT ANALYSIS USING A GRAMMAR-BASED APPROACH." Journal of Bioinformatics and Computational Biology 04, no. 02 (April 2006): 483–501. http://dx.doi.org/10.1142/s0219720006002041.

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We demonstrate how automated text analysis can be used to support the large-scale analysis of metabolic and regulatory pathways by deriving pathway maps from textual descriptions found in the scientific literature. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. Our method uses an algorithm that searches through the syntactic trees produced by a parser based on a Referent Grammar formalism, identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses). The semantic categories used in the classification are based on the relation set used in KEGG (Kyoto Encyclopedia of Genes and Genomes), so that pathway maps using KEGG notation can be automatically generated. We present the current version of the relation extraction algorithm and an evaluation based on a corpus of abstracts obtained from PubMed. The results indicate that the method is able to combine a reasonable coverage with high accuracy. We found that 61% of all sentences were parsed, and 97% of the parse trees were judged to be correct. The extraction algorithm was tested on a sample of 300 parse trees and was found to produce correct extractions in 90.5% of the cases.

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Nersisyan, Lilit, Henry Löffler-Wirth, Arsen Arakelyan, and Hans Binder. "Gene Set- and Pathway- Centered Knowledge Discovery Assigns Transcriptional Activation Patterns in Brain, Blood, and Colon Cancer." International Journal of Knowledge Discovery in Bioinformatics 4, no. 2 (July 2014): 46–69. http://dx.doi.org/10.4018/ijkdb.2014070104.

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Genome-wide ‘omics'-assays provide a comprehensive view on the molecular landscapes of healthy and diseased cells. Bioinformatics traditionally pursues a ‘gene-centered' view by extracting lists of genes differentially expressed or methylated between healthy and diseased states. Biological knowledge mining is then performed by applying gene set techniques using libraries of functional gene sets obtained from independent studies. This analysis strategy neglects two facts: (i) that different disease states can be characterized by a series of functional modules of co-regulated genes and (ii) that the topology of the underlying regulatory networks can induce complex expression patterns that require analysis methods beyond traditional genes set techniques. The authors here provide a knowledge discovery method that overcomes these shortcomings. It combines machine learning using self-organizing maps with pathway flow analysis. It extracts and visualizes regulatory modes from molecular omics data, maps them onto selected pathways and estimates the impact of pathway-activity changes. The authors illustrate the performance of the gene set and pathway signal flow methods using expression data of oncogenic pathway activation experiments and of patient data on glioma, B-cell lymphoma and colorectal cancer.

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Lange, B. Markus, and Majid Ghassemian. "Comprehensive post-genomic data analysis approaches integrating biochemical pathway maps." Phytochemistry 66, no. 4 (February 2005): 413–51. http://dx.doi.org/10.1016/j.phytochem.2004.12.020.

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Kreher, B. W., S. Schnell, I. Mader, K. A. Il'yasov, J. Hennig, V. G. Kiselev, and D. Saur. "Connecting and merging fibres: Pathway extraction by combining probability maps." NeuroImage 43, no. 1 (October 2008): 81–89. http://dx.doi.org/10.1016/j.neuroimage.2008.06.023.

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Chanumolu, Sree K., Mustafa Albahrani, Handan Can, and Hasan H. Otu. "KEGG2Net: Deducing gene interaction networks and acyclic graphs from KEGG pathways." EMBnet.journal 26 (March 5, 2021): e949. http://dx.doi.org/10.14806/ej.26.0.949.

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The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database provides a manual curation of biological pathways that involve genes (or gene products), metabolites, chemical compounds, maps, and other entries. However, most applications and datasets involved in omics are gene or protein-centric requiring pathway representations that include direct and indirect interactions only between genes. Furthermore, special methodologies, such as Bayesian networks, require acyclic representations of graphs. We developed KEGG2Net, a web resource that generates a network involving only the genes represented on a KEGG pathway with all of the direct and indirect gene-gene interactions deduced from the pathway. KEGG2Net offers four different methods to remove cycles from the resulting gene interaction network, converting them into directed acyclic graphs (DAGs). We generated synthetic gene expression data using the gene interaction networks deduced from the KEGG pathways and performed a comparative analysis of different cycle removal methods by testing the fitness of their DAGs to the data and by the number of edges they eliminate. Our results indicate that an ensemble method for cycle removal performs as the best approach to convert the gene interaction networks into DAGs. Resulting gene interaction networks and DAGs are represented in multiple user-friendly formats that can be used in other applications, and as images for quick and easy visualisation. The KEGG2Net web portal converts KEGG maps for any organism into gene-gene interaction networks and corresponding DAGs representing all of the direct and indirect interactions among the genes.Availability: KEGG2Net is freely available at http://otulab.unl.edu/KEGG2Net

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Kuenzi, Brent M., and Trey Ideker. "Author Correction: A census of pathway maps in cancer systems biology." Nature Reviews Cancer 21, no. 3 (January 13, 2021): 212. http://dx.doi.org/10.1038/s41568-021-00331-7.

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Büchel, Finja, Nicolas Rodriguez, Neil Swainston, Clemens Wrzodek, Tobias Czauderna, Roland Keller, Florian Mittag, et al. "Path2Models: large-scale generation of computational models from biochemical pathway maps." BMC Systems Biology 7, no. 1 (2013): 116. http://dx.doi.org/10.1186/1752-0509-7-116.

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Papageorgiou, E., L. F. Ticini, G. Hardiess, F. Schaeffel, H. Wiethoelter, H. A. Mallot, S. Bahlo, et al. "The pupillary light reflex pathway: Cytoarchitectonic probabilistic maps in hemianopic patients." Neurology 70, no. 12 (March 17, 2008): 956–63. http://dx.doi.org/10.1212/01.wnl.0000305962.93520.ed.

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Hung, Fei-Hung, Hung-Wen Chiu, and Yo-Cheng Chang. "Revealing pathway maps of renal cell carcinoma by gene expression change." Computers in Biology and Medicine 51 (August 2014): 111–21. http://dx.doi.org/10.1016/j.compbiomed.2014.04.023.

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Csik, Valerie Pracilio, Michael J. Ramirez, Adam F. Binder, and Nathan Handley. "The value of pathways on drug costs." Journal of Clinical Oncology 39, no. 28_suppl (October 1, 2021): 327. http://dx.doi.org/10.1200/jco.2020.39.28_suppl.327.

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327 Background: Oncology care represents a significant portion of US healthcare spending. Cost of Part B drugs has increased at a rate 5.7x that of overall Medicare spending. As a participant in the Oncology Care Model, drug costs represent a majority of our total costs. Pathways are a clinical decision-support tool that use evidence-based care maps accounting for efficacy, toxicity and cost. Our NCI-designated cancer center implemented pathways in July 2018 to reduce care variation and decrease costs. Methods: We reviewed costs related to pathway utilization over a two year period, analyzing differences in total annual drug cost for patients in three categories: On-Pathway (aligned with pathway recommendation), Off-Pathway (not aligned with recommendation), and No Pathway (not used). Per Member Per Month (PMPM) costs were calculated and a weighted average applied to account for changes in annual drug costs. Results: PMPM drug costs decreased -8% in year 1 (FY19) and -4% in year 2 (FY20) when pathways were used (On- and Off-Pathway). When pathways were followed (On-Pathway) in making treatment decisions, the drug costs were 11% lower than when pathways were not used. The annual impact on drug costs when pathways were used amounted to $2.45 million in year 1 and $1.77 million in year 2 (Table). Conclusions: Pathway use reduced drug costs, a significant variable in oncology value-based care models. This finding highlights the value of clinical decision support tools in reducing care variability, a known contributor to health care costs, in making treatment decisions. Further assessment is needed to determine if these results are similar at other cancer centers to fully realize the impact of pathways on drug costs.[Table: see text]

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Krishnankutty, Sindhu M., Kevin Bigsby, John Hastings, Yu Takeuchi, Yunke Wu, Steven W. Lingafelter, Hannah Nadel, Scott W. Myers, and Ann M. Ray. "Predicting Establishment Potential of an Invasive Wood-Boring Beetle, Trichoferus campestris (Coleoptera: Cerambycidae) in the United States." Annals of the Entomological Society of America 113, no. 2 (February 11, 2020): 88–99. http://dx.doi.org/10.1093/aesa/saz051.

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Abstract Solid wood packaging material (WPM) is widely recognized as a high-risk pathway for transport and potential introduction of wood-boring insects, including longhorned beetles in the family Cerambycidae. These beetles also are occasionally imported in finished wood products, such as furniture and decorative items. A targeted effort to identify wood borers intercepted as larvae in WPM at U.S. ports between 2012 and 2018 revealed that one of the most frequently intercepted species was Trichoferus campestris (Faldermann), a cerambycid native to Asia. Trichoferus campestris is a pest of quarantine concern in the United States, Canada, and Europe. The establishment risk of this beetle in the United States is high because of its frequent introduction through multiple pathways and its potential to inhabit natural and urban forests as well as agricultural systems. In this study, we compiled port interception and detection data to examine risk based on historical introductions and pathways. We tested whether the intended destination of cargo intercepted with T. campestris-infested WPM can be used as a predictor of inland introductions, assuming that individuals of T. campestris are likely to be moved through established trade routes between export–import partners. We also developed maps to predict likely areas of introduction and establishment in the United States based on pathway analysis and climate suitability data. The maps will enable informed prioritization of resources in pest surveillance, and may serve as models for other wood borers identified in the WPM and wood products pathway.

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Faguet, Joshua, Bruno Maranhao, Spencer L. Smith, and Joshua T. Trachtenberg. "Ipsilateral Eye Cortical Maps Are Uniquely Sensitive to Binocular Plasticity." Journal of Neurophysiology 101, no. 2 (February 2009): 855–61. http://dx.doi.org/10.1152/jn.90893.2008.

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In the cerebral cortex, neuronal circuits are first laid down by intrinsic mechanisms and then refined by experience. In the canonical model, this refinement is driven by activity-dependent competition between inputs for some limited cortical resource. Here we examine this idea in the mouse visual cortex at the peak of the critical period for experience-dependent plasticity. By imaging intrinsic optical responses, we mapped the strength and size of each eye's cortical representation in normal mice, mice that had been deprived of patterned vision uni- or bilaterally, and in mice in which the contralateral eye had been removed. We find that for both eyes, a period of visual deprivation results in a loss of cortical responsiveness to stimulation through the deprived eye. In addition, the ipsilateral eye pathway is affected by the quality of vision through the opposite eye. Our findings indicate that although both contra- and ipsilateral eye pathways require visual experience for their maintenance, ipsilateral eye projections bear an additional, unique sensitivity to binocular interactions.

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Csik, Valerie Pracilio, Jared Minetola, Karen Walsh, Michael J. Ramirez, and Mark Hurwitz. "Pathways impact on OCM drug cost." Journal of Clinical Oncology 37, no. 27_suppl (September 20, 2019): 109. http://dx.doi.org/10.1200/jco.2019.37.27_suppl.109.

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109 Background: Oncology care, including drugs, represents a significant portion of US healthcare spending. Cost of Part B drugs has increased at a rate 5.7x that of overall Medicare spending (1997-2004). As a participant in the Oncology Care Model (OCM), we found drug costs represent a majority of our total costs. To reduce treatment (Tx) variability, our NCI-designated cancer center chose to implement pathways. Pathways are a clinical decision-support tool that use evidence-based care maps accounting for efficacy, toxicity and cost. At one institution, use of pathways contributed to $15k in savings for stage IV lung cancer Tx. We hypothesized pathway driven Tx standardization would favorably impact total chemotherapy (CTx) costs at the implementation site. Methods: In July 2018, we implemented pathways in Medical and Radiation Oncology for new starts or changes in Tx. Oncologists accessed the tool through our EMR, selected and placed orders for Tx. OCM quarterly data was used to compare 2 quarters immediately pre- and post-pathway implementation. The cancer-mix-adjusted Per-Member-Per-Month (PMPM) Allowed Amounts for CTx were compared between 3 groups; patients on-pathway, patients off-pathway and patients for which the pathways tool was not used (no utilization). PMPMs were evaluated pre- and post-implementation and an ANOVA test was used to evaluate significance of the difference between the two periods. Results: PMPM CTx costs decreased 4.6% between pre- and post-pathway implementation when oncologists followed pathways. By comparison, the off-pathway cohort and the no utilization groups had increases of 0.9% and 17.7% respectively. An evaluation of cost difference proved significant (p < .0001). Breast patients on-pathway had a cost decrease of 20%, compared to increases of 32% and 11% for off-pathway and no utilization groups, respectively. Conclusions: Pathway use reduced variation, a known contributor to healthcare costs, and therefore may be an effective cost control tool. Additional quarters of claims data is needed post-implementation to fully define the impact of pathways on total cost. [Table: see text]

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Pommier, Y., M. Aladjem, and K. W. Kohn. "417 The ATM-Chk2 kinase pathway: molecular interaction maps and therapeutic rationale." European Journal of Cancer Supplements 2, no. 8 (September 2004): 125. http://dx.doi.org/10.1016/s1359-6349(04)80425-7.

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Slater, Ted. "Recent advances in modeling languages for pathway maps and computable biological networks." Drug Discovery Today 19, no. 2 (February 2014): 193–98. http://dx.doi.org/10.1016/j.drudis.2013.12.011.

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Isserlin, Ruth, Daniele Merico, Rasoul Alikhani-Koupaei, Anthony Gramolini, Gary D. Bader, and Andrew Emili. "Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps." PROTEOMICS - Clinical Applications 4, no. 8-9 (September 2010): 759. http://dx.doi.org/10.1002/prca.201090039.

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Isserlin, Ruth, Daniele Merico, Rasoul Alikhani-Koupaei, Anthony Gramolini, Gary D. Bader, and Andrew Emili. "Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps." PROTEOMICS 10, no. 6 (February 1, 2010): 1316–27. http://dx.doi.org/10.1002/pmic.200900412.

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Reese, Benjamin E., and Gary E. Baker. "Changes in fiber organization within the chiasmatic region of mammals." Visual Neuroscience 9, no. 6 (December 1992): 527–33. http://dx.doi.org/10.1017/s0952523800001772.

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AbstractIntroductionClassical views of the optic chiasm maintain four propositions about the retinofugal pathways: (1) each optic nerve contains a retinotopic representation of its respective retinal surface; (2) this retinotopic map in the nerve is the basis for the subsequent segregation of the decussating from the non-decussating fibers; (3) this retinotopy in the nerve is also the basis for the presence of retinotopy found within the half-retinal maps in the optic tracts; and (4) the half-retinal maps from each optic nerve are brought together within the chiasm to yield a unified, binocularly congruent, map in the optic tract (Brodal, 1969; DukeElder, 1961; Polyak, 1957; Wolff, 1940). The appeal of this classical view is in its simplicity, based on the assumption that the retinofugal pathway should replicate the sensory surface along its course. We now know that each of these four propositions is incorrect, and that the error is not one simply of degree or extent (Guillery, 1982, 1991). Rather, the above description of the visual pathway is fundamentally flawed because it has failed to take into account the constraints under which the pathway develops. We shall first consider the evidence for rejecting the classical view, from recent studies on the organization of the retinofugal pathway in adult animals and on the development of that organization. We shall then describe three transformations in the fiber order which all occur in the chiasmatic region, two of which were only recently recognized, and for which we must account.Observations from adult organizationThe difference in the fiber order in the optic nerve and tract

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Laeremans, Annelies, Babs Van De Plas, Stefan Clerens, Gert Van Den Bergh, Lutgarde Arckens, and Tjing-Tjing Hu. "Protein Expression Dynamics during Postnatal Mouse Brain Development." Journal of Experimental Neuroscience 7 (January 2013): JEN.S12453. http://dx.doi.org/10.4137/jen.s12453.

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We explored differential protein expression profiles in the mouse forebrain at different stages of postnatal development, including 10-day (P10), 30-day (P30), and adult (Ad) mice, by large-scale screening of proteome maps using two-dimensional difference gel electrophoresis. Mass spectrometry analysis resulted in the identification of 251 differentially expressed proteins. Most molecular changes were observed between P10 compared to both P30 and Ad. Computational ingenuity pathway analysis (IPA) confirmed these proteins as crucial molecules in the biological function of nervous system development. Moreover, IPA revealed Semaphorin signaling in neurons and the protein ubiquitination pathway as essential canonical pathways in the mouse forebrain during postnatal development. For these main biological pathways, the transcriptional regulation of the age-dependent expression of selected proteins was validated by means of in situ hybridization. In conclusion, we suggest that proteolysis and neurite outgrowth guidance are key biological processes, particularly during early brain maturation.

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Huynh, Trung, and Sen Xu. "Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways." F1000Research 7 (March 29, 2018): 416. http://dx.doi.org/10.12688/f1000research.14012.1.

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We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.

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Huynh, Trung, and Sen Xu. "Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways." F1000Research 7 (June 28, 2018): 416. http://dx.doi.org/10.12688/f1000research.14012.2.

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We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.

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Huynh, Trung, and Sen Xu. "Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways." F1000Research 7 (May 9, 2019): 416. http://dx.doi.org/10.12688/f1000research.14012.3.

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We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.

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Frodyma, Michael E., and Diana Downs. "The panE Gene, Encoding Ketopantoate Reductase, Maps at 10 Minutes and Is Allelic to apbA inSalmonella typhimurium." Journal of Bacteriology 180, no. 17 (September 1, 1998): 4757–59. http://dx.doi.org/10.1128/jb.180.17.4757-4759.1998.

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ABSTRACT In Salmonella typhimurium, precursors to the pyrimidine moiety of thiamine are synthesized de novo by the purine biosynthetic pathway or the alternative pyrimidine biosynthetic (APB) pathway. TheapbA gene was the first locus defined as required for function of the APB pathway (D. M. Downs and L. Petersen, J. Bacteriol. 176:4858–4864, 1994). Recent work showed the ApbA protein catalyzes the NADPH-specific reduction of ketopantoic acid to pantoic acid. This activity had previously been associated with the pantothenate biosynthetic gene panE. Although previous reports placed panE at 87 min on the Escherichia coli chromosome, we show herein that apbA andpanE are allelic and map to 10 min on both the S. typhimurium and E. coli chromosomes. Results presented here suggest that the role of ApbA in thiamine synthesis is indirect since in vivo labeling studies showed that pantoic acid, the product of the ApbA-catalyzed reaction, is not a direct precursor to thiamine via the APB pathway.

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Wang, Qiuxia, Jianguo Feng, and Liling Tang. "Non-Coding RNA Related to MAPK Signaling Pathway in Liver Cancer." International Journal of Molecular Sciences 23, no. 19 (October 7, 2022): 11908. http://dx.doi.org/10.3390/ijms231911908.

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The advancement in high-throughput sequencing analysis and the evaluation of chromatin state maps have revealed that eukaryotic cells produce many non-coding transcripts/RNAs. Further, a strong association was observed between some non-coding RNAs and cancer development. The mitogen-activated protein kinases (MAPK) belong to the serine–threonine kinase family and are the primary signaling pathways involved in cell proliferation from the cell surface to the nucleus. They play an important role in various human diseases. A few non-coding RNAs associated with the MAPK signaling pathway play a significant role in the development of several malignancies, including liver cancer. In this review, we summarize the molecular mechanisms and interactions of microRNA, lncRNA, and other non-coding RNAs in the development of liver cancer that are associated with the MAPK signaling pathway. Further, we briefly discuss the therapeutic strategies for liver cancer related to ncRNA and the MAPK signaling pathway.

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Calura, Enrica, Paolo Martini, Gabriele Sales, Luca Beltrame, Giovanna Chiorino, Maurizio D’Incalci, Sergio Marchini, and Chiara Romualdi. "Wiring miRNAs to pathways: a topological approach to integrate miRNA and mRNA expression profiles." Nucleic Acids Research 42, no. 11 (May 6, 2014): e96-e96. http://dx.doi.org/10.1093/nar/gku354.

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Abstract The production rate of gene expression data is nothing less than astounding. However, with the benefit of hindsight we can assert that, since we completely ignored the non-coding part of the transcriptome, we spent the last decade to study cell mechanisms having few data in our hands. In this scenario, microRNAs, which are key post-trascriptional regulators, deserve special attention. Given the state of knowledge about their biogenesis, mechanisms of action and the numerous experimentally validated target genes, miRNAs are also gradually appearing in the formal pathway representations such as KEGG and Reactome maps. However, the number of miRNAs annotated in pathway maps are very few and pathway analyses exploiting this new regulatory layer are still lacking. To fill these gaps, we present ‘micrographite’ a new pipeline to perform topological pathway analysis integrating gene and miRNA expression profiles. Here, micrographite is used to study and dissect the epithelial ovarian cancer gene and miRNA transcriptome defining and validating a new regulatory circuit related to ovarian cancer histotype specificity.

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Kanehisa, Minoru, Miho Furumichi, Yoko Sato, Mari Ishiguro-Watanabe, and Mao Tanabe. "KEGG: integrating viruses and cellular organisms." Nucleic Acids Research 49, no. D1 (October 30, 2020): D545—D551. http://dx.doi.org/10.1093/nar/gkaa970.

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Abstract KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.

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Luo, Feng, Xue-Mei Yuan, Hong Xiong, Cong Huang, Chang-Ming Chen, Wu-Kai Ma, and Xue-Ming Yao. "Exploring the mechanism of action of <i>Tripterygium wilfordii</i> Hook F in the treatment of rheumatoid arthritis based on network pharmacology and molecular docking." Tropical Journal of Pharmaceutical Research 23, no. 2 (March 12, 2024): 327–37. http://dx.doi.org/10.4314/tjpr.v23i2.12.

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Purpose: To determine the mechanism of action of Tripterygium wilfordii Hook F (TwHF) in the treatment of rheumatoid arthritis (RA) based on network pharmacology and molecular docking. Methods: The active constituents and targets of TwHF were screened by searching the TCMSP, TCMIP, PharmMapper database, and BATMAN-TCM platform combined with oral bioavailability and drug-like analysis. The drug-component-target maps were drawn using the UniProt database and Cytoscape 3.9.0 software. The drug-target maps were searched in GeneCards, OMIM, TTD, PharmGKB, and DrugBank databases to obtain the predicted targets of RA, Venn diagrams were drawn to derive the common targets of TwHF components and RA and protein-protein interaction (PPI) network, GO enrichment as well as KEGG pathway analyses were performed. The potential binding activities between the active constituents of TwHF and the targets were predicted using molecular docking. Results: Seven active components and 131 potential targets were found for TwHF while RA had 4,917 related targets. However, TwHF and RA had 87 common targets. The target genes obtained from the PPI network include tumor necrosis factor (TNF), p53 tumor protein (TP53) and vascular endothelial growth factor A (VEGFA). The GO enrichment and KEGG pathway analysis yielded 336 results and 121 signal pathways, respectively. Conclusion: Tripterygium wilfordii Hook F therapy for RA may be a multi-component, multi-target and multi-signal pathway biological process, which may regulate VEGFA, TNF, TP53 and other targets and also exhibit anti-inflammatory and immunomodulatory functions amongst others. Future studies should determine the relationship of the identified targets in vivo to produce alternative treatments for RA.

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Sakurai, Nozomu, and Daisuke Shibata. "KaPPA-View for integrating quantitative transcriptomic and metabolomic data on plant metabolic pathway maps." Journal of Pesticide Science 31, no. 3 (2006): 293–95. http://dx.doi.org/10.1584/jpestics.31.293.

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Holschneider, D. P., J. Yang, Y. Guo, and J. M. I. Maarek. "Reorganization of functional brain maps after exercise training: Importance of cerebellar–thalamic–cortical pathway." Brain Research 1184 (December 2007): 96–107. http://dx.doi.org/10.1016/j.brainres.2007.09.081.

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Möller, Steffen, Nadine Saul, Alan A. Cohen, Rüdiger Köhling, Sina Sender, Hugo Murua Escobar, Christian Junghanss, et al. "Healthspan pathway maps in C. elegans and humans highlight transcription, proliferation/biosynthesis and lipids." Aging 12, no. 13 (July 7, 2020): 12534–81. http://dx.doi.org/10.18632/aging.103514.

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Berkvens, N., F. Jansen, H. Casteels, J. Witters, V. Van Damme, and D. Berkvens. "HarmVect - a simulation-based tool for pathway risk maps of invasive arthropods in Belgium." EPPO Bulletin 47, no. 2 (May 23, 2017): 237–45. http://dx.doi.org/10.1111/epp.12379.

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Jennen, Danyel G. J., Stan Gaj, Pieter J. Giesbertz, Joost H. M. van Delft, Chris T. Evelo, and Jos C. S. Kleinjans. "Biotransformation pathway maps in WikiPathways enable direct visualization of drug metabolism related expression changes." Drug Discovery Today 15, no. 19-20 (October 2010): 851–58. http://dx.doi.org/10.1016/j.drudis.2010.08.002.

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Azuma, Yusuke, and Motonori Ota. "2P435 Exploring the minimal pathway maps(48. Bioinformatics, genomics and proteomics (II),Poster Session,Abstract,Meeting Program of EABS & BSJ 2006)." Seibutsu Butsuri 46, supplement2 (2006): S404. http://dx.doi.org/10.2142/biophys.46.s404_3.

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Lazzarotto, G. B., M. I. Timm, M. L. Zaro, A. J. S. Siqueira, and A. M. P. Azevedo. "BIOCHEMISTRY TEACHING WITH VIRTUAL DYNAMIC METABOLIC DIAGRAMS." Revista de Ensino de Bioquímica 2, no. 2 (May 15, 2004): 3. http://dx.doi.org/10.16923/reb.v2i2.135.

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This work presents a game like educational software (courseware) to study metabolic pathways, calledDiagrama Metabolico Din^amico Virtual (DMDV) of Krebs Cycle. The experience acquired teachingwith the logical sequence tray games in the FFFCMPAs Biochemistry Course provides the beddingswith the use of this model as education method. With DMDV, students can assembly the sequenceof reactions that describe the desired metabolic pathway, create situational models which can guidehis/her choices, reduce the subject complexity of the scheme in knowledge construction presentingin a graphical way the current interrelations. Biochemistry teachers can use the present software inclassroom as well as distance classes. This product integrates multimedia resources extensively andis distributed in CD-ROM format. The virtual environment will make possible interaction of thestudent with the environment and with colleagues and teachers, through tools as chats and forum.Experience with the use of this method was carried through with two distinct groups of students.The rst group was composed by 11 students, who were more familiar with the content and answereda specic questionnaire to previously evaluate the software. The second group was formed by 24students regularly registered in the FFFCMPAs Biochemistry Course, who used the software as astudy method. The rst group considered DMDV of easy and pleasant navigation. The knowledgeevaluation of the second group students was made by a written test and the analysis of three conceptualmaps constructed by each one of them: one map before initiating the study with the DMDV, thesecond just after the study and the third one two months later. Every conceptual maps producedafter DMDV method showed an expansion of valid concepts if compared with the rst maps. Simplevisual comparison of maps shows that new elements where added. All students who passed throughthe experiment reached a greater than ve grade in the subjects written test. Current results suggestthe validity of the DMDV related method to metabolic pathway study.

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Mewes, Daniel, and Christoph Jacobi. "Heat transport pathways into the Arctic and their connections to surface air temperatures." Atmospheric Chemistry and Physics 19, no. 6 (March 27, 2019): 3927–37. http://dx.doi.org/10.5194/acp-19-3927-2019.

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Abstract. Arctic amplification causes the meridional temperature gradient between middle and high latitudes to decrease. Through this decrease the large-scale circulation in the midlatitudes may change and therefore the meridional transport of heat and moisture increases. This in turn may increase Arctic warming even further. To investigate patterns of Arctic temperature, horizontal transports and their changes in time, we analysed ERA-Interim daily winter data of vertically integrated horizontal moist static energy transport using self-organizing maps (SOMs). Three general transport pathways have been identified: the North Atlantic pathway with transport mainly over the northern Atlantic, the North Pacific pathway with transport from the Pacific region, and the Siberian pathway with transport towards the Arctic over the eastern Siberian region. Transports that originate from the North Pacific are connected to negative temperature anomalies over the central Arctic. These North Pacific pathways have been becoming less frequent during the last decades. Patterns with origin of transport in Siberia are found to have no trend and show cold temperature anomalies north of Svalbard. It was found that transport patterns that favour transport through the North Atlantic into the central Arctic are connected to positive temperature anomalies over large regions of the Arctic. These temperature anomalies resemble the warm Arctic–cold continents pattern. Further, it could be shown that transport through the North Atlantic has been becoming more frequent during the last decades.

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Vrahatis, Aristidis G., Konstantina Dimitrakopoulou, Panos Balomenos, Athanasios K. Tsakalidis, and Anastasios Bezerianos. "CHRONOS: a time-varying method for microRNA-mediated subpathway enrichment analysis." Bioinformatics 32, no. 6 (November 14, 2015): 884–92. http://dx.doi.org/10.1093/bioinformatics/btv673.

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Abstract Motivation: In the era of network medicine and the rapid growth of paired time series mRNA/microRNA expression experiments, there is an urgent need for pathway enrichment analysis methods able to capture the time- and condition-specific ‘active parts’ of the biological circuitry as well as the microRNA impact. Current methods ignore the multiple dynamical ‘themes’—in the form of enriched biologically relevant microRNA-mediated subpathways—that determine the functionality of signaling networks across time. Results: To address these challenges, we developed time-vaRying enriCHment integrOmics Subpathway aNalysis tOol (CHRONOS) by integrating time series mRNA/microRNA expression data with KEGG pathway maps and microRNA-target interactions. Specifically, microRNA-mediated subpathway topologies are extracted and evaluated based on the temporal transition and the fold change activity of the linked genes/microRNAs. Further, we provide measures that capture the structural and functional features of subpathways in relation to the complete organism pathway atlas. Our application to synthetic and real data shows that CHRONOS outperforms current subpathway-based methods into unraveling the inherent dynamic properties of pathways. Availability and implementation: CHRONOS is freely available at http://biosignal.med.upatras.gr/chronos/. Contact: tassos.bezerianos@nus.edu.sg. Supplementary information: Supplementary data are available at Bioinformatics online.

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Journal articles on the topic 'MAPS pathway'

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