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Journal articles on the topic 'Gene mapping – Computer simulation'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Malakar, Preeti, Thomas George, Sameer Kumar, Rashmi Mittal, Vijay Natarajan, Yogish Sabharwal, Vaibhav Saxena, and Sathish S. Vadhiyar. "A Divide and Conquer Strategy for Scaling Weather Simulations with Multiple Regions of Interest." Scientific Programming 21, no. 3-4 (2013): 93–107. http://dx.doi.org/10.1155/2013/682356.

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Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

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Tyson, Adam L., Charly V. Rousseau, Christian J. Niedworok, Sepiedeh Keshavarzi, Chryssanthi Tsitoura, Lee Cossell, Molly Strom, and Troy W. Margrie. "A deep learning algorithm for 3D cell detection in whole mouse brain image datasets." PLOS Computational Biology 17, no. 5 (May 28, 2021): e1009074. http://dx.doi.org/10.1371/journal.pcbi.1009074.

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Understanding the function of the nervous system necessitates mapping the spatial distributions of its constituent cells defined by function, anatomy or gene expression. Recently, developments in tissue preparation and microscopy allow cellular populations to be imaged throughout the entire rodent brain. However, mapping these neurons manually is prone to bias and is often impractically time consuming. Here we present an open-source algorithm for fully automated 3D detection of neuronal somata in mouse whole-brain microscopy images using standard desktop computer hardware. We demonstrate the applicability and power of our approach by mapping the brain-wide locations of large populations of cells labeled with cytoplasmic fluorescent proteins expressed via retrograde trans-synaptic viral infection.

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3

Xu, Shizhong. "Mapping quantitative trait loci using four-way crosses." Genetical Research 68, no. 2 (October 1996): 175–81. http://dx.doi.org/10.1017/s0016672300034066.

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SummaryIn plant species, typical gene mapping strategies use populations initiated from crosses between two inbred lines. However, schemes including more than two parents could be used. In this paper, a new approach is introduced which uses a four-way cross population derived from four inbred lines. The four-way cross design for mapping quantitative trait loci (QTLs) provides tests for QTL segregation in four lines simultaneously in one experiment. Therefore, it is a more economical strategy than oneusing line crosses between only two lines. The new strategy also increases the probability of detecting QTLs if they segregate in one line cross but not in the other. A multiple linear regression analysis is used for QTL detection. It is proven that the expected residual variance from the regression analysis differs from the pure environmental variance. Correction for the bias is proposed and verified by computer simulations.

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Fortune, Mary D., and Chris Wallace. "simGWAS: a fast method for simulation of large scale case–control GWAS summary statistics." Bioinformatics 35, no. 11 (October 29, 2018): 1901–6. http://dx.doi.org/10.1093/bioinformatics/bty898.

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Abstract Motivation Methods for analysis of GWAS summary statistics have encouraged data sharing and democratized the analysis of different diseases. Ideal validation for such methods is application to simulated data, where some ‘truth’ is known. As GWAS increase in size, so does the computational complexity of such evaluations; standard practice repeatedly simulates and analyses genotype data for all individuals in an example study. Results We have developed a novel method based on an alternative approach, directly simulating GWAS summary data, without individual data as an intermediate step. We mathematically derive the expected statistics for any set of causal variants and their effect sizes, conditional upon control haplotype frequencies (available from public reference datasets). Simulation of GWAS summary output can be conducted independently of sample size by simulating random variates about these expected values. Across a range of scenarios, our method, produces very similar output to that from simulating individual genotypes with a substantial gain in speed even for modest sample sizes. Fast simulation of GWAS summary statistics will enable more complete and rapid evaluation of summary statistic methods as well as opening new potential avenues of research in fine mapping and gene set enrichment analysis. Availability and implementation Our method is available under a GPL license as an R package from http://github.com/chr1swallace/simGWAS. Supplementary information Supplementary data are available at Bioinformatics online.

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Millstein, Joshua, Francesca Battaglin, Malcolm Barrett, Shu Cao, Wu Zhang, Sebastian Stintzing, Volker Heinemann, and Heinz-Josef Lenz. "Partition: a surjective mapping approach for dimensionality reduction." Bioinformatics 36, no. 3 (August 26, 2019): 676–81. http://dx.doi.org/10.1093/bioinformatics/btz661.

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Abstract Motivation Large amounts of information generated by genomic technologies are accompanied by statistical and computational challenges due to redundancy, badly behaved data and noise. Dimensionality reduction (DR) methods have been developed to mitigate these challenges. However, many approaches are not scalable to large dimensions or result in excessive information loss. Results The proposed approach partitions data into subsets of related features and summarizes each into one and only one new feature, thus defining a surjective mapping. A constraint on information loss determines the size of the reduced dataset. Simulation studies demonstrate that when multiple related features are associated with a response, this approach can substantially increase the number of true associations detected as compared to principal components analysis, non-negative matrix factorization or no DR. This increase in true discoveries is explained both by a reduced multiple-testing challenge and a reduction in extraneous noise. In an application to real data collected from metastatic colorectal cancer tumors, more associations between gene expression features and progression free survival and response to treatment were detected in the reduced than in the full untransformed dataset. Availability and implementation Freely available R package from CRAN, https://cran.r-project.org/package=partition. Supplementary information Supplementary data are available at Bioinformatics online.

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Drusbosky, Leylah, Neeraj Kumar Singh, Pranav Tiwari, Shireen Vali, Taher Abbasi, Sarbjit Sarkaria, Adam Lorant, Satin Burns, Rafael Bejar, and Christopher R. Cogle. "A Genomic Rule Predicting HMA Treatment Response in MDS Identified By Protein Network Mapping and Validated By Clinical Trial Simulation." Blood 128, no. 22 (December 2, 2016): 3151. http://dx.doi.org/10.1182/blood.v128.22.3151.3151.

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Abstract Background: Hypomethyating agents (HMAs) for the treatment of the myelodysplastic syndromes (MDS) fail to achieve clinical improvement in nearly 60% of patients. We previously reported a genomics-informed computational method that had >80% accuracy in predicting HMA treatment response in higher risk MDS patients. Aim: To define novel genomic signature rules to predict MDS response to HMA therapy and validate the rules in a clinical trial simulation. Methods: We analyzed a cohort of 213 high-risk MDS patients treated with an HMA and assessed for disease response by IWG criteria (Bejar, et al. Blood 2014). Bone marrow cells from these MDS patients were examined by conventional cytogenetics and next generation sequencing of target myeloid genes. For each patient, every available genomic abnormality was entered into a computational biology program (Cellworks Group) that uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated protein pathways. Digital drug simulations with HMAs were conducted by quantitatively measuring drug effect on a composite MDS disease inhibition score (i.e., cell proliferation, viability, and apoptosis). This information was then used to create virtual Kaplan Meier-type estimates plotting the percent of responders (Y axis) to their disease inhibition score (X axis). A database was developed to house the clinical, genomic, and demographic information for each patient, and used to run clinical trial simulations. Results: A training cohort of 80 MDS patients was used to identify genomic signature rules capable of predicting clinical response to HMA treatment. The 3 rules identified were (1) null hypothesis, no rule for selection of MDS patients for HMA response; (2) TET2 mutation alone, which is known to influence response to HMA in MDS; and (3) TET2 function exclusion, defined as TET2 mutation without the presence of ASXL1 mutation, harboring wild-type SRSF2, and wild-type EZH2. Next, we used these rules in a clinical trial simulation involving 109 different patients in the test dataset. 14 of 203 patients lacked adequate genomic or clinical data for the virtual trial. The 3 rules identified in the training set served as inclusion criteria for 3 HMA treatment arms. The data enabled us to generate the predictive equivalent to a Kaplan-Meier estimate for each arm. Using rule (1) as a control treatment arm, we used rule (2) as an inclusion criterion for a second treatment arm and found a non-significant probability that a randomly selected patient obtained a better MDS disease inhibition score using the rule (2) inclusion criterion (P=0.08) (Figure 1). When rule (3) was used as inclusion criteria, the probability that a randomly selected patient obtained a better MDS disease inhibition score was significantly increased (P=0.0023) (Figure 1). Conclusions: In this study we identified a new four-gene rule predicting MDS response to HMA treatment. We also present a novel method of clinical trial simulation to validate biomarker rules. This unique computer-based approach is intended to inform the design of phase 2 and 3 clinical trials with the ultimate goal of improving drug development time and expense by establishing and validating inclusion criteria for precision enrollment. Figure 1 Clinical Trial Simulation of HMA Treatment in MDS Patients Based on Gene Signature Rules. A genomically-informed computational method identified 3 MDS genomic signatures with potential to predict HMA treatment response based on a training set of patient data (N=80). A separate validation cohort of 109 patients was then virtually recruited into one of 3 HMA treatment arms based on genomic signature rules. In this study, patients with TET2 mutation alone (red line) showed a trend toward greater clinical response than the unselected control cohort (black line) (P=0.08). However, patients harboring TET2 mutation without mutations of ASXL1, SRSF2, and EZH2 (green line) showed significantly greater response to HMA treatment than the unselected control cohort (black line) (p=0.0023). Figure 1. Clinical Trial Simulation of HMA Treatment in MDS Patients Based on Gene Signature Rules. A genomically-informed computational method identified 3 MDS genomic signatures with potential to predict HMA treatment response based on a training set of patient data (N=80). A separate validation cohort of 109 patients was then virtually recruited into one of 3 HMA treatment arms based on genomic signature rules. In this study, patients with TET2 mutation alone (red line) showed a trend toward greater clinical response than the unselected control cohort (black line) (P=0.08). However, patients harboring TET2 mutation without mutations of ASXL1, SRSF2, and EZH2 (green line) showed significantly greater response to HMA treatment than the unselected control cohort (black line) (p=0.0023). Disclosures Kumar Singh: Cellworks: Employment. Tiwari:Cellworks: Employment. Vali:Cellworks Group: Employment. Abbasi:Cellworks: Employment. Bejar:Celgene: Consultancy, Honoraria; Genoptix: Consultancy, Honoraria, Patents & Royalties: No royalties; Foundation Medicine: Consultancy.

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Zhang, Lei, Chenxing Zheng, Yu Zheng, Haihong Huang, and Qingdi Ke. "Product evolutionary design driven by environmental performance." Concurrent Engineering 27, no. 1 (October 15, 2018): 40–56. http://dx.doi.org/10.1177/1063293x18805200.

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This article is in terms of product environmental performance demand and proposes four structure evolutionary operation modes which include combined evolutionary method, decomposition evolutionary method, replacement evolutionary method, and material-changing evolutionary method to express the structure evolutionary process of products. Through the quotient space theory and proposed method combined with probability statistics, probability mapping from environmental performance to product structure is established and the evolutionary individuals with outstanding environmental performance are listed. Through the analysis to the specific conditions of the evolutionary individuals, the design constraints are extracted, and the objective function of environmental performance is established. This article presents an interactive genetic algorithm as evolutionary algorithm and combines it with four structure evolutionary operation modes to conduct corresponding gene manipulation and generates evolutionary product. Finally, the proposed methodology is successfully applied to engine gear chamber and the environmental impact is found to be better than before evolution.

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Hori, Atsushi, Kazumi Yoshinaga, Thomas Herault, Aurélien Bouteiller, George Bosilca, and Yutaka Ishikawa. "Overhead of using spare nodes." International Journal of High Performance Computing Applications 34, no. 2 (February 4, 2020): 208–26. http://dx.doi.org/10.1177/1094342020901885.

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With the increasing fault rate on high-end supercomputers, the topic of fault tolerance has been gathering attention. To cope with this situation, various fault-tolerance techniques are under investigation; these include user-level, algorithm-based fault-tolerance techniques and parallel execution environments that enable jobs to continue following node failure. Even with these techniques, some programs with static load balancing, such as stencil computation, may underperform after a failure recovery. Even when spare nodes are present, they are not always substituted for failed nodes in an effective way. This article considers the questions of how spare nodes should be allocated, how to substitute them for faulty nodes, and how much the communication performance is affected by such a substitution. The third question stems from the modification of the rank mapping by node substitutions, which can incur additional message collisions. In a stencil computation, rank mapping is done in a straightforward way on a Cartesian network without incurring any message collisions. However, once a substitution has occurred, the optimal node-rank mapping may be destroyed. Therefore, these questions must be answered in a way that minimizes the degradation of communication performance. In this article, several spare node allocation and failed node substitution methods will be proposed, analyzed, and compared in terms of communication performance following the substitution. The proposed substitution methods are named sliding methods. The sliding methods are analyzed by using our developed simulation program and evaluated by using the K computer, Blue Gene/Q (BG/Q), and TSUBAME 2.5. It will be shown that when failures occur, the stencil communication performance on the K and BG/Q can be slowed around 10 times depending on the number of node failures. The barrier performance on the K can be cut in half. On BG/Q, barrier performance can be slowed by a factor of 10. Further, it will also be shown that almost no such communication performance degradation can be seen on TSUBAME 2.5. This is because TSUBAME 2.5 has an Infiniband network connected with a FatTree topology, while the K computer and BG/Q have dedicated Cartesian networks. Thus, the communication performance degradation depends on network characteristics.

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Destiarani, Wanda, Rahmaniar Mulyani, Muhammad Yusuf, and Iman Permana Maksum. "Molecular Dynamics Simulation of T10609C and C10676G Mutations of Mitochondrial ND4L Gene Associated With Proton Translocation in Type 2 Diabetes Mellitus and Cataract Patients." Bioinformatics and Biology Insights 14 (January 2020): 117793222097867. http://dx.doi.org/10.1177/1177932220978672.

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The mutation rate of mitochondrial DNA (mtDNA) is 17 times higher than nuclear DNA, and these mutations can cause mitochondrial disease in 1 of 10.000 people. The T10609C mutation was identified in type 2 diabetes mellitus (T2DM) patients and the C10676G mutation in cataract patients, with both mutations occurring in the ND4L gene of mtDNA that encodes ND4L protein. ND4L protein, a subunit of complex I in the respiratory complex, has been shown to play a role in the proton translocation process. The purpose of this study was to investigate the effect of both mutations on the proton translocation mechanism. Mutation mapping showed changes in amino acids M47T (T10609C) and C69W (C10676G). The 100 ns molecular dynamics (MD) simulations performed on native and mutants of ND4L-ND6 subunits. It is revealed that the native model had a similar proton translocation pathway to that of complex I from other organisms. Interestingly, the mutant M47T and C69W showed the interruption of the translocation pathway by a hydrogen bond formation between Glu34 and Tyr157. It is observed that the mutations were restricting the passage of water molecules through the transmembrane region. These results could help to develop the computational assay for the validation of a specific genetic biomarker for T2DM and cataracts.

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Yang, Chin Jian, Rajiv Sharma, Gregor Gorjanc, Sarah Hearne, Wayne Powell, and Ian Mackay. "Origin Specific Genomic Selection: A Simple Process To Optimize the Favorable Contribution of Parents to Progeny." G3: Genes|Genomes|Genetics 10, no. 7 (May 19, 2020): 2445–55. http://dx.doi.org/10.1534/g3.120.401132.

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Modern crop breeding is in constant demand for new genetic diversity as part of the arms race with genetic gain. The elite gene pool has limited genetic variation and breeders are trying to introduce novelty from unadapted germplasm, landraces and wild relatives. For polygenic traits, currently available approaches to introgression are not ideal, as there is a demonstrable bias against exotic alleles during selection. Here, we propose a partitioned form of genomic selection, called Origin Specific Genomic Selection (OSGS), where we identify and target selection on favorable exotic alleles. Briefly, within a population derived from a bi-parental cross, we isolate alleles originating from the elite and exotic parents, which then allows us to separate out the predicted marker effects based on the allele origins. We validated the usefulness of OSGS using two nested association mapping (NAM) datasets: barley NAM (elite-exotic) and maize NAM (elite-elite), as well as by computer simulation. Our results suggest that OSGS works well in its goal to increase the contribution of favorable exotic alleles in bi-parental crosses, and it is possible to extend the approach to broader multi-parental populations.

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Johnson, Paul C. D., and Daniel T. Haydon. "Software for Quantifying and Simulating Microsatellite Genotyping Error." Bioinformatics and Biology Insights 1 (January 2007): BBI.S373. http://dx.doi.org/10.4137/bbi.s373.

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Microsatellite genetic marker data are exploited in a variety of fields, including forensics, gene mapping, kinship inference and population genetics. In all of these fields, inference can be thwarted by failure to quantify and account for data errors, and kinship inference in particular can benefit from separating errors into two distinct classes: allelic dropout and false alleles. Pedant is MS Windows software for estimating locus-specific maximum likelihood rates of these two classes of error. Estimation is based on comparison of duplicate error-prone genotypes: neither reference genotypes nor pedigree data are required. Other functions include: plotting of error rate estimates and confidence intervals; simulations for performing power analysis and for testing the robustness of error rate estimates to violation of the underlying assumptions; and estimation of expected heterozygosity, which is a required input. The program, documentation and source code are available from http://www.stats.gla.ac.uk/~paulj/pedant.html .

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Hill, William G. "Selection with Recurrent Backcrossing to Develop Congenic Lines for Quantitative Trait Loci Analysis." Genetics 148, no. 3 (March 1, 1998): 1341–52. http://dx.doi.org/10.1093/genetics/148.3.1341.

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Abstract Sewall Wright suggested that genes of large effect on a quantitative trait could be isolated by recurrent backcrossing with selection on the trait. Loci [quantitative trait loci (QTL)] at which the recurrent and nonrecurrent lines have genes of different large effect on the trait would remain segregating, while other loci would become fixed for the gene carried by the recurrent parent. If the recurrent line is inbred and the backcrossing and selection is conducted in a series of replicate lines, in each of which only one backcross parent is selected for each generation, the lines will become congenic to the recurrent parent except for the QTL of large effect and closely linked regions of the genome, and these regions can be identified using a dense set of markers that differ between the parental lines. Such lines would be particularly valuable for subsequent fine-scale mapping and gene cloning; but by chance, even QTL of large effect will be lost from some lines. The probability that QTL of specified effect remain segregating is computed as a function of its effect on the trait, the intensity of selection, and the number of generations of backcrossing. Analytical formulas are given for one or two loci, and simulation is used for more. It is shown that the method could have substantial discriminating ability and thus potential practical value.

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TAN, QIHUA, LENE CHRISTIANSEN, KAARE CHRISTENSEN, LISE BATHUM, SHUXIA LI, JING HUA ZHAO, and TORBEN A. KRUSE. "Haplotype association analysis of human disease traits using genotype data of unrelated individuals." Genetical Research 86, no. 3 (November 25, 2005): 223–31. http://dx.doi.org/10.1017/s0016672305007792.

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Haplotype inference has become an important part of human genetic data analysis due to its functional and statistical advantages over the single-locus approach in linkage disequilibrium mapping. Different statistical methods have been proposed for detecting haplotype – disease associations using unphased multi-locus genotype data, ranging from the early approach by the simple gene-counting method to the recent work using the generalized linear model. However, these methods are either confined to case – control design or unable to yield unbiased point and interval estimates of haplotype effects. Based on the popular logistic regression model, we present a new approach for haplotype association analysis of human disease traits. Using haplotype-based parameterization, our model infers the effects of specific haplotypes (point estimation) and constructs confidence interval for the risks of haplotypes (interval estimation). Based on the estimated parameters, the model calculates haplotype frequency conditional on the trait value for both discrete and continuous traits. Moreover, our model provides an overall significance level for the association between the disease trait and a group or all of the haplotypes. Featured by the direct maximization in haplotype estimation, our method also facilitates a computer simulation approach for correcting the significance level of individual haplotype to adjust for multiple testing. We show, by applying the model to an empirical data set, that our method based on the well-known logistic regression model is a useful tool for haplotype association analysis of human disease traits.

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Li, Xin, Xianran Li, Eyal Fridman, Tesfaye T. Tesso, and Jianming Yu. "Dissecting repulsion linkage in the dwarfing gene Dw3 region for sorghum plant height provides insights into heterosis." Proceedings of the National Academy of Sciences 112, no. 38 (September 8, 2015): 11823–28. http://dx.doi.org/10.1073/pnas.1509229112.

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Heterosis is a main contributor to yield increase in many crop species. Different mechanisms have been proposed for heterosis: dominance, overdominance, epistasis, epigenetics, and protein metabolite changes. However, only limited examples of molecular dissection and validation of these mechanisms are available. Here, we present an example of discovery and validation of heterosis generated by a combination of repulsion linkage and dominance. Using a recombinant inbred line population, a separate quantitative trait locus (QTL) for plant height (qHT7.1) was identified near the genomic region harboring the known auxin transporter Dw3 gene. With two loci having repulsion linkage between two inbreds, heterosis in the hybrid can appear as a single locus with an overdominance mode of inheritance (i.e., pseudo-overdominance). Individually, alleles conferring taller plant height exhibited complete dominance over alleles conferring shorter height. Detailed analyses of different height components demonstrated that qHT7.1 affects both the upper and lower parts of the plant, whereas Dw3 affects only the part below the flag leaf. Computer simulations show that repulsion linkage could influence QTL detection and estimation of effect in segregating populations. Guided by findings in linkage mapping, a genome-wide association study of plant height with a sorghum diversity panel pinpointed genomic regions underlying the trait variation, including Dw1, Dw2, Dw3, Dw4, and qHT7.1. Multilocus mixed model analysis confirmed the advantage of complex trait dissection using an integrated approach. Besides identifying a specific genetic example of heterosis, our research indicated that integrated molecular dissection of complex traits in different population types can enable plant breeders to fine tune the breeding process for crop production.

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Ruan, Peifeng, Ya Wang, Ronglai Shen, and Shuang Wang. "Using association signal annotations to boost similarity network fusion." Bioinformatics 35, no. 19 (February 19, 2019): 3718–26. http://dx.doi.org/10.1093/bioinformatics/btz124.

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Abstract Motivation Recent technology developments have made it possible to generate various kinds of omics data, which provides opportunities to better solve problems such as disease subtyping or disease mapping using more comprehensive omics data jointly. Among many developed data-integration methods, the similarity network fusion (SNF) method has shown a great potential to identify new disease subtypes through separating similar subjects using multi-omics data. SNF effectively fuses similarity networks with pairwise patient similarity measures from different types of omics data into one fused network using both shared and complementary information across multiple types of omics data. Results In this article, we proposed an association-signal-annotation boosted similarity network fusion (ab-SNF) method, adding feature-level association signal annotations as weights aiming to up-weight signal features and down-weight noise features when constructing subject similarity networks to boost the performance in disease subtyping. In various simulation studies, the proposed ab-SNF outperforms the original SNF approach without weights. Most importantly, the improvement in the subtyping performance due to association-signal-annotation weights is amplified in the integration process. Applications to somatic mutation data, DNA methylation data and gene expression data of three cancer types from The Cancer Genome Atlas project suggest that the proposed ab-SNF method consistently identifies new subtypes in each cancer that more accurately predict patient survival and are more biologically meaningful. Availability and implementation The R package abSNF is freely available for downloading from https://github.com/pfruan/abSNF. Supplementary information Supplementary data are available at Bioinformatics online.

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Frattini, Annalisa, Sara Faranda, and Paolo Vezzoni. "Computer Gene Mapping byEagI-Based STSs." Genomics 38, no. 1 (November 1996): 87–91. http://dx.doi.org/10.1006/geno.1996.0597.

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Wadge, G., P. A. V. Young, and I. J. McKendrick. "Mapping lava flow hazards using computer simulation." Journal of Geophysical Research: Solid Earth 99, B1 (January 10, 1994): 489–504. http://dx.doi.org/10.1029/93jb01561.

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Qu, Xianggui. "The Statistics of Gene Mapping." Technometrics 50, no. 1 (February 2008): 94. http://dx.doi.org/10.1198/tech.2008.s537.

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Усманова, E. Usmanova, Короткий, Viktor Korotkiy, Хмарова, and Lyudmila Khmarova. "Computer Simulation of Kinematic Surfaces." Geometry & Graphics 3, no. 4 (December 17, 2015): 19–26. http://dx.doi.org/10.12737/17347.

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A geometric surface model is formed taking into account given functional, structural, technological, economic, aesthetic requirements. These requirements are formulated in geometric terms and are expressed in terms of the surface parameters. The surface is modeled either Kinematics manner, or by way of a twodimensional interpolation. In accordance with in accordance with the kinematic method, the surface is formed as a continuous oneparameter many curves that form simulated in the surface. In accordance with the interpolation method, the surface consists of a set of elementary two-dimensional fragments. The article considered cinema optical method based on the use of curves of the second order of change-nests of the eccentricity as the main shaping element. To control the shape of the design surfaces are used for guide ruled surfaces (cilindroidy and conoid). Computer program is compiled, which determines the eccentricity of the forming curves of the second order depending on the boundary conditions. The program allows you to plot curve of the second order, given an arbitrary set of five coplanar points and tangents. When modeling the surface of the passing through a closed circuit, is used the mapping of this contour in four-dimensional space. Such mapping gives more possibilities for control surface shape. It is shown that the kinematics method computer simulation of the surface has technological advantages properties instead of interpolation method.

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Jordan, E., T. Berlec, L. Rihar, and J. Kusar. "Simulation of Cost Driven Value Stream Mapping." International Journal of Simulation Modelling 19, no. 3 (September 15, 2020): 458–69. http://dx.doi.org/10.2507/ijsimm19-3-527.

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Lakaemper, Rolf, and Ali M. Malkawi. "Integrating Robot Mapping and Augmented Building Simulation." Journal of Computing in Civil Engineering 23, no. 6 (November 2009): 384–90. http://dx.doi.org/10.1061/(asce)0887-3801(2009)23:6(384).

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Lakaemper, Rolf, Nagesh Adluru, Longin Jan Latecki, and Raj Madhavan. "Multi robot mapping using force field simulation." Journal of Field Robotics 24, no. 8-9 (2007): 747–62. http://dx.doi.org/10.1002/rob.20210.

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Salis, Howard, and Yiannis Kaznessis. "Numerical simulation of stochastic gene circuits." Computers & Chemical Engineering 29, no. 3 (February 2005): 577–88. http://dx.doi.org/10.1016/j.compchemeng.2004.08.017.

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Gopee, Ajit. "Gene Expression-Based Cross Species Tissue Mapping." BMC Bioinformatics 6, Suppl 3 (2005): P16. http://dx.doi.org/10.1186/1471-2105-6-s3-p16.

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Guo, Jerry Jinfeng, Martin Eisemann, and Elmar Eisemann. "Next Event Estimation++: Visibility Mapping for Efficient Light Transport Simulation." Computer Graphics Forum 39, no. 7 (October 2020): 205–17. http://dx.doi.org/10.1111/cgf.14138.

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Basu, Kashinath, Frank Ball, and Demetres D. Kouvatsos. "A Simulation Study of IPv6 to ATM Flow-Mapping Techniques." SIMULATION 78, no. 7 (July 2002): 423–30. http://dx.doi.org/10.1177/0037549702078007580.

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Cruzalèbes, Pierre, Gérard Schumacher, and Jean-Luc Starck. "Model-independent mapping by optical aperture synthesis: basic principles and computer simulation." Journal of the Optical Society of America A 9, no. 5 (May 1, 1992): 708. http://dx.doi.org/10.1364/josaa.9.000708.

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KANDA, Tohru, Kazuo KANKI, Satoshi YAMADA, and Takeshi NISHIYAMA. "Runoff Simulation for Urban Sewer System Using SWMM Combined with Computer Mapping." PROCEEDINGS OF HYDRAULIC ENGINEERING 37 (1993): 117–22. http://dx.doi.org/10.2208/prohe.37.117.

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Burr, B., F. A. Burr, K. H. Thompson, M. C. Albertson, and C. W. Stuber. "Gene mapping with recombinant inbreds in maize." Genetics 118, no. 3 (March 1, 1988): 519–26. http://dx.doi.org/10.1093/genetics/118.3.519.

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Abstract Recombinant inbred lines of maize have been developed for the rapid mapping of molecular probes to chromosomal location. Two recombinant inbred families have been constructed from F2 populations of T232 X CM37 and CO159 X Tx303. A genetic map based largely on isozymes and restriction fragment length polymorphisms has been produced that covers virtually the entire maize genome. In order to map a new gene, an investigator has only to determine its allelic distribution among the recombinant inbred lines and then compare it by computer with the distributions of all previously mapped loci. The availability of the recombinant inbreds and the associated data base constitute an efficient means of mapping new molecular markers in maize.

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Ragragui, Anouar, Adnane Ouazzani Chahdi, Akram Halli, and Khalid Satori. "Revolution mapping with bump mapping support." Graphical Models 100 (November 2018): 1–11. http://dx.doi.org/10.1016/j.gmod.2018.09.001.

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Ge, Q. J., and B. Ravani. "Computer Aided Geometric Design of Motion Interpolants." Journal of Mechanical Design 116, no. 3 (September 1, 1994): 756–62. http://dx.doi.org/10.1115/1.2919447.

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This paper studies continuous computational geometry of motion and develops a method for Computer Aided Geometric Design (CAGD) of motion interpolants. The approach uses a mapping of spatial kinematics to convert the problem of interpolating displacements to that of interpolating points in the space of the mapping. To facilitate the point interpolation, the previously unorientable mapping space is made orientable. Methods are then developed for designing spline curves in the mapping space with tangent, curvature and torsion continuities. The results have application in computer animation of three-dimensional objects used in computer graphics, computer vision and simulation of mechanical systems.

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Selvakumar, S., and C. Siva Ram Murthy. "An efficient algorithm for mapping VLSI circuit simulation programs onto multiprocessors." Parallel Computing 17, no. 9 (November 1991): 1009–16. http://dx.doi.org/10.1016/s0167-8191(05)80045-6.

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Trebuna, P., M. Pekarcikova, and M. Edl. "Digital Value Stream Mapping Using the Tecnomatix Plant Simulation Software." International Journal of Simulation Modelling 18, no. 1 (March 15, 2019): 19–32. http://dx.doi.org/10.2507/ijsimm18(1)455.

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Khan, Muhammad Awais, Sherif Adeshina Busari, Kazi Mohammed Saidul Huq, Shahid Mumtaz, Saba Al-Rubaye, Jonathan Rodriguez, and Anwer Al-Dulaimi. "A novel mapping technique for ray tracer to system-level simulation." Computer Communications 150 (January 2020): 378–83. http://dx.doi.org/10.1016/j.comcom.2019.11.039.

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35

Kratz, Anton, Masaru Tomita, and Arun Krishnan. "GeNESiS: gene network evolution simulation software." BMC Bioinformatics 9, no. 1 (2008): 541. http://dx.doi.org/10.1186/1471-2105-9-541.

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Seidl, A., and M. Svoboda. "Numerical Conformal Mapping for Treatment of Geometry Problems in Process Simulation." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 4, no. 4 (October 1985): 404–7. http://dx.doi.org/10.1109/tcad.1985.1270138.

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Su, Chengfu, Xinmian Qiu, and Zhixian Ji. "Study of strategies for selecting quantitative trait locus mapping procedures by computer simulation." Molecular Breeding 31, no. 4 (March 17, 2013): 947–56. http://dx.doi.org/10.1007/s11032-013-9848-6.

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Pérez-Enciso, Miguel, Miguel A. Toro, Michel Tenenhaus, and Daniel Gianola. "Combining Gene Expression and Molecular Marker Information for Mapping Complex Trait Genes: A Simulation Study." Genetics 164, no. 4 (August 1, 2003): 1597–606. http://dx.doi.org/10.1093/genetics/164.4.1597.

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Abstract A method for mapping complex trait genes using cDNA microarray and molecular marker data jointly is presented and illustrated via simulation. We introduce a novel approach for simulating phenotypes and genotypes conditionally on real, publicly available, microarray data. The model assumes an underlying continuous latent variable (liability) related to some measured cDNA expression levels. Partial least-squares logistic regression is used to estimate the liability under several scenarios where the level of gene interaction, the gene effect, and the number of cDNA levels affecting liability are varied. The results suggest that: (1) the usefulness of microarray data for gene mapping increases when both the number of cDNA levels in the underlying liability and the QTL effect decrease and when genes are coexpressed; (2) the correlation between estimated and true liability is large, at least under our simulation settings; (3) it is unlikely that cDNA clones identified as significant with partial least squares (or with some other technique) are the true responsible cDNAs, especially as the number of clones in the liability increases; (4) the number of putatively significant cDNA levels increases critically if cDNAs are coexpressed in a cluster (however, the proportion of true causal cDNAs within the significant ones is similar to that in a no-coexpression scenario); and (5) data reduction is needed to smooth out the variability encountered in expression levels when these are analyzed individually.

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Uslu, Erkan, Furkan Çakmak, Nihal Altuntaş, Salih Marangoz, Mehmet Fatih Amasyalı, and Sırma Yavuz. "An architecture for multi-robot localization and mapping in the Gazebo/Robot Operating System simulation environment." SIMULATION 93, no. 9 (June 6, 2017): 771–80. http://dx.doi.org/10.1177/0037549717710098.

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Robots are an important part of urban search and rescue tasks. World wide attention has been given to developing capable physical platforms that would be beneficial for rescue teams. It is evident that use of multi-robots increases the effectiveness of these systems. The Robot Operating System (ROS) is becoming a standard platform for the robotics research community for both physical robots and simulation environments. Gazebo, with connectivity to the ROS, is a three-dimensional simulation environment that is also becoming a standard. Several simultaneous localization and mapping algorithms are implemented in the ROS; however, there is no multi-robot mapping implementation. In this work, two multi-robot mapping algorithm implementations are presented, namely multi-robot gMapping and multi-robot Hector Mapping. The multi-robot implementations are tested in the Gazebo simulation environment. Also, in order to achieve a more realistic simulation, every incremental robot movement is modeled with rotational and translational noise.

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Miele, Antonio, Christian Pilato, and Donatella Sciuto. "A Simulation-Based Framework for the Exploration of Mapping Solutions on Heterogeneous MPSoCs." International Journal of Embedded and Real-Time Communication Systems 4, no. 1 (January 2013): 22–41. http://dx.doi.org/10.4018/jertcs.2013010102.

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The efficient analysis and exploration of mapping solutions of a parallel application on a heterogeneous Multi-Processor Systems-on-Chip (MPSoCs) is usually a challenging task in system-level design, in particular when the architecture integrates hardware cores that may expose reconfigurable features. This paper proposes a system-level design framework based on SystemC simulations for fulfilling this task, featuring (i) an automated flow for the generation of timing models for the hardware cores starting from the application source code, (ii) an enhanced simulation environment for SystemC architectures enabling the specification and modification of mapping choices only by changing an XML descriptor, and (iii) a flexible controller of the simulation environment supporting the exploration of various mapping solutions featuring a customizable engine. The proposed framework has been validated with a case study considering an image processing application to show the possibility to automatically exploring alternative solutions onto a reconfigurable MPSoC platform.

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Mukundan, R., and S. S. Swamy. "A procedure for interactive simulation using mnemonic identifiers and index mapping functions." SIMULATION 55, no. 1 (July 1990): 39–46. http://dx.doi.org/10.1177/003754979005500108.

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Tafesse, Bisrat, and Venkatesan Muthukumar. "Framework for Simulation of Heterogeneous MpSoC for Design Space Exploration." VLSI Design 2013 (July 11, 2013): 1–16. http://dx.doi.org/10.1155/2013/936181.

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Due to the ever-growing requirements in high performance data computation, multiprocessor systems have been proposed to solve the bottlenecks in uniprocessor systems. Developing efficient multiprocessor systems requires effective exploration of design choices like application scheduling, mapping, and architecture design. Also, fault tolerance in multiprocessors needs to be addressed. With the advent of nanometer-process technology for chip manufacturing, realization of multiprocessors on SoC (MpSoC) is an active field of research. Developing efficient low power, fault-tolerant task scheduling, and mapping techniques for MpSoCs require optimized algorithms that consider the various scenarios inherent in multiprocessor environments. Therefore there exists a need to develop a simulation framework to explore and evaluate new algorithms on multiprocessor systems. This work proposes a modular framework for the exploration and evaluation of various design algorithms for MpSoC system. This work also proposes new multiprocessor task scheduling and mapping algorithms for MpSoCs. These algorithms are evaluated using the developed simulation framework. The paper also proposes a dynamic fault-tolerant (FT) scheduling and mapping algorithm for robust application processing. The proposed algorithms consider optimizing the power as one of the design constraints. The framework for a heterogeneous multiprocessor simulation was developed using SystemC/C++ language. Various design variations were implemented and evaluated using standard task graphs. Performance evaluation metrics are evaluated and discussed for various design scenarios.

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Ding, Hong-ming, and Yu-qiang Ma. "Design maps for cellular uptake of gene nanovectors by computer simulation." Biomaterials 34, no. 33 (November 2013): 8401–7. http://dx.doi.org/10.1016/j.biomaterials.2013.06.067.

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44

Sremcev, N., B. Stevanov, M. Lazarevic, J. Mandic, Z. Tesic, and B. Kuzmanovic. "Improving Process of Quotation Creation through Value Stream Mapping and Simulation." International Journal of Simulation Modelling 18, no. 4 (December 1, 2019): 563–73. http://dx.doi.org/10.2507/ijsimm18(4)484.

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MIHALAS, G. I., Z. SIMON, G. BALEA, and E. POPA. "POSSIBLE OSCILLATORY BEHAVIOR IN P53–MDM2 INTERACTION COMPUTER SIMULATION." Journal of Biological Systems 08, no. 01 (March 2000): 21–29. http://dx.doi.org/10.1142/s0218339000000031.

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Specific activator and repressor transcription factors, which bind to specific regulator DNA sequences, play an important role in gene activity control. Interactions between genes coding such transcription factors should explain the different stable or, sometimes, oscillatory gene activities characteristic for different tissues. A set of models has been built for several systems with interconnected genes and the results of the simulations performed for the p53–mdm2 are here presented and discussed.

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McCollum, James M., Gregory D. Peterson, Chris D. Cox, and Michael L. Simpson. "Accelerating Gene Regulatory Network Modeling Using Grid-Based Simulation." SIMULATION 80, no. 4-5 (May 2004): 231–41. http://dx.doi.org/10.1177/0037549704045051.

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Beran, V., P. Dlask, D. Eaton, E. Hromada, and O. Zindulka. "Mapping of synchronous activities through virtual management momentum simulation." Construction Innovation 11, no. 2 (April 19, 2011): 190–211. http://dx.doi.org/10.1108/14714171111124167.

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Sjöstrand, Joel, Lars Arvestad, Jens Lagergren, and Bengt Sennblad. "GenPhyloData: realistic simulation of gene family evolution." BMC Bioinformatics 14, no. 1 (2013): 209. http://dx.doi.org/10.1186/1471-2105-14-209.

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Ghazanfari, A., M. P. Rodriguez, E. Vigmond, and A. Nygren. "Computer Simulation of Cardiac Propagation: Effects of Fiber Rotation, Intramural Conductivity, and Optical Mapping." IEEE Transactions on Biomedical Engineering 61, no. 7 (July 2014): 2041–48. http://dx.doi.org/10.1109/tbme.2014.2311371.

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Sulistio, J., A. P. Hendradewa, and A. Nabila. "Productivity improvement of assembly department by using value stream mapping and computer simulation approach." IOP Conference Series: Materials Science and Engineering 673 (December 10, 2019): 012092. http://dx.doi.org/10.1088/1757-899x/673/1/012092.

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