All Stories

  1. HetNetEX: Exact Asymptotic Inference in Heterogeneous Biomedical Knowledge Graphs
  2. Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution
  3. Deconvolved tumor adipocyte proportions and high grade serous ovarian carcinoma survival
  4. Data from Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race
  5. Supplementary Figure 1 from Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race
  6. Supplementary Figure 2 from Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race
  7. Supplementary Figure 3 from Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race
  8. Supplementary Table 1 from Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race
  9. Supplementary Table 2 from Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race
  10. Supplementary Table 3 from Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race
  11. Characterizing intra- and inter-tumor heterogeneity in Ovarian high-grade serous carcinoma subtypes using single-cell and spatial transcriptomics
  12. Homologous recombination deficiency and survival in ovarian high-grade serous carcinoma by self-reported race
  13. Data from An Analytic Pipeline to Obtain Reliable Genetic Ancestry Estimates from Tumor-Derived RNA Sequencing Data
  14. Supplementary Figure S1 from An Analytic Pipeline to Obtain Reliable Genetic Ancestry Estimates from Tumor-Derived RNA Sequencing Data
  15. Supplementary Table S1 from An Analytic Pipeline to Obtain Reliable Genetic Ancestry Estimates from Tumor-Derived RNA Sequencing Data
  16. Supplementary Table S2 from An Analytic Pipeline to Obtain Reliable Genetic Ancestry Estimates from Tumor-Derived RNA Sequencing Data
  17. Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution
  18. An Analytic Pipeline to Obtain Reliable Genetic Ancestry Estimates from Tumor-Derived RNA Sequencing Data
  19. Research turns hope into reality
  20. BuDDI: Bulk Deconvolution with Domain Invariance to predict cell-type-specific perturbations from bulk
  21. Latent spaces for tumour transcriptomes
  22. Best holdout assessment is sufficient for cancer transcriptomic model selection
  23. A publishing infrastructure for Artificial Intelligence (AI)-assisted academic authoring
  24. Analysis of science journalism reveals gender and regional disparities in coverage
  25. Analysis of science journalism reveals gender and regional disparities in coverage
  26. MousiPLIER: A Mouse Pathway-Level Information Extractor Model
  27. Analysis of science journalism reveals gender and regional disparities in coverage
  28. Many direct-to-consumer canine genetic tests can identify the breed of purebred dogs
  29. Missing cell types in single-cell references impact deconvolution of bulk data but are detectable
  30. The Single-cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors
  31. Pseudomonas aeruginosa transcriptome analysis of metal restriction in ex vivo cystic fibrosis sputum
  32. Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine
  33. Optimizer’s dilemma: optimization strongly influences model selection in transcriptomic prediction
  34. The probability of edge existence due to node degree: a baseline for network-based predictions
  35. Molecular subtypes of high-grade serous ovarian cancer across racial groups and gene expression platforms
  36. Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors
  37. Integration of 168,000 samples reveals global patterns of the human gut microbiome
  38. Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms
  39. Analysis ofPseudomonas aeruginosatranscription in anex vivocystic fibrosis sputum model identifies metal restriction as a gene expression stimulus
  40. MousiPLIER: A Mouse Pathway-Level Information Extractor Model
  41. BuDDI:Bulk Deconvolution with Domain Invarianceto predict cell-type-specific perturbations from bulk
  42. OpenPBTA: The Open Pediatric Brain Tumor Atlas
  43. Is a Picture Worth 1,000 SNPs? Effects of User-Submitted Photographs on Ancestry Estimates from Direct-to-Consumer Canine Genetic Tests
  44. Optimizer’s dilemma: optimization strongly influences model selection in transcriptomic prediction
  45. Deconvolution reveals compositional differences in high-grade serous ovarian cancer subtypes
  46. Macrophages in SHH subgroup medulloblastoma display dynamic heterogeneity that varies with treatment modality
  47. Machine learning in rare disease
  48. Changing word meanings in biomedical literature reveal pandemics and new technologies
  49. Application of Traditional Vaccine Development Strategies to SARS-CoV-2
  50. The Coming of Age of Nucleic Acid Vaccines during COVID-19
  51. MyGeneset.info: an interactive and programmatic platform for community-curated and user-created collections of genes
  52. The effect of non-linear signal in classification problems using gene expression
  53. Biological research and self-driving labs in deep space supported by artificial intelligence
  54. Biomonitoring and precision health in deep space supported by artificial intelligence
  55. Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously
  56. Compendium-Wide Analysis of Pseudomonas aeruginosa Core and Accessory Genes Reveals Transcriptional Patterns across Strains PAO1 and PA14
  57. Computationally Efficient Assembly of Pseudomonas aeruginosa Gene Expression Compendia
  58. Analysis of science journalism reveals gender and regional disparities in coverage
  59. A publishing infrastructure for AI-assisted academic authoring
  60. Hetnet connectivity search provides rapid insights into how two biomedical entities are related
  61. The probability of edge existence due to node degree: a baseline for network-based predictions
  62. The Field-Dependent Nature of PageRank Values in Citation Networks
  63. Author Correction: A phase I/Ib trial and biological correlate analysis of neoadjuvant SBRT with single-dose durvalumab in HPV-unrelated locally advanced HNSCC
  64. Hetnet connectivity search provides rapid insights into how biomedical entities are related
  65. Performance of computational algorithms to deconvolve heterogeneous bulk tumor tissue depends on experimental factors
  66. A phase I/Ib trial and biological correlate analysis of neoadjuvant SBRT with single-dose durvalumab in HPV-unrelated locally advanced HNSCC
  67. Expanding a database-derived biomedical knowledge graph via multi-relation extraction from biomedical abstracts
  68. wenda_gpu: fast domain adaptation for genomic data
  69. SOPHIE: Generative Neural Networks Separate Common and Specific Transcriptional Responses
  70. OpenPBTA: An Open Pediatric Brain Tumor Atlas
  71. Changing word meanings in biomedical literature reveal pandemics and new technologies
  72. GenomicSuperSignature facilitates interpretation of RNA-seq experiments through robust, efficient comparison to public databases
  73. Widespread redundancy in -omics profiles of cancer mutation states
  74. The Effects of Nonlinear Signal on Expression-Based Prediction Performance
  75. An efficient not-only-linear correlation coefficient based on machine learning
  76. Building a Vertically-Integrated Genomic Learning Health System: The Colorado Center for Personalized Medicine Biobank
  77. Compendium-wide analysis of P. aeruginosa core and accessory genes reveal more nuanced transcriptional patterns
  78. wenda_gpu: fast domain adaptation for genomic data
  79. Ten quick tips for deep learning in biology
  80. Ten simple rules for large-scale data processing
  81. Examining linguistic shifts between preprints and publications
  82. Computationally efficient assembly of a Pseudomonas aeruginosa gene expression compendium
  83. Computational audits combat disparities in recognition
  84. Using genome-wide expression compendia to study microorganisms
  85. Identification and Development of Therapeutics for COVID-19
  86. Cancer Informatics for Cancer Centers: Scientific Drivers for Informatics, Data Science, and Care in Pediatric, Adolescent, and Young Adult Cancer
  87. Characterizing Long COVID: Deep Phenotype of a Complex Condition
  88. Human Intrigue: Meta-analysis approaches for big questions with big data while shaking up the peer review process
  89. Widespread redundancy in -omics profiles of cancer mutation states
  90. Multi-ancestry gene-trait connection landscape using electronic health record (EHR) linked biobank data
  91. A field guide to cultivating computational biology
  92. Analysis of scientific society honors reveals disparities
  93. Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design
  94. Reproducibility standards for machine learning in the life sciences
  95. Author Correction: Community-wide hackathons to identify central themes in single-cell multi-omics
  96. miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data
  97. Community-wide hackathons to identify central themes in single-cell multi-omics
  98. Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms
  99. Characterizing Long COVID: Deep Phenotype of a Complex Condition
  100. Dietary Supplements and Nutraceuticals under Investigation for COVID-19 Prevention and Treatment
  101. Analysis of science journalism reveals gender and regional disparities in coverage
  102. GenomicSuperSignature: interpretation of RNA-seq experiments through robust, efficient comparison to public databases
  103. Generative neural networks separate common and specific transcriptional responses
  104. Linguistic Analysis of the bioRxiv Preprint Landscape
  105. miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data
  106. Macrophages in SHH subgroup medulloblastoma display dynamic heterogeneity that varies with treatment modality
  107. Induction of ADAM10 by Radiation Therapy Drives Fibrosis, Resistance, and Epithelial-to-Mesenchyal Transition in Pancreatic Cancer
  108. Genome-wide association study implicates novel loci and reveals candidate effector genes for longitudinal pediatric bone accrual
  109. Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design
  110. Correcting for experiment-specific variability in expression compendia can remove underlying signals
  111. Expanding and Remixing the Metadata Landscape
  112. Biologically Informed Neural Networks Predict Drug Responses
  113. Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)
  114. Transparency and reproducibility in artificial intelligence
  115. Corrigendum to: Recommendations to enhance rigor and reproducibility in biomedical research
  116. Prognostic gene expression signature for high-grade serous ovarian cancer
  117. Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing
  118. The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment
  119. Responsible, practical genomic data sharing that accelerates research
  120. Publisher Correction: Building an international consortium for tracking coronavirus health status
  121. Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States
  122. Building an international consortium for tracking coronavirus health status
  123. Incorporating biological structure into machine learning models in biomedicine
  124. Recommendations to enhance rigor and reproducibility in biomedical research
  125. Compressing gene expression data using multiple latent space dimensionalities learns complementary biological representations
  126. Correcting for experiment-specific variability in expression compendia can remove underlying signals
  127. Specific histone modifications associate with alternative exon selection during mammalian development
  128. Analysis of ISCB honorees and keynotes reveals disparities
  129. Building an International Consortium for Tracking Coronavirus Health Status
  130. Integrative Analysis Identifies Candidate Tumor Microenvironment and Intracellular Signaling Pathways that Define Tumor Heterogeneity in NF1
  131. Genome-wide association study implicates novel loci and reveals candidate effector genes for longitudinal pediatric bone accrual through variant-to-gene mapping
  132. Single-cell transcriptomic profile reveals macrophage heterogeneity in medulloblastoma and their treatment-dependent recruitment
  133. Pseudomonas aeruginosa lasR mutant fitness in microoxia is supported by an Anr-regulated oxygen-binding hemerythrin
  134. Graph biased feature selection of genes is better than random for many genes
  135. Integrative analysis identifies candidate tumor microenvironment and intracellular signaling pathways that define tumor heterogeneity in NF1
  136. Constructing knowledge graphs and their biomedical applications
  137. Immune landscapes associated with different glioblastoma molecular subtypes
  138. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
  139. Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design
  140. Integrated phosphoproteomics and transcriptional classifiers reveal hidden RAS signaling dynamics in multiple myeloma
  141. Pseudomonas aeruginosa lasR mutant fitness in microoxia is supported by an Anr-regulated oxygen-binding hemerythrin
  142. Embracing study heterogeneity for finding genetic interactions in large‐scale research consortia
  143. Voices in methods development
  144. Reusing label functions to extract multiple types of biomedical relationships from biomedical abstracts at scale
  145. Discovering Pathway and Cell Type Signatures in Transcriptomic Compendia with Machine Learning
  146. Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing
  147. Open collaborative writing with Manubot
  148. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
  149. Show me the models
  150. MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease
  151. The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution
  152. Sequential compression across latent space dimensions enhances gene expression signatures
  153. Genomic profiling of childhood tumor patient-derived xenograft models to enable rational clinical trial design
  154. Integrated Phosphoproteomics and Transcriptional Classifiers Reveal Hidden RAS Signaling Dynamics in Multiple Myeloma
  155. Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design
  156. Bayesian deep learning for single-cell analysis
  157. New Drosophila Long-Term Memory Genes Revealed by Assessing Computational Function Prediction Methods
  158. A Parasite's Perspective on Data Sharing
  159. Enter the Matrix: Factorization Uncovers Knowledge from Omics
  160. Inflammatory and JAK-STAT Pathways as Shared Molecular Targets for ANCA-Associated Vasculitis and Nephrotic Syndrome
  161. Learning and Imputation for Mass-spec Bias Reduction (LIMBR)
  162. Discovering pathway and cell-type signatures in transcriptomic compendia with machine learning
  163. Discovering pathway and cell-type signatures in transcriptomic compendia with machine learning
  164. New Drosophila long-term memory genes revealed by assessing computational function prediction methods.
  165. MultiPLIER: a transfer learning framework reveals systemic features of rare autoimmune disease
  166. Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics
  167. Metabolic pathways and immunometabolism in rare kidney diseases
  168. Specific histone modifications associate with alternative exon selection during mammalian development
  169. PathCORE-T: identifying and visualizing globally co-occurring pathways in large transcriptomic compendia
  170. Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay*
  171. Learning and Imputation for Mass-spec Bias Reduction (LIMBR)
  172. Opportunities and obstacles for deep learning in biology and medicine
  173. Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas
  174. Oncogenic Signaling Pathways in The Cancer Genome Atlas
  175. Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas
  176. Research: Sci-Hub provides access to nearly all scholarly literature
  177. Sci-Hub provides access to nearly all scholarly literature
  178. A Multimodal Strategy Used by a Large c-di-GMP Network
  179. A Pilot Characterization of the Human Chronobiome
  180. ADAGE signature analysis: differential expression analysis with data-defined gene sets
  181. Advances in Text Mining and Visualization for Precision Medicine
  182. Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders
  183. Functional network community detection can disaggregate and filter multiple underlying pathways in enrichment analyses
  184. Sci-Hub provides access to nearly all scholarly literature
  185. Sci-Hub provides access to nearly all scholarly literature
  186. A Multimodal Strategy Used By A Large c-di-GMP Network
  187. Enter the matrix: Interpreting unsupervised feature learning with matrix decomposition to discover hidden knowledge in high-throughput omics data
  188. Machine Learning Analysis Identifies Drosophila Grunge/Atrophin as an Important Learning and Memory Gene Required for Memory Retention and Social Learning
  189. Extracting a Biologically Relevant Latent Space from Cancer Transcriptomes with Variational Autoencoders
  190. Implicating candidate genes at GWAS signals by leveraging topologically associating domains
  191. Functional network community detection can disaggregate and filter multiple underlying pathways in enrichment analyses
  192. Sci-Hub provides access to nearly all scholarly literature
  193. Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules
  194. Privacy-preserving generative deep neural networks support clinical data sharing
  195. Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks
  196. Machine learning analysis identifies Drosophila Grunge/Atrophin as an important learning and memory gene required for memory retention and social learning.
  197. ADAGE signature analysis: differential expression analysis with data-defined gene sets
  198. PathCORE: Visualizing globally co-occurring pathways in large transcriptomic compendia
  199. Data-Sharing Models
  200. Opportunities And Obstacles For Deep Learning In Biology And Medicine
  201. Celebrating parasites
  202. A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis
  203. Cross-Platform Normalization Enables Machine Learning Model Training On Microarray And RNA-Seq Data Simultaneously
  204. Reproducibility of computational workflows is automated using continuous analysis
  205. Tell me your neighbors, and I will tell you what you are
  206. A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation signal in glioblastoma
  207. Cheap-seq
  208. Semi-supervised learning of the electronic health record for phenotype stratification
  209. NO-BOUNDARY THINKING IN BIOINFORMATICS
  210. Implicating candidate genes at GWAS signals by leveraging topologically associating domains
  211. How to know what we dont
  212. Comprehensive Cross-Population Analysis of High-Grade Serous Ovarian Cancer Supports No More Than Three Subtypes
  213. System-wide automatic extraction of functional signatures in Pseudomonas aeruginosa with eADAGE
  214. A stromal focus reveals tumor immune signatures
  215. A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation signal in glioblastoma
  216. An expanded evaluation of protein function prediction methods shows an improvement in accuracy
  217. Gut check
  218. Integrative networks illuminate biological factors underlying gene-disease associations
  219. The future is unsupervised
  220. Pathway and network-based strategies to translate genetic discoveries into effective therapies
  221. Evolution of High Cellulolytic Activity in Symbiotic Streptomyces through Selection of Expanded Gene Content and Coordinated Gene Expression
  222. Reproducible Computational Workflows with Continuous Analysis
  223. Tribe: The collaborative platform for reproducible web-based analysis of gene sets
  224. Nothing but a hound dog
  225. Pathway and network-based strategies to translate genetic discoveries into effective therapies
  226. CoINcIDE: All together now
  227. Genetic Association–Guided Analysis of Gene Networks for the Study of Complex Traits
  228. Genomic characterization of patient-derived xenograft models established from fine needle aspirate biopsies of a primary pancreatic ductal adenocarcinoma and from patient-matched metastatic sites
  229. Semi-Supervised Learning of the Electronic Health Record with Denoising Autoencoders for Phenotype Stratification
  230. A Novel Multi-network Approach Reveals Tissue-specific Cellular Modulators of Fibrosis in Systemic Sclerosis, Pulmonary Fibrosis and Pulmonary Arterial Hypertension
  231. Erratum to: Evolving hard problems: generating human genetics datasets with a complex etiology
  232. Cross-platform normalization of microarray and RNA-seq data for machine learning applications
  233. Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer’s disease: a study of ADNI cohorts
  234. ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions
  235. Leveraging global gene expression patterns to predict expression of unmeasured genes
  236. ADAGE analysis of publicly available gene expression data collections illuminates Pseudomonas aeruginosa-host interactions
  237. Comprehensive cross-population analysis of high-grade serous ovarian cancer supports no more than three subtypes
  238. Cross-platform normalization of microarray and RNA-seq data for machine learning applications
  239. Cross-platform normalization of microarray and RNA-seq data for machine learning applications
  240. Identification of shared and unique susceptibility pathways among cancers of the lung, breast, and prostate from genome-wide association studies and tissue-specific protein interactions
  241. Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery
  242. International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways
  243. Testing multiple hypotheses through IMP weighted FDR based on a genetic functional network with application to a new zebrafish transcriptome study
  244. Understanding multicellular function and disease with human tissue-specific networks
  245. Adapting bioinformatics curricula for big data
  246. Targeted exploration and analysis of large cross-platform human transcriptomic compendia
  247. Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms
  248. Testing multiple hypotheses through IMP weighted FDR based on a genetic functional network with application to a new zebrafish transcriptome study
  249. Big Data Bioinformatics
  250. Predicting targeted drug combinations based on Pareto optimal patterns of coexpression network connectivity
  251. Computational genetics analysis of grey matter density in Alzheimer’s disease
  252. Defining cell-type specificity at the transcriptional level in human disease
  253. LT-IIb(T13I), a Non-Toxic Type II Heat-Labile Enterotoxin, Augments the Capacity of a Ricin Toxin Subunit Vaccine to Evoke Neutralizing Antibodies and Protective Immunity
  254. Functional Knowledge Transfer for High-accuracy Prediction of Under-studied Biological Processes
  255. Time-Point Specific Weighting Improves Coexpression Networks from Time-Course Experiments
  256. Chapter 2: Data-Driven View of Disease Biology
  257. IMP: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks
  258. Accurate evaluation and analysis of functional genomics data and methods
  259. PILGRM: an interactive data-driven discovery platform for expert biologists
  260. Evolving hard problems: Generating human genetics datasets with a complex etiology
  261. An Open-Ended Computational Evolution Strategy for Evolving Parsimonious Solutions to Human Genetics Problems
  262. An Analysis of New Expert Knowledge Scaling Methods for Biologically Inspired Computing
  263. Integrative Systems Biology for Data-Driven Knowledge Discovery
  264. Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS
  265. The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics
  266. A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships
  267. Fast genome-wide epistasis analysis using ant colony optimization for multifactor dimensionality reduction analysis on graphics processing units
  268. Artificial Immune Systems for Epistasis Analysis in Human Genetics
  269. Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions
  270. Failure to Replicate a Genetic Association May Provide Important Clues About Genetic Architecture
  271. Sensible initialization using expert knowledge for genome-wide analysis of epistasis using genetic programming
  272. Nature-inspired algorithms for the genetic analysis of epistasis in common human diseases: Theoretical assessment of wrapper vs. filter approaches
  273. Development and evaluation of an open-ended computational evolution system for the creation of digital organisms with complex genetic architecture
  274. Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease
  275. Environmental noise improves epistasis models of genetic data discovered using a computational evolution system
  276. Accelerating epistasis analysis in human genetics with consumer graphics hardware
  277. Ability of epistatic interactions of cytokine single‐nucleotide polymorphisms to predict susceptibility to disease subsets in systemic sclerosis patients
  278. Solving complex problems in human genetics using GP
  279. LTR Retrotransposon-Gene Associations in Drosophila melanogaster
  280. Solving Complex Problems in Human Genetics using Nature-Inspired Algorithms Requires Strategies which Exploit Domain-Specific Knowledge
  281. Ant Colony Optimization for Genome-Wide Genetic Analysis
  282. Relief-based bioinformatics methods for the analysis of epistasis in genetic association studies.
  283. An Expert Knowledge-Guided Mutation Operator for Genome-Wide Genetic Analysis Using Genetic Programming