All Stories

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