All Stories

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