All Stories

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