All Stories

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