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A Biologically Informed Method for Detecting Associations with Rare Variants.

, , , , , and . EvoBIO, volume 7246 of Lecture Notes in Computer Science, page 201-210. Springer, (2012)

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Phenome-Wide Interaction Study (PheWIS) in Aids Clinical Trials Group Data (ACTG)., , , , , , and . PSB, page 57-68. (2016)Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry., , , , , , , and . BioData Min., (2015)Visual Integration of Results from a Large Dna Biobank (Biovu) Using Synthesis-View., , , , and . Pacific Symposium on Biocomputing, page 265-275. World Scientific Publishing, (2011)Using BioBin to Explore Rare Variant Population Stratification., , , , and . Pacific Symposium on Biocomputing, page 332-343. World Scientific Publishing, (2013)Integrating Clinical Laboratory Measures and ICD-9 Code Diagnoses in Phenome-Wide Association Studies., , , , , , , , , and 7 other author(s). PSB, page 168-179. (2016)Next-Generation Analysis of Cataracts: Determining Knowledge Driven Gene-Gene Interactions Using Biofilter, and Gene-Environment Interactions Using the PhenX Toolkit., , , , , , , , , and 2 other author(s). Pacific Symposium on Biocomputing, page 147-158. World Scientific Publishing, (2013)Interpretation of machine learning predictions for patient outcomes in electronic health records., , , and . AMIA, AMIA, (2019)Contrasting Association Results Between Existing PheWAS Phenotype Definition Methods and Five Validated Electronic Phenotypes., , , , , , and . AMIA, AMIA, (2015)Diverse convergent evidence in the genetic analysis of complex disease: coordinating omic, informatic, and experimental evidence to better identify and validate risk factors., , , , , , , , , and 5 other author(s). BioData Min., (2014)Session introduction., , and . Pacific Symposium on Biocomputing, page 183-187. (2014)