On Comparing Two Structured RNA Multiple alignments. - Vandanaben Patel; Jason T. L. Wang; Shefali Setia; Anurag Verma; Charles D. Warden; Kaizhong Zhang (J. Bioinform. Comput. Biol., 2010)

Next-Generation Analysis of Cataracts: Determining Knowledge Driven Gene-Gene Interactions Using Biofilter, and Gene-Environment Interactions Using the PhenX Toolkit. - Sarah A. Pendergrass; Shefali S. Verma; Emily Rose Holzinger; Carrie Moore; John R. Wallace; Scott M. Dudek; Wayne Huggins; Terrie E. Kitchner; Carol Waudby; Richard L. Berg; Catherine A. McCarty; Marylyn D. Ritchie (Pacific Symposium on Biocomputing, 2013)

Benefits of Accurate Imputations in GWAS. - Shefali S. Verma; Peggy L. Peissig; Deanna S. Cross; Carol Waudby; Murray H. Brilliant; Catherine A. McCarty; Marylyn D. Ritchie (EvoApplications, 2014)

Session Introduction. - Molly A. Hall; Shefali S. Verma; Dennis P. Wall; Jason H. Moore; Brendan Keating; Daniel B. Campbell; Gregory Gibson; Folkert W. Asselbergs; Sarah A. Pendergrass (Pacific Symposium on Biocomputing, 2015)

Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR). - Rishika De; Shefali S. Verma; Fotios Drenos; Emily Rose Holzinger; Michael Holmes; Molly A. Hall; David R. Crosslin; David Carrell; Hakon Hakonarson; Gail P. Jarvik; Eric B. Larson; Jennifer A. Pacheco; et al. (BioData Min., 2015)

Biofilter as a Functional Annotation Pipeline for Common and Rare Copy Number Burden. - Dokyoon Kim; Anastasia Lucas; Joseph Glessner; Shefali S. Verma; Yukiko Bradford; Ruowang Li; Alex T. Frase; Hakon Hakonarson; Peggy L. Peissig; Murray H. Brilliant; Marylyn D. Ritchie (PSB, 2016)

Phenome-Wide Interaction Study (PheWIS) in Aids Clinical Trials Group Data (ACTG). - Shefali S. Verma; Alex T. Frase; Anurag Verma; Sarah A. Pendergrass; Shaun Mahony; David W. Haas; Marylyn D. Ritchie (PSB, 2016)

Integrating Clinical Laboratory Measures and ICD-9 Code Diagnoses in Phenome-Wide Association Studies. - Anurag Verma; Joseph B. Leader; Shefali S. Verma; Alex T. Frase; John R. Wallace; Scott M. Dudek; Daniel R. Lavage; Cristopher V. Van Hout; Frederick E. Dewey; John Penn; Alexander E. Lopez; John D. Overton; et al. (PSB, 2016)

Identifying Genetic Associations with Variability in Metabolic Health and Blood Count Laboratory Values: Diving into the Quantitative Traits by Leveraging Longitudinal Data from an EHR. - Shefali S. Verma; Anastasia Lucas; Daniel R. Lavage; Joseph B. Leader; Raghu Metpally; Sarathbabu Krishnamurthy; Frederick E. Dewey; Ingrid B. Borecki; Alexander E. Lopez; John D. Overton; John Penn; Jeffrey G. Reid; et al. (PSB, 2017)

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. - Emily Rose Holzinger; Shefali S. Verma; Carrie Colleen Buchanan Moore; Molly A. Hall; Rishika De; Diane Gilbert-Diamond; Matthew B. Lanktree; Nathan Pankratz; Antoinette Amuzu; Amber Burt; Caroline Dale; Scott M. Dudek; et al. (BioData Min., 2017)

Using knowledge-driven genomic interactions for multi-omics data analysis: metadimensional models for predicting clinical outcomes in ovarian carcinoma. - Dokyoon Kim; Ruowang Li; Anastasia Lucas; Shefali S. Verma; Scott M. Dudek; Marylyn D. Ritchie (J. Am. Medical Informatics Assoc., 2017)

Evaluation of PrediXcan for prioritizing GWAS associations and predicting gene expression. - Binglan Li; Shefali S. Verma; Yogasudha Veturi; Anurag Verma; Yuki Bradford; David W. Haas; Marylyn D. Ritchie (PSB, 2018)

Session Introduction. - Shefali Setia Verma; Anurag Verma; Anna Okula Basile; Marta Byrska-Bishop; Christian Darabos (PSB, 2018)

Collective feature selection to identify crucial epistatic variants. - Shefali S. Verma; Anastasia Lucas; Xinyuan Zhang 003; Yogasudha Veturi; Scott M. Dudek; Binglan Li; Ruowang Li; Ryan J. Urbanowicz; Jason H. Moore; Dokyoon Kim; Marylyn D. Ritchie (BioData Min., 2018)

A simulation study investigating power estimates in phenome-wide association studies. - Anurag Verma; Yukiko Bradford; Scott M. Dudek; Anastasia Lucas; Shefali S. Verma; Sarah A. Pendergrass; Marylyn D. Ritchie (BMC Bioinform., 2018)

Neural network-based multiomics data integration in Alzheimer's disease. - Pankhuri Singhal; Shefali S. Verma; Scott M. Dudek; Marylyn D. Ritchie (GECCO (Companion), 2019)

Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies. - Binglan Li; Yogasudha Veturi; Yukiko Bradford; Shefali S. Verma; Anurag Verma; Anastasia M. Lucas; David W. Haas; Marylyn D. Ritchie (PSB, 2019)

Session Introduction. - Shefali Setia Verma; Anurag Verma; Dokyoon Kim; Christian Darabos (PSB, 2019)

Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43, 870 individuals from the eMERGE network. - Xinyuan Zhang 003; Yogasudha Veturi; Shefali Setia Verma; William Bone; Anurag Verma; Anastasia Lucas; Scott J. Hebbring; Joshua C. Denny; Ian B. Stanaway; Gail P. Jarvik; David R. Crosslin; Eric B. Larson; et al. (PSB, 2019)

What about the environment? Leveraging multi-omic datasets to characterize the environment's role in human health. - Kristin Passero; Shefali Setia Verma; Kimberly McAllister; Arjun K. Manrai; Chirag J. Patel; Molly A. Hall (PSB, 2021)

Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies. - Ning Shang; Atlas Khan; Fernanda Polubriaginof; Francesca Zanoni; Karla Mehl; David Fasel; Paul E. Drawz; Robert J. Carroll; Joshua C. Denny; Matthew A. Hathcock; Adelaide M. Arruda-Olson; Peggy L. Peissig; et al. (npj Digit. Medicine, 2021)

A radiomics-based model for the outcome prediction in COVID-19 positive patients through deep learning with both longitudinal chest x-ray and chest computed tomography images. - Chunrui Zou; Walter C. Mankowski; Lauren Pantalone; Shefali Setia Verma; Eduardo Jose Mortani Barbosa Jr.; Tessa S. Cook; Peter B. Noël; Erica L. Carpenter; Jeffrey C. Thompson; Russell T. Shinohara; Sharyn Katz; Despina Kontos (Computer-Aided Diagnosis, 2023)

Leveraging electronic health record data for endometriosis research. - Nadia Penrod; Chelsea Okeh; Digna Velez Edwards; Kurt Barnhart; Suneeta Senapati; Shefali S. Verma (Frontiers Digit. Health, 2023)