Author

Mohammed Falih Hassan

Virginia Commonwealth UniversityORCID 0000-0002-2995-7442Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Amanda Elswick GentryiD· 1 shared Bradley Todd WebbiD· 1 shared Brien P. RileyiD· 1 shared Kenneth S. KendleriD· 1 shared Mohammad Mehdi AhangariiD· 1 shared Roseann Elizabeth PetersoniD· 1 shared Silviu‐Alin BacanuiD· 1 shared Tan Hoang NguyeniD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperGenetics

Amanda Elswick GentryORCID

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1 paper

Recent·Most cited

Improving the discovery of rare variants associated with alcohol problems by leveraging machine learning phenotype prediction and functional information.

Mohammad Mehdi Ahangari, Amanda Elswick Gentry, Mohammed Falih Hassan, Tan Hoang Nguyen, Kenneth S. Kendler, Silviu‐Alin Bacanu, Roseann Elizabeth Peterson, Brien P. Riley, Bradley Todd Webb

This study uses machine learning and functional weights to identify rare variants associated with AUDIT-P, finding significant associations in ADH1C and THRA genes.

bioRxiv · Sep 11, 2023 · PreprintGenetics