Author

Mulong Du

Harvard UniversityORCID 0000-0002-2733-6490Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 2 Assay:GWAS summary statistics· 2 Approach:deep learning· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Meilin WangiD· 2 shared Aesun ShiniD· 1 shared Alicja WolkiD· 1 shared Amanda I. PhippsiD· 1 shared Andrea GsuriD· 1 shared Andrea N. Burnett‐HartmaniD· 1 shared Andrew Tan ChaniD· 1 shared Ann Graham ZauberiD· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Meilin WangORCID

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2 papers

Recent·Most cited

Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity

Minta Thomas, Yu‐Ru Su, Elisabeth A. Rosenthal, Lori C. Sakoda, Stephanie L. Schmit, Maria N Timofeeva, Zhishan Chen, Ceres Fernández–Rozadilla, Philip Law, Neil Murphy, Robert Carreras‐Torres, Virginia Díez‐Obrero, Fränzel JB van Duijnhoven, Shangqing Jiang, Aesun Shin, , Taiki Yamaji

This study improves polygenic risk scores for colorectal cancer by combining Asian and European ancestry data, enhancing risk prediction across diverse racial and ethnic groups.

medRxiv · Jan 19, 2023 · PreprintGenetic & Genomic Medicine

Explaining the genetic causality for complex diseases via deep association kernel learning

Feng Bao, Yue Cheng Deng, Mulong Du, Zhiquan Ren, Sen Wan, Junyi Xin, Feng Chen, David C. Christiani, Meilin Wang, Qionghai Dai

This paper introduces a deep learning model to improve GWAS by detecting complex genetic effects, revealing potential causal pathways in disease development.

bioRxiv · Dec 17, 2019 · PreprintBioinformatics