Author

Tooba Rizwan

Loyola University Chicago

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:fine-mapping· 1 Research Focus:GWAS / association mapping· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Ani W ManichaikuliD· 1 shared Claudia Krueger· 1 shared Hae Kyung ImiD· 1 shared Heather E. WheeleriD· 1 shared Jerome I. RotteriD· 1 shared Kent D. TayloriD· 1 shared Matthew FischeriD· 1 shared Michael H. ChoiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Ani W ManichaikulORCID

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1 paper

Recent·Most cited

Multi-ancestry modeling improves fine-mapping resolution, protein prediction, and discovery for proteome-wide association studies

Claudia Krueger, Matthew Fischer, Tooba Rizwan, Mira M. Kumar, Siyaa Bhargava, Robert Edgardo Gerszten, Kent D. Taylor, Michael H. Cho, Jerome I. Rotter, Minoli A. Perera, Xiaowei Hu, Ani W Manichaikul, Hae Kyung Im, Heather E. Wheeler

This study improves proteome-wide association study results by using multi-ancestry data, finding more protein-phenotype associations and better prediction models.

medRxiv · Jul 1, 2026 · PreprintGenetic & Genomic Medicine