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Aditya Pratapa
Researcher at Virginia Tech
Publications - 14
Citations - 649
Aditya Pratapa is an academic researcher from Virginia Tech. The author has contributed to research in topics: Flux balance analysis & Inference. The author has an hindex of 5, co-authored 14 publications receiving 259 citations. Previous affiliations of Aditya Pratapa include Indian Institute of Technology Madras & Broad Institute.
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Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data.
TL;DR: A systematic evaluation of state-of-the-art algorithms for inferring gene regulatory networks from single-cell transcriptional data finds heterogeneous performance and suggests recommendations to users.
Posted ContentDOI
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
TL;DR: It is suggested that new ideas for avoiding the prediction of indirect interactions appear to be necessary to improve the accuracy of GRN inference algorithms for single cell gene expression data.
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Image-based cell phenotyping with deep learning.
TL;DR: Applications wherein deep learning is powering the recognition, profiling, and prediction of visual phenotypes to answer important biological questions are reviewed.
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Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks
TL;DR: An algorithm, Fast-SL, is proposed, which surmounts the computational complexity of previous approaches by iteratively reducing the search space for synthetic lethals, resulting in a substantial reduction in running time, even for higher order synthetic lethality analysis.
Journal ArticleDOI
Multiple Myeloma DREAM Challenge reveals epigenetic regulator PHF19 as marker of aggressive disease.
Michael Mason,Carolina Schinke,Christine Eng,Fadi Towfic,Fred K. Gruber,Andrew Dervan,Brian S. White,Aditya Pratapa,Yuanfang Guan,Hongjie Chen,Yi Cui,Bailiang Li,Thomas Yu,Elias Chaibub Neto,Konstantinos Mavrommatis,Maria Ortiz,Valeriy V. Lyzogubov,Kamlesh Bisht,Hongyue Y Dai,Frank Schmitz,Erin Flynt,Dan Rozelle,Samuel A. Danziger,Alexander V. Ratushny,William S. Dalton,Hartmut Goldschmidt,Hervé Avet-Loiseau,Mehmet Kemal Samur,Boris Hayete,Pieter Sonneveld,Kenneth H. Shain,Nikhil C. Munshi,Nikhil C. Munshi,Daniel Auclair,Dirk Hose,Gareth J. Morgan,Matthew Trotter,Douglas Bassett,Jonathan Göke,Brian A Walker,Brian A Walker,Anjan Thakurta,Justin Guinney +42 more
TL;DR: The Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models, found that incorporating specific demographic and clinical features improved gene expression-based models of high risk.