Multitask Matrix Completion for Learning Protein Interactions Across Diseases

Author:

Kshirsagar Meghana1,Murugesan Keerthiram2,Carbonell Jaime G.2,Klein-Seetharaman Judith3

Affiliation:

1. Memorial Sloan Kettering Cancer Center, New York, New York.

2. Language Technologies Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania.

3. Metabolic & Vascular Health, Warwick Medical School, University of Warwick, Coventry, United Kingdom.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exploration of Computational Aids for Effective Drug Designing and Management of Viral Diseases: A Comprehensive Review;Current Topics in Medicinal Chemistry;2023-08-07

2. Computational Modeling in the Development of Antiviral Agents;Challenges and Advances in Computational Chemistry and Physics;2023

3. A Survey on Multi-Task Learning;IEEE Transactions on Knowledge and Data Engineering;2021

4. Noisy low‐rank matrix completion under general bases;Stat;2020-01

5. Exploring Energy Profiles of Protein-Protein Interactions (PPIs) Using DFT Method;Letters in Drug Design & Discovery;2019-05-24

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