Deep learning identifies synergistic drug combinations for treating COVID-19
Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been challenging. Combination therapies play an important role in antiviral therapies, due to their improved effic...
Main Authors: | Jin, Wengong (Author), Stokes, Jonathan (Author), Eastman, Richard T. (Author), Itkin, Zina (Author), Zakharov, Alexey V. (Author), Collins, James J. (Author), Jaakkola, Tommi S (Author), Barzilay, Regina (Author) |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Synthetic Biology Center (Contributor), Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor) |
Format: | Article |
Language: | English |
Published: |
National Academy of Sciences,
2021-09-24T18:41:00Z.
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Subjects: | |
Online Access: | Get fulltext |
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