AI Bibliography
AI Bibliography |
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Nussinov, R., Jang, H., Nir, G., Tsai, C.-J., & Cheng, F. (2021). A new precision medicine initiative at the dawn of exascale computing. Signal Transduction and Targeted Therapy, 6(1), 1–8. |
| Resource type: Journal Article BibTeX citation key: Nussinov2021 View all bibliographic details  |
Categories: Artificial Intelligence, Biological Science, Computer Science, Data Sciences, Decision Theory, General, Medical science Subcategories: Deep learning, Informatics Creators: Cheng, Jang, Nir, Nussinov, Tsai Publisher: Collection: Signal Transduction and Targeted Therapy |
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| Abstract |
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Which signaling pathway and protein to select to mitigate the patient’s expected drug resistance? The number of possibilities facing the physician is massive, and the drug combination should fit the patient status. Here, we briefly review current approaches and data and map an innovative patient-specific strategy to forecast drug resistance targets that centers on parallel (or redundant) proliferation pathways in specialized cells. It considers the availability of each protein in each pathway in the specific cell, its activating mutations, and the chromatin accessibility of its encoding gene. The construction of the resulting Proliferation Pathway Network Atlas will harness the emerging exascale computing and advanced artificial intelligence (AI) methods for therapeutic development. Merging the resulting set of targets, pathways, and proteins, with current strategies will augment the choice for the attending physicians to thwart resistance.
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