canSAR : update to the cancer translational research and drug discovery knowledgebase
© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research..
canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular profiling, pharmacology, chemistry, structural and systems biology. Moreover, canSAR applies a unique suite of machine learning algorithms designed to inform drug discovery. Here, we describe the latest updates to the knowledgebase, including a focus on significant novel data. These include canSAR's ligandability assessment of AlphaFold; mapping of fragment-based screening data; and new chemical bioactivity data for novel targets. We also describe enhancements to the data and interface.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:51 |
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| Enthalten in: |
Nucleic acids research - 51(2023), D1 vom: 06. Jan., Seite D1212-D1219 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
di Micco, Patrizio [VerfasserIn] |
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| Links: |
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| Themen: |
Antineoplastic Agents |
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| Anmerkungen: |
Date Completed 13.01.2023 Date Revised 28.01.2023 published: Print Citation Status MEDLINE |
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| doi: |
10.1093/nar/gkac1004 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular profiling, pharmacology, chemistry, structural and systems biology. Moreover, canSAR applies a unique suite of machine learning algorithms designed to inform drug discovery. Here, we describe the latest updates to the knowledgebase, including a focus on significant novel data. These include canSAR's ligandability assessment of AlphaFold; mapping of fragment-based screening data; and new chemical bioactivity data for novel targets. We also describe enhancements to the data and interface | ||
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| 700 | 1 | |a Sanfelice, Domenico |e verfasserin |4 aut | |
| 700 | 1 | |a Dolciami, Daniela |e verfasserin |4 aut | |
| 700 | 1 | |a Ramagiri, Pradeep |e verfasserin |4 aut | |
| 700 | 1 | |a Mica, Ioan L |e verfasserin |4 aut | |
| 700 | 1 | |a Tym, Joseph E |e verfasserin |4 aut | |
| 700 | 1 | |a Gingrich, Philip W |e verfasserin |4 aut | |
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