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Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.03.20.533508Source: DataRank Database

Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 4 times.

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Open Access4 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)OA: greenTopics (26)IDs (PubMed, OpenAlex)SDGs (1)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (6)

Daniel J. Diaz ORCID,Tianlong Chen ORCID,T. Jeffrey Cole ORCID,Andrew D. Ellington ORCID,Claus O. Wilke ORCID

Live enrichment

PubMed:36993648 OpenAlex:https://openalex.org/W4328114198

National Institutes of Health

Grant: 5R01AI148419-03

Investigating nanobodies to target multidrug resistant bacterial pathogens

National Science Foundation

Grant: 2019844

AI Institute: Institute for Foundations of Machine Learning

NIAID NIH HHS

Grant: R01 AI148419

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/03/20/2023.03.20.533508.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.03.20.533508

repositoryhttp://dx.doi.org/10.1101/2023.03.20.533508

repositoryhttps://pubmed.ncbi.nlm.nih.gov/36993648

Fields of Study

RNA and protein synthesis mechanismsProtein Structure and DynamicsMachine Learning in Bioinformatics0206 medical engineering02 engineering and technology

Keywords

Leverage (statistics)Convolutional neural networkProtein structure predictionArtificial intelligenceComputer scienceMachine learningProtein structureSequence (biology)Computational biologyBiologyBiochemistryElectric Power SuppliesScienceQRMedicineAmino Acid SequenceAmino AcidsArticleAntifibrinolytic AgentsLanguage

Sustainable Development Goals

SDG 0: Quality Education