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MIND-S is a deep-learning prediction model for elucidating protein post-translational modifications in human diseases

Cell Reports Methods(2023)10.1016/j.crmeth.2023.100430Source: DataRank Database

MIND-S is a deep-learning prediction model for elucidating protein post-translational modifications in human diseases is a research paper published in Cell Reports Methods (2023). On theSindex it has a DataRank of 0. It has been cited 27 times.

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Open Access27 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (8 grants)Impact (FWCI 2.45)OA: goldTopics (47)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (9)

Jyun‐Yu Jiang ORCID,Mingzhou Fu ORCID,Ding Wang ORCID,Alexander R. Pelletier ORCID,Dibakar Sigdel ORCID

Live enrichment

PubMed:37056379 OpenAlex:https://openalex.org/W4361001942

National Institutes of Health

Grant: R35 HL135772

National Institutes of Health

Grant: R01 HL146739

National Institutes of Health

Grant: T32 HL139450

National Science Foundation

Grant: NRT 1829071

National Science Foundation

Grant: 1829071

NRT-HDR: Modeling and Understanding Human Behavior: Harnessing Data from Genes to Social Networks

National Institutes of Health

Grant: 1R01HL146739-01

Extraction of molecular signature of HFpEF via a machine learning-empowered proteomic characterization: A study of the BCAA pathway

National Institutes of Health

Grant: 1T32HL139450-01

iDISCOVER: Integrated Data Science Training in CardioVascular Medicine

National Institutes of Health

Grant: 5R35HL135772-07

Omics Phenotyping for Identifying Molecular Signatures of the Healthy and Failing Heart: An Integrated Data Science Platform

FWCI

2.45

Citation Percentile

0.9%

Citation Trend

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://doi.org/10.1016/j.crmeth.2023.100430

publisherhttps://doi.org/10.1016/j.crmeth.2023.100430

publisherhttps://api.elsevier.com/content/article/PII:S2667237523000450?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2667237523000450?httpAccept=text/plain

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37056379

Fields of Study

RNA and protein synthesis mechanismsMachine Learning in BioinformaticsChemical Synthesis and Analysis0206 medical engineering02 engineering and technology

MeSH Terms

Deep LearningAmino AcidsHumansProtein Processing, Post-TranslationalProteinsNeural Networks, Computer

Keywords

Posttranslational modificationComputer scienceArtificial intelligenceWorkflowMachine learningDeep learningComputational biologyRelevance (law)Artificial neural networkBiologyBiochemistryNeural Networks1.1 Normal biological development and functioningBioinformatics and Computational Biology610graph neural networkBioengineeringComputermulti-labelMachine Learning and Artificial IntelligenceGWASHumansprotein structureAmino AcidsProtein Processingcardiac proteomePost-TranslationalProteinsBiological Sciences004Networking and Information Technology R&D (NITRD)AIGeneric health relevanceNeural Networks, ComputerinterpretabilityProtein Processing, Post-Translational