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Deep Learning to Predict the Biosynthetic Gene Clusters in Bacterial Genomes

Journal of Molecular Biology(2022)10.1016/j.jmb.2022.167597Source: DataRank Database

Deep Learning to Predict the Biosynthetic Gene Clusters in Bacterial Genomes is a research paper published in Journal of Molecular Biology (2022). On theSindex it has a DataRank of 0. It has been cited 39 times.

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39 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 2.27)OA: closedTopics (25)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

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Authors (3)

Yun Li ORCID,Hongzhe Li ORCID,Mingyang Liu ORCID

Live enrichment

PubMed:35526560 OpenAlex:https://openalex.org/W4229073727

National Institutes of Health

Grant: GM123056

National Institutes of Health

Grant: GM129781

FWCI

2.27

Citation Percentile

0.9%

Citation Trend

2022

2023

2024

2025

2026

closedLicense: http://www.elsevier.com/open-access/userlicense/1.0/

publisherhttps://api.elsevier.com/content/article/PII:S0022283622001772?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0022283622001772?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.jmb.2022.167597

repositoryhttps://pubmed.ncbi.nlm.nih.gov/35526560

Fields of Study

Genomics and Phylogenetic StudiesMicrobial Natural Products and BiosynthesisRNA and protein synthesis mechanismsBacteriaBiosynthetic PathwaysDeep LearningGenome, BacterialMultigene Family

MeSH Terms

Deep LearningBacteriaMultigene FamilyGenome, BacterialBiosynthetic Pathways

Keywords

Bacterial genome sizeGenomeGeneBiologyComputational biologyPhylumGeneticsIdentification (biology)Data AugmentationFunctional MicrobiomeProtein Family DomainsLong Short-term Memory Rnn

Deep Learning to Predict the Biosynthetic Gene Clusters in Bacterial Genomes

FAIR Checklist

Authors (3)

Funding (2 grants)

Impact

Open Access

Topics