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Personal transcriptome variation is poorly explained by current genomic deep learning models

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.06.30.547100Source: DataRank Database

Personal transcriptome variation is poorly explained by current genomic deep learning models is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 18 times.

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Open Access18 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (2 grants)OA: greenTopics (34)IDs (PubMed, OpenAlex)

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Authors (7)

Richard W. Shuai ORCID,Parth Baokar,Ryan Chung ORCID,Ruchir Rastogi ORCID,Pooja Kathail ORCID

Live enrichment

PubMed:19965766 OpenAlex:https://openalex.org/W4382931192

National Institutes of Health

Grant: 4R00HG009677-03

Statistical Methods for Personal Genome Interpretation

National Institutes of Health

Grant: 1R13HG000967-01

WORKSHOP ON THE IDENTIFICATION OF TRANSCRIBED SEQUENCES

greenLicense: cc-by-nc-nd

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/06/30/2023.06.30.547100.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.06.30.547100

repositoryhttps://doi.org/10.1101/2023.06.30.547100

https://doi.org/10.1038/s41588-023-01574-w

Fields of Study

Genomics and Chromatin DynamicsGene expression and cancer classificationEpigenetics and DNA Methylation0206 medical engineering02 engineering and technology

Keywords

TranscriptomeBiologyGenomeEpigeneticsComputational biologyGeneVariation (astronomy)GeneticsGenetic variationGenomicsGene expressionHuman genomeEvolutionary biology1.1 Normal biological development and functioningAgricultural biotechnologyBioinformatics and Computational BiologyBiological SciencesBrief CommunicationMedical and Health Sciences4.1 Discovery and preclinical testing of markers and technologiesCancer GenomicsDeep LearningNetworking and Information Technology R&D (NITRD)Machine Learning and Artificial IntelligenceHumansGeneric health relevanceBiotechnologyCancerDevelopmental Biology