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SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization

Bioinformatics(2021)10.1093/bioinformatics/btab207Source: DataRank Database

SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization is a research paper published in Bioinformatics (2021). On theSindex it has a DataRank of 0. It has been cited 177 times.

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Authors (6)

Kexin Huang ORCID,Chao Zhang ORCID,Lucas M. Glass ORCID,Jimeng Sun ORCID,Cao Xiao ORCID

Live enrichment

PubMed:33769494 PMC:PMC10060701

National Science Foundation

Grant: SCH-2014438

National Science Foundation

Grant: IIS-1418511

National Science Foundation

Grant: CCF-1533768

National Science Foundation

Grant: IIS-1838042

NIH

Grant: R01 1R01NS107291-01

NIH

Grant: R56HL138415

NINDS NIH HHS

Grant: R01 NS107291

National Science Foundation

Grant: 1418511

SCH: INT: Collaborative Research: High-throughput Phenotyping on Electronic Health Records using Multi-Tensor Factorization

National Institutes of Health

Grant: 1R01NS107291-01

Big Data and Deep Learning for the Interictal-Ictal-Injury Continuum

National Science Foundation

Grant: 1533768

XPS: FULL: DSD: A Parallel Tensor Infrastructure (ParTI!) for Data Analysis

National Institutes of Health

Grant: 1R56HL138415-01

Interpretable Deep Learning Model for Longitudinal Electronic Health Records and Applications to Heart Failure Prediction

National Science Foundation

Grant: 1838042

BigData:IA:Collaborative Research: TIMES: A tensor factorization platform for spatio-temporal data

National Science Foundation

Grant: 2014438

SCH:INT: Collaborative Research: Deep Sense: Interpretable Deep Learning for Zero-effort Phenotype Sensing and Its Application to Sleep Medicine

National Institute of Health

hybridLicense: cc-by

publisherhttps://academic.oup.com/bioinformatics/article-pdf/37/18/2988/40471587/btab207.pdf

publisherhttp://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btab207/37061809/btab207.pdf

publisherhttps://academic.oup.com/bioinformatics/article-pdf/37/18/2988/50579378/btab207.pdf

repositoryhttps://arxiv.org/pdf/2010.01450

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10060701/pdf/btab207.pdf

Fields of Study

0301 basic medicine0303 health sciences03 medical and health sciences

MeSH Terms

Drug InteractionsPattern Recognition, AutomatedMachine LearningNeural Networks, Computer

Keywords

FOS: Computer and information sciencesComputer Science - Machine LearningComputer Science - Computation and LanguageQuantitative Biology - Quantitative MethodsOriginal PapersComputer Science - Information RetrievalPattern Recognition, AutomatedMachine Learning (cs.LG)Machine LearningFOS: Biological sciencesDrug InteractionsNeural Networks, ComputerComputation and Language (cs.CL)Information Retrieval (cs.IR)Quantitative Methods (q-bio.QM)

Additional file 1 of On the robustness of generalization of drug–drug interaction models

10.6084/m9.figshare.16735774.v1figshare

Additional file 1 of On the robustness of generalization of drug–drug interaction models

10.6084/m9.figshare.16735774figshare

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization

10.48550/arxiv.2010.01450arXiv