MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification is a research paper published in Bioinformatics (2022). On theSindex it has a DataRank of 0. It has been cited 89 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph β no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full β never from an abstract alone.
Korean government MSIT
Grant: NRF-2018M3C7A1054935
Korea government MEST
Grant: 2021M3A9E4021818
Republic of Korea
Grant: HI18C0460
NIA NIH HHS
Grant: R01 AG017917
NIA NIH HHS
Grant: P30 AG010161
NIA NIH HHS
Grant: R01 AG015819
NIA NIH HHS
Grant: R01 AG036042
NIA NIH HHS
Grant: R01 AG036836
NIA NIH HHS
Grant: R01 AG030146
National Institutes of Health
Grant: 5R01AG036836-03
Exploring the Role of the Brain Transcriptome in Cognitive Decline
National Institutes of Health
Grant: 5R01AG036042-05
Exploring the Role of the Brain Epigenome: Cognitive Decline and Life Experiences
National Institutes of Health
Grant: 2R01AG030146-06A1
Genetic Epidemiology of Cognitive Decline in an Aging Population Sample
National Institutes of Health
Grant: 1P30AG010161-01
SHORT-TERM STABILITY OF CLINICAL TESTS
National Institutes of Health
Grant: 5R01AG015819-07
Risk Factors, Pathology, and Clinical Expressions of AD
Bio & Medical Technology Development Program
Korea Health Technology R&D Project
Korea Health Industry Development Institute
National Research Foundation of Korea
Ministry of Health & Welfare
NIH
FWCI
7.45
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals