Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model is a research paper published in Bioinformatics (2024). On theSindex it has a DataRank of 0. It has been cited 7 times.
Scored on demand from live citation data
Linked data & code
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.
National Institutes of Health
Grant: R35GM142701
NIA NIH HHS
Grant: R01 AG062577
NINDS NIH HHS
Grant: R35 NS111602
NIA NIH HHS
Grant: R01 AG064786
NIA NIH HHS
Grant: R01 AG078937
National Institutes of Health
Grant: 5R35GM142701-05
Computational modeling of genetic variations by multi-omics integration todecipher personal genome
FWCI
1.31
Citation Percentile
0.8%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals