Statistically principled feature selection for single cell transcriptomics is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2024). On theSindex it has a DataRank of 0. It has been cited 2 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — 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 — never from an abstract alone.
National Institutes of Health
Grant: 5U54CA217378-05
Complexity, Cooperation and Community in Cancer
National Institutes of Health
Grant: 1R01GM152494-01
Development of tools for analyzing cell-cell communication using spatial transcriptomic data
National Institutes of Health
Grant: 5P30AR075047-04
Skin Biology Resource-Based Center at UCI
National Institutes of Health
Grant: 1R01AR081671-01A1
Cell Transitions during Bone Fracture Healing
National Institutes of Health
Grant: 5T32GM136624-05
Mathematical, Computational and Systems Biology
National Institutes of Health
Grant: 5R01CA237563-05
Phosphorylation-dependent regulation of GLI transcription factors
National Institutes of Health
Grant: 5R01DE019638-07
The role of continuous phenotypic variation in structural defects of the face
NIGMS NIH HHS
Grant: R01 GM152494
NCI NIH HHS
Grant: R01 CA237563
NIAMS NIH HHS
Grant: P30 AR075047
NIDCR NIH HHS
Grant: R01 DE019638
NIAMS NIH HHS
Grant: R01 AR081671
NCI NIH HHS
Grant: U54 CA217378
NIGMS NIH HHS
Grant: T32 GM136624
Fields of Study
Keywords
Sustainable Development Goals