Analyzing scRNA-seq data by CCP-assisted UMAP and tSNE is a research paper published in PLoS ONE (2024). On theSindex it has a DataRank of 0. It has been cited 10 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 Aeronautics and Space Administration
Grant: 80NSSC21M0023
National Science Foundation
Grant: DMS-2052983
National Science Foundation
Grant: DMS-1761320
National Science Foundation
Grant: IIS-1900473
National Institute of Health
Grant: R01GM126189
National Institute of Health
Grant: R01AI164266
National Institute of Health
Grant: R35GM148196
Bristol-Myers Squibb
Grant: 65109
National Institutes of Health
Grant: 5R35GM148196-02
Discovery-Driven Mathematics and Artificial Intelligence for Biosciences and Drug Discovery
National Institutes of Health
Grant: 5R01GM126189-03
Synergistic integration of topology and machine learning for the predictions of protein-ligand binding affinities and mutation impacts
National Science Foundation
Grant: 2052983
Collaborative Research: Integrating Algebraic Topology, Graph Theory, and Multiscale Analysis for Learning Complex and Diverse Datasets
National Science Foundation
Grant: 1761320
Kinetics-Driven Drug Discovery Using Persistent Homology, Rare-Event Molecular Dynamics and Experimental Data
National Institutes of Health
Grant: 1R01AI164266-01A1
AI-based platform for predicting emerging vaccine-escape variants and designing mutation-proof antibodies
National Science Foundation
Grant: 1900473
III: Medium: De Rham-Hodge theory modeling and learning of biomolecular data
Pfizer
Michigan State University Foundation
Influential Citations
1
Fields of Study
MeSH Terms
Keywords