CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials is a research paper published in Journal of Chemical Information and Modeling (2020). On theSindex it has a DataRank of 0.614. It has been cited 59 times.
Scored on demand from live citation data
Linked data & code
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.
Base Score Contribution
0.614
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →U.S. Department of Health and Human Services
Grant: ASPIRE Challenge Awards
U.S. Department of Health and Human Services
Grant: UL1TR001412
U.S. Department of Health and Human Services
Grant: UL1TR002529
U.S. Department of Health and Human Services
Grant: P30 CA023168
U.S. Department of Health and Human Services
Grant: 1DP1OD006779
Ralph W. and Grace M. Showalter Research Trust Fund
Grant: 41000370
Purdue University
Grant: Integrative Data Science Initiative Award
Javna Agencija za Raziskovalno Dejavnost RS
Grant: L7-8269
NLM NIH HHS
Grant: DP1 LM011509
NIH HHS
Grant: DP1 OD006779
Department of Chemistry, Purdue University
FWCI
4.27
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals