A multi-scale pipeline linking drug transcriptomics with pharmacokinetics predicts in vivo interactions of tuberculosis drugs is a research paper published in Scientific Reports (2021). On theSindex it has a DataRank of 0.649. It has been cited 26 times, with 9 citing works in its 1-hop citation network.
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?
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Base Score Contribution
0.494
From this paper's citation signal
Citation Network Contribution
0.155
From 7 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 9 citers.
National Institutes of Health
Grant: U01HL131072
National Institutes of Health
Grant: UL1TR002240
NIAID NIH HHS
Grant: R01 AI123093
NIAID NIH HHS
Grant: R01 AI150684
NIAID NIH HHS
Grant: U19 AI106761
National Institutes of Health
Grant: 5R01AI123093-02
Predicting protective T-cell responses in Tuberculosis using a systems biology approach
National Institutes of Health
Grant: 5UL1TR002240-02
Michigan Institute for Clinical and Health Research (MICHR)
National Institutes of Health
Grant: 5R01AI150684-04
Lesion-centric optimization of multidrug therapies for tuberculosis
National Institutes of Health
Grant: 1U19AI106761-01
Administrative Core
National Institutes of Health
Grant: 5U01HL131072-04
A Multi-scale systems pharmacology approach to TB therapy
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals