A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination is a research paper published in PLoS Computational Biology (2020). On theSindex it has a DataRank of 0. It has been cited 34 times.
Scored on demand from live citation data
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: R01AI123093
National Institutes of Health
Grant: R01HL110811
National Institutes of Health
Grant: UO1HL131072
National Institutes of Health
Grant: 5R01AI123093-02
Predicting protective T-cell responses in Tuberculosis using a systems biology approach
National Institutes of Health
Grant: 5U01HL131072-04
A Multi-scale systems pharmacology approach to TB therapy
National Institutes of Health
Grant: 4R01HL110811-05
Predicting immune responses that correlate with protection against tuberculosis
Fields of Study
Keywords
Sustainable Development Goals