In Silico Tools and Software to Predict ADMET of New Drug Candidates.

Kar S, Roy K, Leszczynski J

DOI: 10.1007/978-1-0716-1960-5_4
Published: 2022
Container: Methods in molecular biology (Clifton, N.J.)
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1007/978-1-0716-1960-5_4,
  title = {In Silico Tools and Software to Predict ADMET of New Drug Candidates.},
  author = {Kar S and Roy K and Leszczynski J},
  year = {2022},
  journal = {Methods in molecular biology (Clifton, N.J.)},
  doi = {10.1007/978-1-0716-1960-5_4},
  url = {https://doi.org/10.1007/978-1-0716-1960-5_4}
}

RIS

TY  - JOUR
TI  - In Silico Tools and Software to Predict ADMET of New Drug Candidates.
AU  - Kar S
AU  - Roy K
AU  - Leszczynski J
PY  - 2022
JO  - Methods in molecular biology (Clifton, N.J.)
DO  - 10.1007/978-1-0716-1960-5_4
UR  - https://doi.org/10.1007/978-1-0716-1960-5_4
ER  -

APA

S, K., K, R., & J, L. (2022). In Silico Tools and Software to Predict ADMET of New Drug Candidates.. Methods in molecular biology (Clifton, N.J.). https://doi.org/10.1007/978-1-0716-1960-5_4

Source records

pubmed · retrieved 2026-09-26T17:11:34.424Z
europe-pmc · retrieved 2026-09-26T17:11:34.101Z