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Volumn 57, Issue 3, 2010, Pages 586-590

Ranking of QSAR models to predict minimal inhibitory concentrations toward Mycobacterium tuberculosis for a set of fluoroquinolones

Author keywords

Method comparison; Modeling; Neural networks; Prediction of antituberculosis activity; QSAR; Ranking

Indexed keywords


EID: 77957001536     PISSN: 13180207     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (19)

References (19)
  • 16
    • 77957002977 scopus 로고    scopus 로고
    • NIAID-Division of AIDS, HIV/OI/TB Therapeutics Database, accessed: May 27
    • NIAID-Division of AIDS, HIV/OI/TB Therapeutics Database http://chemdb2.niaid.nih.gov. (accessed: May 27, 2010).
    • (2010)
  • 17
    • 77957013219 scopus 로고    scopus 로고
    • Talete, srl. DRAGON for Windows Software for Molecular Descriptor Calculations, version 5.4
    • Talete, srl. DRAGON for Windows (Software for Molecular Descriptor Calculations), version 5.4. 2006.
    • (2006)
  • 19
    • 80051553414 scopus 로고    scopus 로고
    • Quantitative structureactivity relationship study of antitubercular fluoroquinolones
    • press, DOI: 10.1007/s11030-010-9238
    • N. Minovski, M. Vračko, T. Šolmajer, Quantitative structureactivity relationship study of antitubercular fluoroquinolones. Mol. Divers. (in press 2010) DOI: 10.1007/s11030-010-9238.
    • (2010) Mol. Divers
    • Minovski, N.1    Vračko, M.2    Šolmajer, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.