Structure-Activity Relationships on Purine and 2,3-Dihydropurine Derivatives as Antitubercular Agents: a Data Mining Approach

Data Mining Approach ◽

ChemInform Abstract: Three Data Mining Techniques to Improve Lazy Structure-Activity Relationships for Noncongeneric Compounds.

ChemInform ◽

10.1002/chin.200807195 ◽

2008 ◽

Vol 39 (7) ◽

Author(s):

Selina Sommer ◽

Stefan Kramer

Keyword(s):

Data Mining ◽

Data Mining Techniques ◽

Design, synthesis and investigation on the structure–activity relationships of N-substituted 2-aminothiazole derivatives as antitubercular agents

European Journal of Medicinal Chemistry ◽

10.1016/j.ejmech.2013.11.007 ◽

2014 ◽

Vol 72 ◽

pp. 26-34 ◽

Cited By ~ 40

Author(s):

Marco Pieroni ◽

Baojie Wan ◽

Sanghyun Cho ◽

Scott G. Franzblau ◽

Gabriele Costantino

Keyword(s):

Antitubercular Agents ◽

Design Synthesis ◽

Antitubercular Agents: Quantitative Structure Activity Relationships and Drug Design

Chemoinformatics: Directions Toward Combating Neglected Diseases ◽

10.2174/978160805183011201010069 ◽

2012 ◽

pp. 69-128

Keyword(s):

Drug Design ◽

Quantitative Structure ◽

Antitubercular Agents ◽

Quantitative Structure Activity Relationships

Structure Activity ◽

Three-Dimensional Quantitative Structure-Activity Relationships for a Large Series of Potent Antitubercular Agents

Letters in Drug Design & Discovery ◽

10.2174/157018008785777289 ◽

2008 ◽

Vol 5 (6) ◽

pp. 377-387 ◽

Cited By ~ 12

Author(s):

Carolina Andrade ◽

Livia Salum ◽

Kerly Mesquita Pasqualoto ◽

Elizabeth Ferreira ◽

Adriano Andricopulo

Keyword(s):

Three Dimensional ◽

Large Series ◽

Quantitative Structure ◽

Antitubercular Agents ◽

Quantitative Structure Activity Relationships

Structure Activity ◽

Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure—Activity Relationships of Noncongeneric Compounds.

ChemInform ◽

10.1002/chin.200439208 ◽

2004 ◽

Vol 35 (39) ◽

Cited By ~ 1

Author(s):

Christoph Helma ◽

Tobias Cramer ◽

Stefan Kramer ◽

Luc De Raedt

Keyword(s):

Machine Learning ◽

Data Mining ◽

Machine Learning Techniques ◽

Structure Activity ◽

Learning Techniques

Synthesis and structure-activity relationships of novel fused ring analogues of Q203 as antitubercular agents

European Journal of Medicinal Chemistry ◽

10.1016/j.ejmech.2017.05.021 ◽

2017 ◽

Vol 136 ◽

pp. 420-427 ◽

Cited By ~ 9

Author(s):

Sunhee Kang ◽

Young Mi Kim ◽

Heekyung Jeon ◽

Sejin Park ◽

Min Jung Seo ◽

...

Keyword(s):

Antitubercular Agents ◽

Structure Activity ◽

Fused Ring

Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds

Journal of Chemical Information and Computer Sciences ◽

10.1021/ci034254q ◽

2004 ◽

Vol 44 (4) ◽

pp. 1402-1411 ◽

Cited By ~ 105

Author(s):

Christoph Helma ◽

Tobias Cramer ◽

Stefan Kramer ◽

Luc De Raedt

Keyword(s):

Machine Learning ◽

Data Mining ◽

Machine Learning Techniques ◽

Structure Activity ◽

Learning Techniques

Structure–Activity Relationships of Pyrazolo[1,5-a]pyrimidin-7(4H)-ones as Antitubercular Agents

ACS Infectious Diseases ◽

10.1021/acsinfecdis.0c00851 ◽

2021 ◽

Author(s):

Sangmi Oh ◽

M. Daben J. Libardo ◽

Shaik Azeeza ◽

Gary T. Pauly ◽

Jose Santinni O. Roma ◽

...

Keyword(s):

Antitubercular Agents ◽

Three Data Mining Techniques To Improve Lazy Structure−Activity Relationships for Noncongeneric Compounds

Journal of Chemical Information and Modeling ◽

10.1021/ci600560m ◽

2007 ◽

Vol 47 (6) ◽

pp. 2035-2043 ◽

Cited By ~ 7

Author(s):

Selina Sommer ◽

Stefan Kramer

Keyword(s):

Data Mining ◽

Data Mining Techniques ◽

Structure-Activity Relationships of MDMA-Like Substances

PsycEXTRA Dataset ◽

10.1037/e496472006-001 ◽

1989 ◽

Cited By ~ 3

Author(s):

David E. Nichols ◽

◽

Robert Oberlender

Keyword(s):