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Comparative Study|Journal Article|Research Support, Non-U.S. Gov't |
| endingPage |
845 |
| issn |
0223-5234 |
| pageRange |
831-845 |
| publicationName |
European Journal of Medicinal Chemistry |
| startingPage |
831 |
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http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_172b63497eb85b496161ffb7c3217982 |
| bibliographicCitation |
Ventura C, Latino DARS, Martins F. Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds. European Journal of Medicinal Chemistry. 2013 Dec;70():831–45. doi: 10.1016/j.ejmech.2013.10.029. |
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http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0003-1618-4230 |
| date |
201312 |
| identifier |
https://pubmed.ncbi.nlm.nih.gov/24246731
https://doi.org/10.1016/j.ejmech.2013.10.029 |
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http://rdf.ncbi.nlm.nih.gov/pubchem/journal/21651
https://portal.issn.org/resource/ISSN/0223-5234 |
| language |
English |
| source |
https://www.crossref.org/
https://pubmed.ncbi.nlm.nih.gov/ |
| title |
Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds |
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