Advanced search
Publication Cover
SAR and QSAR in Environmental Research Volume 13, 2002 - Issue 5
Submit an article Journal homepage
43
Views
18
CrossRef citations to date
0
Altmetric
Original Articles

Fragment generation and support vector machines for inducing SARs

S. Kramer Institute for Computer Science, Machine Learning Lab, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee Geb. 079, Freiburg i. Br., D-79110, Germany
,
E. Frank Department of Computer Science, University of Waikato, Hamilton, New Zealand
&
C. Helma Institute for Computer Science, Machine Learning Lab, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee Geb. 079, Freiburg i. Br., D-79110, Germany
Pages 509-523 | Published online: 29 Oct 2010

Citations (18)

Keep up to date with the latest research on this topic with citation updates for this article.

Subscribe to citation updates

Read on this site (2)

G. Cerruela García, B. Palacios-Bejarano, I. Luque Ruiz & M.Á. Gómez-Nieto. (2012) Comparison of representational spaces based on structural information in the development of QSAR models for benzylamino enaminone derivatives. SAR and QSAR in Environmental Research 23:7-8, pages 751-774.
Read now
A. Panaye, B. T. Fan, J. P. Doucet, X. J. Yao, R. S. Zhang, M. C. Liu & Z. D. Hu. (2006) Quantitative structure-toxicity relationships (QSTRs): A comparative study of various non linear methods. General regression neural network, radial basis function neural network and support vector machine in predicting toxicity of nitro- and cyano- aromatics to Tetrahymena pyriformis § . SAR and QSAR in Environmental Research 17:1, pages 75-91.
Read now

Articles from other publishers (16)

Fangfang Wang & Jinyi Xing. (2018) Classification of thyroid hormone receptor agonists and antagonists using statistical learning approaches. Molecular Diversity 23:1, pages 85-92.
Crossref
Quan Zhang, Lu Yan, Yan Wu, Li Ji, Yuanchen Chen, Meirong Zhao & Xiaowu Dong. (2017) A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals. Science of The Total Environment 580, pages 1268-1275.
Crossref
Rachid Darnag, Brahim Minaoui & Mohamed Fakir. (2017) QSAR models for prediction study of HIV protease inhibitors using support vector machines, neural networks and multiple linear regression. Arabian Journal of Chemistry 10, pages S600-S608.
Crossref
R. I. Nugmanov, T. I. Madzhidov, G. R. Khaliullina, I. I. Baskin, I. S. Antipin & A. A. Varnek. (2015) Development of “structure-property” models in nucleophilic substitution reactions involving azides. Journal of Structural Chemistry 55:6, pages 1026-1032.
Crossref
Edouard Pauwels, Véronique Stoven & Yoshihiro Yamanishi. (2011) Predicting drug side-effect profiles: a chemical fragment-based approach. BMC Bioinformatics 12:1.
Crossref
Daria Prilutsky, Boris Rogachev, Robert S. Marks, Leslie Lobel & Mark Last. (2011) Classification of infectious diseases based on chemiluminescent signatures of phagocytes in whole blood. Artificial Intelligence in Medicine 52:3, pages 153-163.
Crossref
FRANK HOONAKKER, NICOLAS LACHICHE, ALEXANDRE VARNEK & ALAIN WAGNER. (2012) A REPRESENTATION TO APPLY USUAL DATA MINING TECHNIQUES TO CHEMICAL REACTIONS — ILLUSTRATION ON THE RATE CONSTANT OF S N 2 REACTIONS IN WATER . International Journal on Artificial Intelligence Tools 20:02, pages 253-270.
Crossref
Frank Hoonakker, Nicolas Lachiche, Alexandre Varnek & Alain Wagner. 2010. Trends in Applied Intelligent Systems. Trends in Applied Intelligent Systems 318 326 .
Xiuli Sun, Yan Li, Xianjie Liu, Jun Ding, Yonghua Wang, Hui Shen & Yaqing Chang. (2008) Classification of bioaccumulative and non-bioaccumulative chemicals using statistical learning approaches. Molecular Diversity 12:3-4, pages 157-169.
Crossref
Quan Liao, Jianhua Yao & Shengang Yuan. (2007) Prediction of mutagenic toxicity by combination of Recursive Partitioning and Support Vector Machines. Molecular Diversity 11:2, pages 59-72.
Crossref
Paolo Mazzatorta, Liên-Anh Tran, Benoît Schilter & Martin Grigorov. (2006) Integration of Structure−Activity Relationship and Artificial Intelligence Systems To Improve in Silico Prediction of Ames Test Mutagenicity. Journal of Chemical Information and Modeling 47:1, pages 34-38.
Crossref
Fabian Birzele & Stefan Kramer. (2006) A new representation for protein secondary structure prediction based on frequent patterns. Bioinformatics 22:21, pages 2628-2634.
Crossref
Quan Liao, Jianhua Yao & Shengang Yuan. (2006) SVM approach for predicting LogP. Molecular Diversity 10:3, pages 301-309.
Crossref
Christoph Helma. 2005. Predictive Toxicology. Predictive Toxicology 479 499 .
X. J. Yao, A. Panaye, J. P. Doucet, R. S. Zhang, H. F. Chen, M. C. Liu, Z. D. Hu & B. T. Fan. (2004) Comparative Study of QSAR/QSPR Correlations Using Support Vector Machines, Radial Basis Function Neural Networks, and Multiple Linear Regression. Journal of Chemical Information and Computer Sciences 44:4, pages 1257-1266.
Crossref
Christoph Helma, Tobias Cramer, Stefan Kramer & Luc De Raedt. (2004) 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 44:4, pages 1402-1411.
Crossref

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.