inhouse matlab toolbox zp-explore (MathWorks Inc)
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inhouse matlab toolbox zp-explore
Inhouse Matlab Toolbox Zp Explore, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/inhouse+matlab+toolbox+zp-explore/10__1016_slash_j__chemolab__2011__11__012-69-11-12
Average 90 stars, based on 1 article reviews
Inhouse Matlab Toolbox Zp Explore, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/inhouse+matlab+toolbox+zp-explore/10__1016_slash_j__chemolab__2011__11__012-69-11-12
Average 90 stars, based on 1 article reviews
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2026-09
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other:Article Title: Predicting minimum alveolar concentration (MAC) of anesthetic agents by statistical modeling methods and theoretical descriptors derived from electrostatic potentials on molecular surface Article Snippet: Contents lists available at SciVerse ScienceDirect Chemometrics and Intelligent Laboratory Systems j ourna l homepage: www.e lsev ie r .com/ locate /chemolab Predicting minimum alveolar concentration (MAC) of anesthetic agents by statistical modeling methods and theoretical descriptors derived from electrostatic potentials on molecular surface Peng Sang a, Jian-Wei Zou a,b,⁎, Ya-Li Yu b, Mei-Lan Huang c a Department of Chemistry, Zhejiang University, Hangzhou 310027, China b Ningbo Institute of Technology, Zhejiang University, Ningbo 315104, China c School of Chemistry and Chemical Engineering, Queen's University, Belfast, BT9 5AD, UK ⁎ Corresponding author: Tel.. : +86 574 88229517; fa E-mail address: jwzou@nit.zju.edu.cn (J.-W. Zou).. 0169-7439/$ – see front matter © 2011 Elsevier B.V. All doi:10.1016/j.chemolab.2011.11.012 a b s t r a c t a r t i c l e i n f o Article history: Received 21 May 2011 Received in revised form 19 September 2011 Accepted 17 November 2011 Available online 2 December 2011 Keywords: General anesthetics Minimum alveolar concentration Statistical modeling methods Quantitative structure–activity relationship Molecular electrostatic potentials Some up-to-date modeling techniques, which include nonlinear support vector machine (SVM), leastsquares support vector machine (LSSVM), random forest (RF) and Gaussian process (GP), together with linear methods (multiple linear regression (MLR) and partial least-squares regression (PLS)) were employed to establish quantitative relationships between the structural descriptors and the minimum alveolar concentration (MAC). |