NDLI: Statistical prediction of the bioactivity of amoebapores peptide and its analogs

Content Provider	IEEE Xplore Digital Library
Author	Feifei Tian Fenglin Lv Li Zhong Li Yang
Copyright Year	2011
Description	Author affiliation: Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering College, Chongqing University, China (Feifei Tian; Fenglin Lv; Li Zhong; Li Yang)
Abstract	totally 77 physicochemical properties of amino acids are collected and used as the structural descriptors of peptide sequences, and based upon it several statistical models are constructed by using stepwise multiple regression (SMR) and partial least squares (PLS) regression. In both MRL and PLS model, the obtained correlation coefficients r are all above 0.95. And then the predictive capability of these statistical models is further confirmed by using leave-one-out (LOO) cross-validation technique. The modeling results show that hydrophobicity and electronic property have a fundamental influence on the minimal growth inhibitory concentration (MIC) and minimal lethal concentration (MLC) of amoebapores peptide and its analogs.
Starting Page	7109
Ending Page	7112
File Size	319178
Page Count	4
File Format	PDF
ISBN	9781424491728
e-ISBN	9781424491711
DOI	10.1109/RSETE.2011.5966003
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Amoebapores Microwave integrated circuits Antibacterial peptide statistical modeling Peptides Stepwise multiple regression Amino acids Anti-bacterial Partial least squares regression Indexes Immune system Biomedical engineering
Content Type	Text
Resource Type	Article

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