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AntAngioCOOL: computational detection of anti-angiogenic peptides
, Article Journal of Translational Medicine ; Volume 17, Issue 1 , 2019 ; 14795876 (ISSN) ; Khorsand, B ; Yousefi, A. A ; Kargar, M. J ; Shirali Hossein Zade, R ; Mahdevar, G ; Sharif University of Technology
BioMed Central Ltd
2019
Abstract
Background: Angiogenesis inhibition research is a cutting edge area in angiogenesis-dependent disease therapy, especially in cancer therapy. Recently, studies on anti-angiogenic peptides have provided promising results in the field of cancer treatment. Methods: A non-redundant dataset of 135 anti-angiogenic peptides (positive instances) and 135 non anti-angiogenic peptides (negative instances) was used in this study. Also, 20% of each class were selected to construct an independent test dataset (see Additional files 1, 2). We proposed an effective machine learning based R package (AntAngioCOOL) to predict anti-angiogenic peptides. We have examined more than 200 different classifiers to build...