Efficient computational model for classification of protein localization images using Extended Threshold Adjacency Statistics and Support Vector Machines

Author:

Tahir MuhammadORCID,Jan Bismillah,Hayat Maqsood,Shah Shakir Ullah,Amin Muhammad

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference84 articles.

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2. A multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteins;Wang;PLoS One,2012

3. Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of chou’s pseudo amino acid composition;Chen;J. Theor. Biol.,2012

4. Subcellular localization prediction of apoptosis proteins based on evolutionary information and support vector machine;Xiang;Artif. Intell. Med.,2017

5. iloc-euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins;Chou;PLoS One,2011

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