Performance of rotation forest ensemble classifier and feature extractor in predicting protein interactions using amino acid sequences

[1] Chan HS(1993)The protein folding problem Phys Today 46 24-32

[2] Dill KA(2016)Construction of reliable protein–protein interaction networks using weighted sparse representation based classifier with pseudo substitution matrix representation features Neurocomputing 218 131-8

[3] Huang Y-A(2008)Principles of protein- protein interactions: What are the preferred ways for proteins to interact? Chemical Rev 108 1225-44

[4] You Z-H(2017)An improved sequence-based prediction protocol for protein-protein interactions using amino acids substitution matrix and rotation forest ensemble classifiers Neurocomputing 228 277-82

[5] Li X(2012)Fast parallel markov clustering in bioinformatics using massively parallel computing on gpu with cuda and ellpack-r sparse format IEEE/ACM Trans Comput Biol Bioinforma (TCBB) 9 679-92

[6] Chen X(2016)Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding BMC Bioinformatics 17 184-6

[7] Hu P(2013)A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition J Theoret Biol 320 41-94

[8] Li S(2015)Gram-positive and gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into chou’s general pseaac J Theoret Biol 364 284-20

[9] Luo X(2018)Texture and gene expression analysis of the mri brain in detection of alzheimer’s disease J Artif Intell Soft Comput Res 8 111-30

[10] Keskin O(2006)Rotation forest: A new classifier ensemble method IEEE Trans Pattern Anal Mach Intell 28 1619-10

[1] Chan HS(1993)The protein folding problem Phys Today 46 24-32

[2] Dill KA(2016)Construction of reliable protein–protein interaction networks using weighted sparse representation based classifier with pseudo substitution matrix representation features Neurocomputing 218 131-8

[3] Huang Y-A(2008)Principles of protein- protein interactions: What are the preferred ways for proteins to interact? Chemical Rev 108 1225-44

[4] You Z-H(2017)An improved sequence-based prediction protocol for protein-protein interactions using amino acids substitution matrix and rotation forest ensemble classifiers Neurocomputing 228 277-82

[5] Li X(2012)Fast parallel markov clustering in bioinformatics using massively parallel computing on gpu with cuda and ellpack-r sparse format IEEE/ACM Trans Comput Biol Bioinforma (TCBB) 9 679-92

[6] Chen X(2016)Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding BMC Bioinformatics 17 184-6

[7] Hu P(2013)A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition J Theoret Biol 320 41-94

[8] Li S(2015)Gram-positive and gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into chou’s general pseaac J Theoret Biol 364 284-20

[9] Luo X(2018)Texture and gene expression analysis of the mri brain in detection of alzheimer’s disease J Artif Intell Soft Comput Res 8 111-30

[10] Keskin O(2006)Rotation forest: A new classifier ensemble method IEEE Trans Pattern Anal Mach Intell 28 1619-10