TY - JOUR
T1 - Detection of protein-protein interactions from amino acid sequences using a rotation forest model with a novel PR-LPQ descriptor
AU - Wong, Leon
AU - You, Zhu Hong
AU - Li, Shuai
AU - Huang, Yu An
AU - Liu, Gang
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Protein-protein interactions (PPIs) play an essential role in almost all cellular processes. In this article, a sequence-based method is proposed to detect PPIs by combining Rotation Forest (RF) model with a novel feature representation. In the procedure of the feature representation, we first adopt the Physicochemical Property Response Matrix (PR) method to transform the amino acids sequence into a matrix and then employ the Local Phase Quantization (LPQ)-based texture descriptor to extract the local phrase information in the matrix. When performed on the PPIs dataset of Saccharomyces cerevisiae, the proposed method achieves the high prediction accuracy of 93.92 % with 91.10 % sensitivity at 96.45 % precision. Compared with the existing sequence-based method, the results of the proposed method demonstrate that it is a meaningful tool for future proteomics research.
AB - Protein-protein interactions (PPIs) play an essential role in almost all cellular processes. In this article, a sequence-based method is proposed to detect PPIs by combining Rotation Forest (RF) model with a novel feature representation. In the procedure of the feature representation, we first adopt the Physicochemical Property Response Matrix (PR) method to transform the amino acids sequence into a matrix and then employ the Local Phase Quantization (LPQ)-based texture descriptor to extract the local phrase information in the matrix. When performed on the PPIs dataset of Saccharomyces cerevisiae, the proposed method achieves the high prediction accuracy of 93.92 % with 91.10 % sensitivity at 96.45 % precision. Compared with the existing sequence-based method, the results of the proposed method demonstrate that it is a meaningful tool for future proteomics research.
KW - Local phase quantization
KW - Physicochemical property response matrix (PR)
KW - Protein-Protein interactions
KW - Rotation forest
UR - http://www.scopus.com/inward/record.url?scp=84983605925&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-22053-6_75
DO - 10.1007/978-3-319-22053-6_75
M3 - 会议文章
AN - SCOPUS:84983605925
SN - 0302-9743
VL - 9227
SP - 713
EP - 720
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 11th International Conference on Intelligent Computing, ICIC 2015
Y2 - 20 August 2015 through 23 August 2015
ER -