TY - JOUR
T1 - A survey of current trends in computational predictions of protein-protein interactions
AU - Wang, Yanbin
AU - You, Zhuhong
AU - Li, Liping
AU - Chen, Zhanheng
N1 - Publisher Copyright:
© 2020, Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2020/8/1
Y1 - 2020/8/1
N2 - Proteomics become an important research area of interests in life science after the completion of the human genome project. This scientific is to study the characteristics of proteins at the large-scale data level, and then gain a holistic and comprehensive understanding of the process of disease occurrence and cell metabolism at the protein level. A key issue in proteomics is how to efficiently analyze the massive amounts of protein data produced by high-throughput technologies. Computational technologies with low-cost and short-cycle are becoming the preferred methods for solving some important problems in post-genome era, such as protein-protein interactions (PPIs). In this review, we focus on computational methods for PPIs detection and show recent advancements in this critical area from multiple aspects. First, we analyze in detail the several challenges for computational methods for predicting PPIs and summarize the available PPIs data sources. Second, we describe the state-of-the-art computational methods recently proposed on this topic. Finally, we discuss some important technologies that can promote the prediction of PPI and the development of computational proteomics.
AB - Proteomics become an important research area of interests in life science after the completion of the human genome project. This scientific is to study the characteristics of proteins at the large-scale data level, and then gain a holistic and comprehensive understanding of the process of disease occurrence and cell metabolism at the protein level. A key issue in proteomics is how to efficiently analyze the massive amounts of protein data produced by high-throughput technologies. Computational technologies with low-cost and short-cycle are becoming the preferred methods for solving some important problems in post-genome era, such as protein-protein interactions (PPIs). In this review, we focus on computational methods for PPIs detection and show recent advancements in this critical area from multiple aspects. First, we analyze in detail the several challenges for computational methods for predicting PPIs and summarize the available PPIs data sources. Second, we describe the state-of-the-art computational methods recently proposed on this topic. Finally, we discuss some important technologies that can promote the prediction of PPI and the development of computational proteomics.
KW - computational proteomics
KW - protein feature extraction
KW - protein-protein interactions
KW - proteomics
UR - http://www.scopus.com/inward/record.url?scp=85077339609&partnerID=8YFLogxK
U2 - 10.1007/s11704-019-8232-z
DO - 10.1007/s11704-019-8232-z
M3 - 文献综述
AN - SCOPUS:85077339609
SN - 2095-2228
VL - 14
JO - Frontiers of Computer Science
JF - Frontiers of Computer Science
IS - 4
M1 - 144901
ER -