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Protein Interaction Mapping

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Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network.

Molecular bioSystems
Protein-protein interactions (PPIs) play an important role in most of the biological processes. How to correctly and efficiently detect protein interaction is a problem that is worth studying. Although high-throughput technologies provide the possibi...

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

Medicinal chemistry (Shariqah (United Arab Emirates))
BACKGROUND: Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determini...

Computational Methods to Predict Protein Functions from Protein-Protein Interaction Networks.

Current protein & peptide science
Predicting functions of proteins is a key issue in the post-genomic era. Some experimental methods have been designed to predict protein functions. However, these methods cannot accommodate the vast amount of sequence data due to their inherent diffi...

An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

Methods in molecular biology (Clifton, N.J.)
Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to ...

Identification of self-interacting proteins by exploring evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix.

Oncotarget
Self-interacting Proteins (SIPs) play an essential role in a wide range of biological processes, such as gene expression regulation, signal transduction, enzyme activation and immune response. Because of the limitations for experimental self-interact...

Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.

Molecular bioSystems
Protein-protein interactions (PPIs) play a vital role in most biological processes. Hence their comprehension can promote a better understanding of the mechanisms underlying living systems. However, besides the cost and the time limitation involved i...

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

Journal of biosciences
Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown tha...

Protein interaction network constructing based on text mining and reinforcement learning with application to prostate cancer.

IET systems biology
Constructing interaction network from biomedical texts is a very important and interesting work. The authors take advantage of text mining and reinforcement learning approaches to establish protein interaction network. Considering the high computatio...