AIMC Topic: Protein Interaction Mapping

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Effect of Protein Repetitiveness on Protein-Protein Interaction Prediction Results Using Support Vector Machines.

Journal of computational biology : a journal of computational molecular cell biology
BACKGROUND: There are many computational approaches to predict the protein-protein interactions using support vector machines (SVMs) with high performance. In fact, performance of currently reported methods are significantly over-estimated and affect...

A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces.

International journal of molecular sciences
Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous publ...

Machine Learning of Protein Interactions in Fungal Secretory Pathways.

PloS one
In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict prote...

An improved method for predicting interactions between virus and human proteins.

Journal of bioinformatics and computational biology
The interaction of virus proteins with host proteins plays a key role in viral infection and consequent pathogenesis. Many computational methods have been proposed to predict protein-protein interactions (PPIs), but most of the computational methods ...

A knowledge-based approach for predicting gene-disease associations.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances of next-generation sequence technologies have made it possible to rapidly and inexpensively identify gene variations. Knowing the disease association of these gene variations is important for early intervention to treat de...

Effectively Identifying Compound-Protein Interactions by Learning from Positive and Unlabeled Examples.

IEEE/ACM transactions on computational biology and bioinformatics
Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been d...

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

Journal of theoretical biology
Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic si...

A New Feature Vector Based on Gene Ontology Terms for Protein-Protein Interaction Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-protein interaction (PPI) plays a key role in understanding cellular mechanisms in different organisms. Many supervised classifiers like Random Forest (RF) and Support Vector Machine (SVM) have been used for intra or inter-species interaction...

Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules.

BMC bioinformatics
BACKGROUND: It is generally acknowledged that a functional understanding of a biological system can only be obtained by an understanding of the collective of molecular interactions in form of biological networks. Protein networks are one particular n...

Detection of overlapping protein complexes in gene expression, phenotype and pathways of Saccharomyces cerevisiae using Prorank based Fuzzy algorithm.

Gene
Proteins show their functional activity by interacting with other proteins and forms protein complexes since it is playing an important role in cellular organization and function. To understand the higher order protein organization, overlapping is an...