AIMC Topic: Protein Interaction Mapping

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A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

Computers in biology and medicine
Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interact...

Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase.

Scientific reports
The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are impo...

NewGOA: Predicting New GO Annotations of Proteins by Bi-Random Walks on a Hybrid Graph.

IEEE/ACM transactions on computational biology and bioinformatics
A remaining key challenge of modern biology is annotating the functional roles of proteins. Various computational models have been proposed for this challenge. Most of them assume the annotations of annotated proteins are complete. But in fact, many ...

Machine learning based identification of protein-protein interactions using derived features of physiochemical properties and evolutionary profiles.

Artificial intelligence in medicine
Proteins are the central constitute of a cell or biological system. Proteins execute their functions by interacting with other molecules such as RNA, DNA and other proteins. The major functionality of protein-protein interactions (PPIs) is the execut...

DeepPPI: Boosting Prediction of Protein-Protein Interactions with Deep Neural Networks.

Journal of chemical information and modeling
The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many proteins variants statistically associated with human disease, nearly all such variants have unknown mechanisms, for example,...

InterPred: A pipeline to identify and model protein-protein interactions.

Proteins
Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the numb...

Prior knowledge guided active modules identification: an integrated multi-objective approach.

BMC systems biology
BACKGROUND: Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or diseas...

Imputation for transcription factor binding predictions based on deep learning.

PLoS computational biology
Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard....

Evaluating the effect of annotation size on measures of semantic similarity.

Journal of biomedical semantics
BACKGROUND: Ontologies are widely used as metadata in biological and biomedical datasets. Measures of semantic similarity utilize ontologies to determine how similar two entities annotated with classes from ontologies are, and semantic similarity is ...