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Detecting Essential Proteins Based on Network Topology, Gene Expression Data, and Gene Ontology Information.

IEEE/ACM transactions on computational biology and bioinformatics
The identification of essential proteins in protein-protein interaction (PPI) networks is of great significance for understanding cellular processes. With the increasing availability of large-scale PPI data, numerous centrality measures based on netw...

HEMEsPred: Structure-Based Ligand-Specific Heme Binding Residues Prediction by Using Fast-Adaptive Ensemble Learning Scheme.

IEEE/ACM transactions on computational biology and bioinformatics
Heme is an essential biomolecule that widely exists in numerous extant organisms. Accurately identifying heme binding residues (HEMEs) is of great importance in disease progression and drug development. In this study, a novel predictor named HEMEsPre...

Sequence-Based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines.

Journal of chemical information and modeling
Carbohydrate-binding proteins play significant roles in many diseases including cancer. Here, we established a machine-learning-based method (called sequence-based prediction of residue-level interaction sites of carbohydrates, SPRINT-CBH) to predict...

PCE-FR: A Novel Method for Identifying Overlapping Protein Complexes in Weighted Protein-Protein Interaction Networks Using Pseudo-Clique Extension Based on Fuzzy Relation.

IEEE transactions on nanobioscience
Identifying overlapping protein complexes in protein-protein interaction (PPI) networks can provide insight into cellular functional organization and thus elucidate underlying cellular mechanisms. Recently, various algorithms for protein complexes de...

TMSEG: Novel prediction of transmembrane helices.

Proteins
Transmembrane proteins (TMPs) are important drug targets because they are essential for signaling, regulation, and transport. Despite important breakthroughs, experimental structure determination remains challenging for TMPs. Various methods have bri...

Predicting protein subcellular localization based on information content of gene ontology terms.

Computational biology and chemistry
Predicting the location where a protein resides within a cell is important in cell biology. Computational approaches to this issue have attracted more and more attentions from the community of biomedicine. Among the protein features used to predict t...

Purely Structural Protein Scoring Functions Using Support Vector Machine and Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics
The function of a protein is determined by its structure, which creates a need for efficient methods of protein structure determination to advance scientific and medical research. Because current experimental structure determination methods carry a h...

Eliciting the Functional Taxonomy from protein annotations and taxa.

Scientific reports
The advances of omics technologies have triggered the production of an enormous volume of data coming from thousands of species. Meanwhile, joint international efforts like the Gene Ontology (GO) consortium have worked to provide functional informati...

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

PloS one
Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine l...

OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method.

Journal of computational biology : a journal of computational molecular cell biology
In the two transmembrane protein types, outer membrane proteins (OMPs) perform diverse important biochemical functions, including substrate transport and passive nutrient uptake and intake. Hence their 3D structures are expected to reveal these funct...