AIMC Topic: Sequence Analysis, Protein

Clear Filters Showing 141 to 150 of 266 articles

Protein binding hot spots prediction from sequence only by a new ensemble learning method.

Amino acids
UNLABELLED: Hot spots are interfacial core areas of binding proteins, which have been applied as targets in drug design. Experimental methods are costly in both time and expense to locate hot spot areas. Recently, in-silicon computational methods hav...

A novel alignment-free method to classify protein folding types by combining spectral graph clustering with Chou's pseudo amino acid composition.

Journal of theoretical biology
The present work employs pseudo amino acid composition (PseAAC) for encoding the protein sequences in their numeric form. Later this will be arranged in the similarity matrix, which serves as input for spectral graph clustering method. Spectral metho...

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic...

S-SulfPred: A sensitive predictor to capture S-sulfenylation sites based on a resampling one-sided selection undersampling-synthetic minority oversampling technique.

Journal of theoretical biology
Protein S-sulfenylation is a reversible post-translational modification involving covalent attachment of hydroxide to the thiol group of cysteine residues, which is involved in various biological processes including cell signaling, response to stress...

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

Journal of theoretical biology
Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid ...

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...

predCar-site: Carbonylation sites prediction in proteins using support vector machine with resolving data imbalanced issue.

Analytical biochemistry
The carbonylation is found as an irreversible post-translational modification and considered a biomarker of oxidative stress. It plays major role not only in orchestrating various biological processes but also associated with some diseases such as Al...

Protein sequence-similarity search acceleration using a heuristic algorithm with a sensitive matrix.

Journal of structural and functional genomics
Protein database search for public databases is a fundamental step in the target selection of proteins in structural and functional genomics and also for inferring protein structure, function, and evolution. Most database search methods employ amino ...

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

PLoS computational biology
MOTIVATION: Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predict...

Combining sequence and Gene Ontology for protein module detection in the Weighted Network.

Journal of theoretical biology
Studies of protein modules in a Protein-Protein Interaction (PPI) network contribute greatly to the understanding of biological mechanisms. With the development of computing science, computational approaches have played an important role in locating ...