MOTIVATION: Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally r...
Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new method...
Impedimetric biosensors for measuring small molecules based on weak/transient interactions between bioreceptors and target analytes are a challenge for detection electronics, particularly in field studies or in the analysis of complex matrices. Prote...
MOTIVATION: Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries or polyadenylation site. Deep learning has become the a...
MOTIVATION: Fast and accurate prediction of protein-ligand binding structures is indispensable for structure-based drug design and accurate estimation of binding free energy of drug candidate molecules in drug discovery. Recently, accurate pose predi...
MOTIVATION: A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often ...
MOTIVATION: Protein-peptide interactions are one of the most important biological interactions and play crucial role in many diseases including cancer. Therefore, knowledge of these interactions provides invaluable insights into all cellular processe...
MOTIVATION: Knowledge of the correct protein subcellular localization is necessary for understanding the function of a protein and revealing the mechanism of many human diseases due to protein subcellular mislocalization, which is required before app...
Machine Learning (ML) models are very useful to predict physicochemical properties of small organic molecules, proteins, proteomes, and complex systems. These methods may be useful to reduce the cost of research in terms of materials resources, time,...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2018
Gene ontology (GO) is a controlled vocabulary of gene functions across all species, which is widely used for functional analyses of individual genes and large-scale proteomic studies. NaviGO is a webserver for visualizing and quantifying the relation...
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