It is of utmost importance to develop a computational method for accurate prediction of antioxidants, as they play a vital role in the prevention of several diseases caused by oxidative stress. In this correspondence, we present an effective computat...
BACKGROUND: Protein protein interactions (PPIs) are essential to most of the biological processes. The prediction of PPIs is beneficial to the understanding of protein functions and thus is helpful to pathological analysis, disease diagnosis and drug...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 8, 2021
Next-generation sequencing techniques provide us with an opportunity for generating sequenced proteins and identifying the biological families and functions of these proteins. However, compared with identified proteins, uncharacterized proteins consi...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Protein fold recognition is one of the most essential steps for protein structure prediction, aiming to classify proteins into known protein folds. There are two main computational approaches: one is the template-based method based on the alignment s...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
X-ray crystallography is the most popular approach for analyzing protein 3D structure. However, the success rate of protein crystallization is very low (2-10 percent). To reduce the cost of time and resources, lots of computation-based methods are de...
The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino acids on a grid. In-depth analyses of the pockets, frequently occurring atoms, influential distances...
IEEE journal of biomedical and health informatics
Oct 5, 2021
Biophysical protein-protein interactions perform dominant roles in the initiation and progression of many cancer-related pathways. A protein-protein interaction might play different roles in diverse cancer types. Hence, prioritizing the PPIs in each ...
It has been a landmark year for artificial intelligence (AI) and biotechnology. Perhaps the most noteworthy of these advances was Google DeepMind's AlphaFold2 algorithm which smashed records in protein structure prediction (Jumper et al., 2021, Natur...
Deep learning using neural networks relies on a class of machine-learnable models constructed using 'differentiable programs'. These programs can combine mathematical equations specific to a particular domain of natural science with general-purpose, ...
Graph representations are traditionally used to represent protein structures in sequence design protocols in which the protein backbone conformation is known. This infrequently extends to machine learning projects: existing graph convolution algorith...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.