Protein structure prediction is a long-standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction metho...
Protein O-GlcNAcylation, involving the β-attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues, is an O-linked glycosylation catalyzed by O-GlcNAc transferase (OGT). Molecular level investigation of t...
Reversible posttranslational modification (PTM) plays a very important role in biological process by changing properties of proteins. As many proteins are multiply modified by PTMs, cross talk of PTMs is becoming an intriguing topic and draws much at...
Interdisciplinary sciences, computational life sciences
Aug 6, 2015
Protein's posttranslational modification (PTM) represents a major dynamic regulation of protein functions after the translation of polypeptide chains from mRNA molecule. Compared with the costly and labor-intensive wet laboratory characterization of ...
Motif identification is among the most common and essential computational tasks for bioinformatics and genomics. Here we proposed a novel convolutional layer for deep neural network, named variable convolutional (vConv) layer, for effective motif ide...
Transcription factors (TFs) play an important role in regulating gene expression, thus identification of the regions bound by them has become a fundamental step for molecular and cellular biology. In recent years, an increasing number of deep learnin...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2021
RNA-binding proteins (RBPs) have a significant role in various regulatory tasks. However, the mechanism by which RBPs identify the subsequence target RNAs is still not clear. In recent years, several machine and deep learning-based computational mode...
Journal of bioinformatics and computational biology
Apr 1, 2020
Presynaptic and postsynaptic neurotoxins are two types of neurotoxins from venomous animals and functionally important molecules in the neurosciences; however, their experimental characterization is difficult, time-consuming, and costly. Therefore, b...
Although convolutional neural networks (CNNs) have been applied to a variety of computational genomics problems, there remains a large gap in our understanding of how they build representations of regulatory genomic sequences. Here we perform systema...