Journal of bioinformatics and computational biology
Feb 4, 2018
Predicting the native poses of ligands correctly is one of the most important steps towards successful structure-based drug design. Binding affinities (BAs) estimated by traditional scoring functions (SFs) are typically used to score and rank-order p...
As one of the most intrinsically reactive amino acids, cysteine carries a variety of important biochemical functions, including catalysis and redox regulation. Discovery and characterization of cysteines with heightened reactivity will help annotate ...
Journal of bioinformatics and computational biology
Jun 13, 2017
Correct inference of genetic regulations inside a cell from the biological database like time series microarray data is one of the greatest challenges in post genomic era for biologists and researchers. Recurrent Neural Network (RNN) is one of the mo...
IEEE/ACM transactions on computational biology and bioinformatics
Mar 17, 2017
Automated protein function prediction is a challenging problem with distinctive features, such as the hierarchical organization of protein functions and the scarcity of annotated proteins for most biological functions. We propose a multitask learning...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 20, 2016
Protein-protein interaction (PPI) plays a key role in understanding cellular mechanisms in different organisms. Many supervised classifiers like Random Forest (RF) and Support Vector Machine (SVM) have been used for intra or inter-species interaction...
The article focus is the improvement of machine learning models capable of predicting protein expression levels based on their codon encoding. Support vector regression (SVR) and partial least squares (PLS) were used to create the models. SVR yields ...
Proceedings of the National Academy of Sciences of the United States of America
Apr 9, 2015
Transmembrane β-barrels (TMBs) carry out major functions in substrate transport and protein biogenesis but experimental determination of their 3D structure is challenging. Encouraged by successful de novo 3D structure prediction of globular and α-hel...
Thirty to seventy percent of proteins in any given genome have no assigned function and have been labeled as the protein "unknome." This large knowledge shortfall is one of the final frontiers of biology. Machine learning (ML) approaches are enticing...
The arginine dihydrolase pathway (arc operon) provides a metabolic niche by transforming arginine into metabolic byproducts. We investigate the role of the arc operon in probiotic Escherichia coli Nissle 1917 on human gut community assembly and healt...
Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting knowledge from this data are critical. Here, we assembled a top-down expression and regulation knowledge base for Escherichia coli. The expression component is a 1035-...
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