Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
We describe and demonstrate the effectiveness of a method of predicting protein secondary structures, sheet regions in particular, using a class of stochastic tree grammars as rep...
Background: An important challenge in eukaryotic gene prediction is accurate identification of alternatively spliced exons. Functional transcripts can go undetected in gene expres...
Summary: We developed a Python package, ProDy, for structurebased analysis of protein dynamics. ProDy allows for quantitative characterization of structural variations in heteroge...
Background: Prediction of protein solvent accessibility, also called accessible surface area (ASA) prediction, is an important step for tertiary structure prediction directly from...