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Protein contact map prediction is useful for protein folding rate prediction, model selection and 3D structure prediction. Here we describe NNcon, a fast and reliable contact map prediction server and software. NNcon was ranked among the most accurate residue contact predictors in the Eighth Critical Assessment of Techniques for Protein Structure Prediction(More)
Neuropeptides are an important class of signaling molecules that result from complex and variable posttranslational processing of precursor proteins and thus are difficult to identify based solely on genomic information. Bioinformatics prediction of precursor cleavage sites can support effective biochemical characterization of neuropeptides. Neuropeptide(More)
Evaluating the quality of protein structure models is important for selecting and using models. Here, we describe the MULTICOM series of model quality predictors which contains three predictors tested in the CASP8 experiments. We evaluated these predictors on 120 CASP8 targets. The average correlations between predicted and real GDT-TS scores of the two(More)
The ventricular-subventricular zone harbors neural stem cells (NSCs) that can differentiate into neurons, astrocytes, and oligodendrocytes. This process requires loss of stem cell properties and gain of characteristics associated with differentiated cells. miRNAs function as important drivers of this transition; miR-124, -128, and -137 are among the most(More)
Knowing the quality of a protein structure model is important for its appropriate usage. We developed a model evaluation method to assess the absolute quality of a single protein model using only structural features with support vector machine regression. The method assigns an absolute quantitative score (i.e. GDT-TS) to a model by comparing its secondary(More)
Machine learning methods are widely used in bioinformatics and computational and systems biology. Here, we review the development of machine learning methods for protein structure prediction, one of the most fundamental problems in structural biology and bioinformatics. Protein structure prediction is such a complex problem that it is often decomposed and(More)
Identifying perturbed or dysregulated pathways is critical to understanding the biological processes that change within an experiment. Previous methods identified important pathways that are significantly enriched among differentially expressed genes; however, these methods cannot account for small, coordinated changes in gene expression that amass across a(More)
MOTIVATION Cells communicate with their environment via signal transduction pathways. On occasion, the activation of one pathway can produce an effect downstream of another pathway, a phenomenon known as crosstalk. Existing computational methods to discover such pathway pairs rely on simple overlap statistics. RESULTS We present Xtalk, a path-based(More)
Signaling pathways function as the information-passing mechanisms of cells. A number of databases with extensive manual curation represent the current knowledge base for signaling pathways. These databases motivate the development of computational approaches for prediction and analysis. Such methods require an accurate and computable representation of(More)
Analysis of signaling pathways and their crosstalk is a cornerstone of systems biology. Thousands of papers have been published on these topics. Surprisingly, there is no database that carefully and explicitly documents crosstalk between specific pairs of signaling pathways. We have developed XTalkDB (http://www.xtalkdb.org) to fill this very important gap.(More)