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Custom-made zinc-finger nucleases (ZFNs) can induce targeted genome modifications with high efficiency in cell types including Drosophila, C. elegans, plants, and humans. A bottleneck in the application of ZFN technology has been the generation of highly specific engineered zinc-finger arrays. Here we describe OPEN (Oligomerized Pool ENgineering), a rapid,(More)
The identification and characterization of B-cell epitopes play an important role in vaccine design, immunodiagnostic tests, and antibody production. Therefore, computational tools for reliably predicting linear B-cell epitopes are highly desirable. We evaluated Support Vector Machine (SVM) classifiers trained utilizing five different kernel methods using(More)
RNA-protein interactions are vitally important in a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have developed a computational tool for predicting which amino acids of an RNA binding protein participate in RNA-protein interactions, using only the protein(More)
We report here an efficient method for targeted mutagenesis of Arabidopsis genes through regulated expression of zinc finger nucleases (ZFNs)-enzymes engineered to create DNA double-strand breaks at specific target loci. ZFNs recognizing the Arabidopsis ADH1 and TT4 genes were made by Oligomerized Pool ENgineering (OPEN)-a publicly available,(More)
Glycosylation is one of the most complex post-translational modifications (PTMs) of proteins in eukaryotic cells. Glycosylation plays an important role in biological processes ranging from protein folding and subcellular localization, to ligand recognition and cell-cell interactions. Experimental identification of glycosylation sites is expensive and(More)
RNA-protein interactions (RPIs) play important roles in a wide variety of cellular processes, ranging from transcriptional and post-transcriptional regulation of gene expression to host defense against pathogens. High throughput experiments to identify RNA-protein interactions are beginning to provide valuable information about the complexity of RNA-protein(More)
Understanding the molecular details of protein-DNA interactions is critical for deciphering the mechanisms of gene regulation. We present a machine learning approach for the identification of amino acid residues involved in protein-DNA interactions. We start with a Naïve Bayes classifier trained to predict whether a given amino acid residue is a DNA-binding(More)
Understanding interactions between proteins and RNA is key to deciphering the mechanisms of many important biological processes. Here we describe RNABindR, a web-based server that identifies and displays RNA-binding residues in known protein-RNA complexes and predicts RNA-binding residues in proteins of unknown structure. RNABindR uses a distance cutoff to(More)
Identifying B-cell epitopes play an important role in vaccine design, immunodiagnostic tests, and antibody production. Therefore, computational tools for reliably predicting B-cell epitopes are highly desirable. We explore two machine learning approaches for predicting flexible length linear B-cell epitopes. The first approach utilizes four sequence kernels(More)
Engineered zinc-finger nucleases (ZFNs) enable targeted genome modification. Here we describe context-dependent assembly (CoDA), a platform for engineering ZFNs using only standard cloning techniques or custom DNA synthesis. Using CoDA-generated ZFNs, we rapidly altered 20 genes in Danio rerio, Arabidopsis thaliana and Glycine max. The simplicity and(More)