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Dive into the research topics where Jay Vyas is active.

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Featured researches published by Jay Vyas.


Nucleic Acids Research | 2009

Minimotif miner 2nd release: a database and web system for motif search

Sanguthevar Rajasekaran; Sudha Balla; Patrick R. Gradie; Michael R. Gryk; Krishna Kadaveru; Vamsi Kundeti; Mark W. Maciejewski; Tian Mi; Nicholas Rubino; Jay Vyas; Martin R. Schiller

Minimotif Miner (MnM) consists of a minimotif database and a web-based application that enables prediction of motif-based functions in user-supplied protein queries. We have revised MnM by expanding the database more than 10-fold to approximately 5000 motifs and standardized the motif function definitions. The web-application user interface has been redeveloped with new features including improved navigation, screencast-driven help, support for alias names and expanded SNP analysis. A sample analysis of prion shows how MnM 2 can be used. Weblink: http://mnm.engr.uconn.edu, weblink for version 1 is http://sms.engr.uconn.edu.


Frontiers in Bioscience | 2008

Viral infection and human disease--insights from minimotifs.

Krishna Kadaveru; Jay Vyas; Martin R. Schiller

Short functional peptide motifs cooperate in many molecular functions including protein interactions, protein trafficking, and posttranslational modifications. Viruses exploit these motifs as a principal mechanism for hijacking cells and many motifs are necessary for the viral life-cycle. A virus can accommodate many short motifs in its small genome size providing a plethora of ways for the virus to acquire host molecular machinery. Host enzymes that act on motifs such as kinases, proteases, and lipidation enzymes, as well as protein interaction domains, are commonly mutated in human disease, suggesting that the short peptide motif targets of these enzymes may also be mutated in disease; however, this is not observed. How can we explain why viruses have evolved to be so dependent on motifs, yet these motifs, in general do not seem to be as necessary for human viability? We propose that short motifs are used at the system level. This system architecture allows viruses to exploit a motif, whereas the viability of the host is not affected by mutation of a single motif.


Nucleic Acids Research | 2009

VENN, a tool for titrating sequence conservation onto protein structures

Jay Vyas; Michael R. Gryk; Martin R. Schiller

Residue conservation is an important, established method for inferring protein function, modularity and specificity. It is important to recognize that it is the 3D spatial orientation of residues that drives sequence conservation. Considering this, we have built a new computational tool, VENN that allows researchers to interactively and graphically titrate sequence homology onto surface representations of protein structures. Our proposed titration strategies reveal critical details that are not readily identified using other existing tools. Analyses of a bZIP transcription factor and receptor recognition of Fibroblast Growth Factor using VENN revealed key specificity determinants. Weblink: http://sbtools.uchc.edu/venn/.


PLOS ONE | 2011

HIVToolbox, an Integrated Web Application for Investigating HIV

David P. Sargeant; Sandeep Deverasetty; Yang Luo; Angel Villahoz Baleta; Stephanie Zobrist; Viraj Rathnayake; Jacqueline C. Russo; Jay Vyas; Mark A. Muesing; Martin R. Schiller

Many bioinformatic databases and applications focus on a limited domain of knowledge federating links to information in other databases. This segregated data structure likely limits our ability to investigate and understand complex biological systems. To facilitate research, therefore, we have built HIVToolbox, which integrates much of the knowledge about HIV proteins and allows virologists and structural biologists to access sequence, structure, and functional relationships in an intuitive web application. HIV-1 integrase protein was used as a case study to show the utility of this application. We show how data integration facilitates identification of new questions and hypotheses much more rapid and convenient than current approaches using isolated repositories. Several new hypotheses for integrase were created as an example, and we experimentally confirmed a predicted CK2 phosphorylation site. Weblink: [http://hivtoolbox.bio-toolkit.com]


BMC Genomics | 2009

A proposed syntax for Minimotif Semantics, version 1.

Jay Vyas; Ronald J. Nowling; Mark W. Maciejewski; Sanguthevar Rajasekaran; Michael R. Gryk; Martin R. Schiller

BackgroundOne of the most important developments in bioinformatics over the past few decades has been the observation that short linear peptide sequences (minimotifs) mediate many classes of cellular functions such as protein-protein interactions, molecular trafficking and post-translational modifications. As both the creators and curators of a database which catalogues minimotifs, Minimotif Miner, the authors have a unique perspective on the commonalities of the many functional roles of minimotifs. There is an obvious usefulness in standardizing functional annotations both in allowing for the facile exchange of data between various bioinformatics resources, as well as the internal clustering of sets of related data elements. With these two purposes in mind, the authors provide a proposed syntax for minimotif semantics primarily useful for functional annotation.ResultsHerein, we present a structured syntax of minimotifs and their functional annotation. A syntax-based model of minimotif function with established minimotif sequence definitions was implemented using a relational database management system (RDBMS). To assess the usefulness of our standardized semantics, a series of database queries and stored procedures were used to classify SH3 domain binding minimotifs into 10 groups spanning 700 unique binding sequences.ConclusionOur derived minimotif syntax is currently being used to normalize minimotif covalent chemistry and functional definitions within the MnM database. Analysis of SH3 binding minimotif data spanning many different studies within our database reveals unique attributes and frequencies which can be used to classify different types of binding minimotifs. Implementation of the syntax in the relational database enables the application of many different analysis protocols of minimotif data and is an important tool that will help to better understand specificity of minimotif-driven molecular interactions with proteins.


Proteins | 2011

A computational tool for identifying minimotifs in protein-protein interactions and improving the accuracy of minimotif predictions

Sanguthevar Rajasekaran; Jerlin Camilus Merlin; Vamsi Kundeti; Tian Mi; Aaron Oommen; Jay Vyas; Izua J. Alaniz; Keith Chung; Farah Chowdhury; Sandeep Deverasatty; Tenisha M. Irvey; David Lacambacal; Darlene Lara; Subhasree Panchangam; Viraj Rathnayake; Paula Watts; Martin R. Schiller

Protein–protein interactions are important to understanding cell functions; however, our theoretical understanding is limited. There is a general discontinuity between the well‐accepted physical and chemical forces that drive protein–protein interactions and the large collections of identified protein–protein interactions in various databases. Minimotifs are short functional peptide sequences that provide a basis to bridge this gap in knowledge. However, there is no systematic way to study minimotifs in the context of protein–protein interactions or vice versa. Here we have engineered a set of algorithms that can be used to identify minimotifs in known protein–protein interactions and implemented this for use by scientists in Minimotif Miner. By globally testing these algorithms on verified data and on 100 individual proteins as test cases, we demonstrate the utility of these new computation tools. This tool also can be used to reduce false‐positive predictions in the discovery of novel minimotifs. The statistical significance of these algorithms is demonstrated by an ROC analysis (P = 0.001). Proteins 2010.


Progress in Nuclear Magnetic Resonance Spectroscopy | 2010

Biomolecular NMR Data Analysis

Michael R. Gryk; Jay Vyas; Mark W. Maciejewski

Published by Elsevier B.V.


Journal of Biomolecular NMR | 2011

CONNJUR spectrum translator: an open source application for reformatting NMR spectral data.

Ronald J. Nowling; Jay Vyas; Gerard Weatherby; Matthew Fenwick; Heidi J. C. Ellis; Michael R. Gryk

NMR spectroscopists are hindered by the lack of standardization for spectral data among the file formats for various NMR data processing tools. This lack of standardization is cumbersome as researchers must perform their own file conversion in order to switch between processing tools and also restricts the combination of tools employed if no conversion option is available. The CONNJUR Spectrum Translator introduces a new, extensible architecture for spectrum translation and introduces two key algorithmic improvements. This first is translation of NMR spectral data (time and frequency domain) to a single in-memory data model to allow addition of new file formats with two converter modules, a reader and a writer, instead of writing a separate converter to each existing format. Secondly, the use of layout descriptors allows a single fid data translation engine to be used for all formats. For the end user, sophisticated metadata readers allow conversion of the majority of files with minimum user configuration. The open source code is freely available at http://connjur.sourceforge.net for inspection and extension.


Journal of Bacteriology | 2011

Extremely Variable Conservation of γ-Type Small, Acid-Soluble Proteins from Spores of Some Species in the Bacterial Order Bacillales

Jay Vyas; Jesse Cox; Barbara Setlow; William H. Coleman; Peter Setlow

γ-Type small, acid-soluble spore proteins (SASP) are the most abundant proteins in spores of at least some members of the bacterial order Bacillales, yet they remain an enigma from both functional and phylogenetic perspectives. Current work has shown that the γ-type SASP or their coding genes (sspE genes) are present in most spore-forming members of Bacillales, including at least some members of the Paenibacillus genus, although they are apparently absent from Clostridiales species. We have applied a new method of searching for sspE genes, which now appear to also be absent from a clade of Bacillales species that includes Alicyclobacillus acidocaldarius and Bacillus tusciae. In addition, no γ-type SASP were found in A. acidocaldarius spores, although several of the DNA-binding α/β-type SASP were present. These findings have elucidated the phylogenetic origin of the sspE gene, and this may help in determining the precise function of γ-type SASP.


international conference on information technology: new generations | 2012

An Open-Source Sandbox for Increasing the Accessibility of Functional Programming to the Bioinformatics and Scientific Communities

Matthew Fenwick; Colbert Sesanker; Martin R. Schiller; Heidi J. C. Ellis; M. Lee Hinman; Jay Vyas; Michael R. Gryk

Scientists are continually faced with the need to express complex mathematical notions in code. The renaissance of functional languages such as LISP and Haskell is often credited to their ability to implement complex data operations and mathematical constructs in an expressive and natural idiom. The slow adoption of functional computing in the scientific community does not, however, reflect the congeniality of these fields. Unfortunately, the learning curve for adoption of functional programming techniques is steeper than that for more traditional languages in the scientific community, such as Python and Java, and this is partially due to the relative sparseness of available learning resources. To fill this gap, we demonstrate and provide applied, scientifically substantial examples of functional programming, We present a multi-language source-code repository for software integration and algorithm development, which generally focuses on the fields of machine learning, data processing, bioinformatics. We encourage scientists who are interested in learning the basics of functional programming to adopt, reuse, and learn from these examples. The source code is available at: https://github.com/CONNJUR/CONNJUR-Sandbox (see also http://www.connjur.org).

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Michael R. Gryk

University of Connecticut Health Center

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Heidi J. C. Ellis

Western New England University

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Ronald J. Nowling

University of Connecticut Health Center

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Matthew Fenwick

University of Connecticut Health Center

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Gerard Weatherby

Western New England University

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Mark W. Maciejewski

University of Connecticut Health Center

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Vamsi Kundeti

University of Connecticut Health Center

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