Life Sciences Commons^™

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 Schiller

Life Sciences Faculty Research

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 …

Scireader Enables Reading Of Medical Content With Instantaneous Definitions, Patrick R. Gradie, Megan Litster, Rinu Thomas, Jay Vyas, Martin Schiller

Life Sciences Faculty Research

Background

A major problem patients encounter when reading about health related issues is document interpretation, which limits reading comprehension and therefore negatively impacts health care. Currently, searching for medical definitions from an external source is time consuming, distracting, and negatively impacts reading comprehension and memory of the material.

Methods

SciReader was built as a Java application with a Flex-based front-end client. The dictionary used bySciReader was built by consolidating data from several sources and generating new definitions with a standardized syntax. The application was evaluated by measuring the percentage of words defined in different documents. A survey was used …

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

Life Sciences Faculty Research

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.