The methodology for the pLogo generator was published online in the journal Nature Methods<\/i> on Oct. 6.<\/p>\n \u201cThis project represents a major goal of our lab, which is to create resources for the molecular biology research community that are user-friendly and as interactive as possible,\u201d says Daniel Schwartz, assistant professor of physiology and neurobiology and leader of the pLogo development team.<\/p>\n Schwartz conceived the algorithm that became the pLogo visualization strategy when he was a postdoctoral researcher at Harvard Medical School along with Michael Chou, who is currently a lecturer at Harvard Medical School. Schwartz and Chou both worked in the lab of George Church, professor of genetics at Harvard Medical School; all three are co-authors on the paper.<\/p>\n The program is remarkable not only for the new features it provides to the scientific community, but also for the work that went into its public debut: Schwartz drew on the computational and Web development expertise of several UConn computer science and engineering students to convert his visualization strategy into the Web-based tool.<\/p>\n Computer science Ph.D. student Saad Quader and undergraduate students Joey O\u2019Shea \u201914 (ENG) and Kevin Ryan \u201914 (ENG) are also co-authors on the paper, with O\u2019Shea billed as a co-first author.<\/p>\n \u201cIt is quite an achievement for an undergraduate student to be lead programmer on a project and co-first author on a paper published in Nature Methods<\/i>,\u201d says Schwartz.<\/p>\n pLogo at work<\/b><\/p>\n The new program allows users to visualize short linear patterns, or \u201cmotifs,\u201d in a biological molecule by producing a series of scaled, color-coded letters that represent the biological residues that make up the molecule. The size of each letter indicates the relative significance of a residue occurring at a particular position in a motif.<\/p>\n While pLogo is not the first open access logo generator, it does introduce several groundbreaking interactive features. Users supply a foreground data set, which they collect from a sample organism, and pLogo automatically generates a background data set that represents the entire set of proteins in that organism.<\/p>\n \u201cWith a foreground and background data set, we can compare and scale letters relative to their overall statistical significance instead of just their frequency of occurrence,\u201d says Schwartz. \u201cThis means we can determine if a data set generated in a lab is special and to what extent it is special.\u201d<\/p>\n In addition to the visualization, pLogo allows users to interact with their motif data in real time, which Schwartz says has never been offered before. Researchers can generate specific statistical information and new visualizations based on conditional probabilities by simply dragging their cursor over a letter.<\/p>\n The program has other \u201csmart\u201d attributes; it automatically detects and corrects formatting inconsistencies and proposes parameters for analyzing user data, which according to Schwartz may easily contain 5,000 or 10,000 sequences.<\/p>\n \u201cWe wanted the interface to be virtually effortless, with researchers being able to spend time on analysis rather than troubleshooting minor formatting errors in their data sets,\u201d he says.<\/p>\n![\"Daniel](\"https:\/\/today.uconn.edu\/wp-content\/uploads\/2013\/10\/DanSchwartz5.jpg\")
<\/a>![\"A](\"https:\/\/today.uconn.edu\/wp-content\/uploads\/2013\/10\/plogo-high-res-sumo.jpg\")
<\/a>
![\"Professor](\"https:\/\/today.uconn.edu\/wp-content\/uploads\/2013\/10\/Schwartz-group.jpg\")
<\/a>