Jack Rogers, Tanner Robart April 2012 New College of Florida Goals: To aid scientists and academics in using orange in the study of biology To possibly meet satisfactory criteria for our bioinformatic machine learning class without risk of failure wasting anything but time Learn about Orange widget creation, file parsing, metadata associations, and logistic regression algorithms Orange Widgets: Bioinformatic Data Converter Orange is very limited by the data types it can access The default file widget can read data from simple tab-delimited or comma-separated files, as well as files in C4.5 format and Weka’s .arrf files. Bioinformatic data sets come in a variety of very unique formats that store metadata in very differnt ways Be able to load files to data tables or convert to tab delimited format Support for .cel, .fasta, .chp, etc... whatever orange doesnt support and is convenient to implement Penalized Logistic Regression Very popular Logistic regression method over the last 5ish years in regards to bioinformatic machine learning journal articles not present in current widget implemented in many other machine learning libraries easy to reengineer possibly cut and paste if credit can be given without trouble