Collaborating All the Way to the Top

Abstract

The classes I teach have a predictive modeling component. As a student, havingà
participated in blind protein structure prediction competitions (CASP,à
http://predictioncenter.org) and data mining competitions like KDD Cup, I haveà
implemented this form of competitions in my bioinformatics and data mining classes. This semester I extended this idea to a different class (Parallel Computing).à

Specifically, as part of an assignment (or final project) students have to train a predictiveà
models to distinguish a specific class of proteins called "solenoids" using the availableà
protein sequence information. As part of this competition, the truth-values are hiddenà
from the students and they have to make a prediction (guess) and submit their results toà
the instructor. The instructor then evaluates the results using the truth-values andà
provides a ranking of the class students based on the predictive performance. Theà
concepts introduced in class allow the students to build base line predictive models, butà
to improve performance, students have to research, think critically and come up withà
innovative solutions.à

In my past two implementations of this project, I have used an in-house evaluation scriptà
and requested participants to send me solutions via a simple web server. Both times, theà
assignment was run for a 4-week period. I have also used technologies like Kaggle to setup this competition.à

In the future, I would like to implement the competition for the duration of theà
semester. Students would be taught a concept, and they would implement the sameà
towards improving their predictive models and engineer better solutions as new,à
advanced concepts are taught.

I am also developing a model that allows students to achieve these projects in a collaborative fashion by enabling resources like Wikis and other tools. As such, this session will be an introduction to the tools used and how they could be adapted to general purpose classes