Major Qualifying Project

Giving Students a Challenge—and a Competitive Edge

The Major Qualifying Project (MQP) is a high-level research project in the student's field. Through the MQP every WPI student has the chance to experience the kind of real-world problem solving that will soon characterize their professional careers. With an MQP on their resume, WPI students have a leg up on the competition when it comes to launching careers or gaining admission to the best graduate schools.

The MQP involves problems typical of those found in the fields of bioinformatics and computational biology, and addresses challenging research issues. These qualifying projects are far from trivial; each requires a substantial part of an academic year.

Get to know some of our students and learn how their MQP experience has direct ties to their success.

Project Title

Gene Expression Classification

Project Author

Gregory M Barrett, CS

Project Description

In this project, we constructed classification models for gene expression based on association rules. Gene expression patterns from cell types in the nematode C. elegans were used. The promoter regions associated with these genes were gathered. Motifs were mined from this data set. Multiple methods were used to select subsets of these motifs. Classification models were built from these subsets. The performance of these models was analyzed. A novel method of selecting motifs was shown to produce the best models. Learn more…


Project Title

Cluster Visualization of Upregulated HDAC1 in Mouse Using Integration of Treeview and Galaxy

Project Authors

Timothy Bonci

Project Description

In order to better understand genetic expression changes in experiments, microarray data is computer analyzed by tools such as the freely available Galaxy, which currently lacks microarray visualization. A visualization interface was built into the toolset using Python. It was enabled with selectable clustering algorithms which were used to analyze the RNA from mice infected with AAV to upregulate HDAC1 or LacZ. The HDAC enzymes have been shown to play a part in the negative regulation of types of learning. This clustering identifies other genes as likely actors in the chemistry of memory and learning. Learn more…