Project Mentor

Dr. Paola Vera-Licona
Center for Quantitative Medicine

Undergraduate Research Opportunity Description

Project Description	The student involved in this project will apply computational systems biology and bioinformatics approaches to analyze gene expression RNA-seq data from Neuroblastoma cell lines to propose and prioritize combinations of therapeutic targets, that will then be provided to our collaborators for experimental validation. Bioinformatics tools will include the use of the software package geneXplain (http://genexplain.com/) and some R packages to visualize and analyze RNA-seq data. In addition, the student will learn to use some Cytoscape apps (http://www.cytoscape.org/) and customize them to our needs.
Project Direction	Our research group is focused on developing and applying bioinformatics, computational systems biology and mathematical biology approaches to identify combinations of therapeutic targets in cancer diseases such as neuroblastoma. Neuroblastoma is the most common extra-cranial solid tumor in children and the most frequent cancer in infants. While our knowledge of prognostic factors has increased in recent decades, few therapeutic breakthroughs have occurred. Together with our collaborators at UConn Health, the goal of this project is to reveal and validate potential new combinations of therapeutic targets.
Mentorship and Supervision	The student will be trained, in the first week, to use the geneXplain package (http://genexplain.com/) and the some basics of Cytoscape (http://www.cytoscape.org/) and one of our in-house developed apps, OCSANA (http://bioinfo-out.curie.fr/projects/ocsana/OCSANA.html). The student will have have some reading materials to familiarize with the algorithms applied to analyze the RNA-seq data as well as the basic concepts related to neuroblastoma and cancer systems biology. The reading materials as well as the student’s progress will be discussed in weekly meetings with the PI. If the findings of the student are suitable for publication, the PI will provide guidance on the manuscript preparation.
Student Qualifications	– Be proficient in at least one of the following programming languages: R, C++ or Java – Interest in computational systems biology and bioinformatics. Even if the student has no experience in these biomedical/computational biology/bioinformatics areas, motivation is extremely important. – Suitable for either computer science student, biological sciences, pharmacy studies or biomedical engineering student interested in computational systems biology and systems medicine.
Academic Year Time Commitment	9 hours/week
Schedule Options	To be determined in consultation with the selected student
Project Continuation	Fall 2017, Spring 2018, Summer 2018
Possible Thesis Project	Yes

Application

Submit an online application for this research opportunity using the form below. The application deadline is Thursday, March 2, 2017.

This application requires a cover letter, a resume or CV, an unofficial transcript, a brief statement of research interests, and a brief statement of career interests.