Undergraduate Participation in Bioinformatics Training (UPBiT)
UPBit is funded in part by the National Science Foundation (NSF) through NSF’s Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences (UBM) program. The goal of the UBM activity is to enhance undergraduate education and training at the intersection of the biological and mathematical sciences and to better prepare undergraduate biology or mathematics students to pursue graduate studies and careers in fields that integrate the mathematical and biological sciences.
Research opportunities are available for UPBiT trainees to participate in individualized 3-year training programs starting in the sophomore year. Activities include communication workshops, lab training, research rotations, field trips, conferences, and specialized research projects. Trainees from two different disciplins will work together with joint mentorship by two faculty mentors in their collaborative research with the following themes:
- Biomolecular Sequence Analysis
- Ecoinformatics and Phylogenetic Analysis
- Microarray and Proteomics Data Analysis
- Molecular Structure Prediction.
UPBiT trainees will join our ongoing research projects involving graduate students and postdoctoral fellows supervised by faculty mentors. In most cases, they will have opportunities to participate in research design, data collection, data analysis, presentation, and publication. Please email to UPBiT@utep.edu or click one of the following to apply:
- Online UPBiT Application Form for Admission
- UPBiT Application Form (fillable form in Word)
- UPBiT Application Form (PDF) .
***Upcoming Talk on 7/22/16***
UPBiT alum Andrés Ortiz-Muñoz from CalTech will present a talk entitled " Computing with Molecules " in our upcoming UPBiT Friday Meeting at BE300, 2:00 p.m.
The Bioinformatics Rationale:
Technological improvements in instrumentation, computational abilities, information systems, and mathematical tools, with fast acquisition and availability of bioinformatics data, have transformed our understanding of life processes. Theoretical advances in complexity, dynamical systems, and uncertainty, coupled with advances in computational methods and modeling, have led to a rapid development of bioinformatics research in recent years. This has enabled expansion in the use of mathematics and statistics beyond the traditional fields of physical science and engineering. As that expansion has taken hold, the life sciences and other fields are posing new kinds of questions for the mathematical sciences, stimulating further the growth of mathematical ideas.