Integration of Informatics and Quantitative Concepts in Biology at UPR

The goal of this proposal is to increase the quantitative and informatics skills of undergraduate Biology majors at the University of Puerto Rico, Rio Piedras Campus.  It is aligned with the objective of the MARC U*STAR Program which is to increase the number of minority students that pursue graduate education in one of the STEM fields.  The National Research Council in its report “BIO2010: Transforming Undergraduate Education for Future Research Biologists” identified the need for Biology majors to receive a more quantitative and interdisciplinary education as undergraduates.  The Department of Biology, following this recommendation and an on-going comprehensive curricular revision, has delineated several strategies to address this issue.  This proposal aims to incorporate quantitative and informatics concepts and skills throughout the Biology curriculum.  Undergraduate laboratory courses are being targeted as they provide the perfect environment to offer our students quantitative and interdisciplinary research-like activities.  In addition, we will enrich our academic offering by describing new interdisciplinary courses to allow our students to be better prepared for their future academic or professional goals. Our proposed specific aims are:

  1. Design a course sequence that will promote the development of quantitative skills in biology majors.
  2. Integration of quantitative and computational skills into Biology’s laboratory courses.
  3. Increase the Bioinformatics and interdisciplinary course offering in the Biology Department.
  4. Interdisciplinary training of faculty and support personnel.

The proposed changes will be integrated into the Biology Department’s on-going comprehensive curricular revision as we expect that they will contribute to increase student’s interest in biological research and significantly improve our student competitiveness, particularly of those who pursue graduate studies.


This material is based upon work supported by the National Institutes of Health (NIH) under Grant # 5T36 GM 0078010.