Year 1
I-BioSTeP trainees will complete core courses within their own individual graduate groups, while doing research rotations in assigned faculty labs. In Fall year 1, trainees will also take the semester-long 1- unit Responsible Conduct of Research Course (required across all participating graduate groups) and two semesters of their group’s 1-unit seminar series.
Trainees will complete the introductory I-BioSTeP course on Molecular and Cellular Biotechnology during their year 1 semester in Spring.
Molecular and Cellular Biotechnology
Current state-of-the-art techniques and concepts in molecular and cellular biotechnology will be introduced. Topics include bioinformatics, molecular dynamics simulations, systems modeling, protein engineering, biomolecular assemblies, drug and gene delivery, recombinant DNA, tissue engineering, single molecule measurements, optogenetics, CRISPR, in vivo imaging, biomaterials, bioelectronics. Students will also receive training in fellowship proposal writing and will engage in a mentored process to write an NIH F31 style fellowship proposal by the end of the semester
Year 2
The trainees will focus exclusively on research with their chosen advisors and complete the two I-BioSTeP courses, one in the Fall semester and one in Spring, which will serve as electives in their respective primary graduate programs:
Imaging and Spectroscopy
This is a semester-long course, taken by trainees in Fall of Year 2, that will emphasize laboratory experience for students after assimilation of the theoretical basis of different imaging and spectroscopic techniques. It will start by introducing current biomedical problems and related research to students, who will need to envision ways to improve our understanding and/or to advance toward potential solutions.
Computation and Modeling
This will include Atomistic Molecular Dynamics (Protein Structure), Coarse grained Molecular Dynamics (to model long-chain macromolecules, e.g. DNA or cell cytoskeletal proteins), Monte Carlo simulations including the Gillespie algorithm (to model chemical reactions in the cellular environment, as well as larger scale ecological processes such as bacterial colony formation and foraging ), mathematical modeling using PDEs (to model the mechanics of fluid flows and elastic deformations in cells and biomaterials) and ODEs to model systems-level networks such as in intercellular signaling) and also on statistical modeling, data and image analysis (important for all quantitative analysis of biological research including in cell and developmental biology).
