There is a need to train this generation of future biomedical scientists with strong knowledge and understanding of quantitative and computational skills in biology. The use of fundamental mathematical, statistical and computational techniques to study life and living organisms plays a central role in the development of predictive models based on fundamental biological and physical principles. Predictive models will accelerate our understanding of relevant biomedical process by enabling biomedical scientists to analyze and visualize complex biological process. The future generation of biomedical scientists must be equipped with appropriate data management and analysis tools that can enable them to develop an experimental design that includes a predictive model that can facilitate the approach to address and challenge existing knowledge before they even perform the first experimental measurement.
The specific aim of this supplement is to develop an active learning experience that can be used by undergraduate RISE E BASE students to learn and apply basic quantitative methods. To accomplish this specific aim, we have set forth the following objectives: (1)help RISE E BASE students to become acquainted with computational biology by requiring an introductory course in computer programming (INGE 3016) and the online MIT Quantitative Biology course in the Fall 2020 term and (2) develop a hands on activity with this supplement where students can identify basic elements of the experimental design, including justification of research, identification of bias, variables, develop a hypothesis, data collection and statistical analysis and develop a simple computer program to construct a predictive model. We expect all UG RISE E BASE students to become acquainted with the use of statistics as part of the data analysis process and the development of basic computer programming approaches to build quantitative and predictive models. The principal outcome expected from this active learning experience is that 100 % of the RISE UG students will be able to perform statistical analysis and develop a computer program to model at least one component of their sponsored RISE E BASE nine (9) month in-campus and summer off- campus research experience We expect that 100 % of RISE E BASE students will be able to prepare and turn in an Experimental Design and poster by the end of the Spring term that includes the use of statistics and computer modeling as part of their data analysis sections for their research experience. The in- campus and off-campus PI of each student will write an evaluation on the use of statistics and the development of simple quantitative models in their research. The activities and outcomes, including any software code developed, of the active learning activities will be disseminated by publication in the RISE E BASE web page and peer review journal and poster and/or oral presentations at the bi-annual TWD program directors meeting.
There is a need to train this generation of future biomedical scientists with knowledge and understanding of quantitative and computational skills that can be used to develop predictive model to address relevant problems in biology. This supplement seeks to develop and implement an active learning experience for undergraduate RISE E BASE students to learn and apply basic statistical and quantitative methods and a simple predictive model of cancer and benign cell proliferation under various conditions.