[Embrio-list] Announcement of 4 wk EMBRIO Intro Course starting June 3rd: Computational Understanding of Biological Systems and Data

[Ladd, Brent Thomas]

An opportunity for EMBRIO Students to learn together, as well as team up with our Research for Undergraduates cohort this summer:
Institute members have developed a new introductory course “Computational Understanding of Biological Systems and Data” from which we are especially offering a four-week version to you (non-credit, but with a certificate of completion available). The course orientation begins next Monday, June 3 with course times running from 10am – Noon on M, W, F during the four weeks of June. The course is designed to be a true introduction and on-ramp to learn about some of the foundational computational approaches being used in EMBRIO from a biological context, and with no pre-requisites required. You do NOT have to know anything about coding, or modeling, or computational methods to join and learn. Below is a broader sense of the purpose of the course.
Please reach out and contact one of the EMBRIO graduate student instructors below to learn about participating in the course.
Course Development Team and Instructors (alphabetically)
Janice Evans, janiceevans at purdue.edu<mailto:janiceevans at purdue.edu>, Professor, Biological Sciences & Assoc. Dean, College of Science
Brent Ladd, laddb at purdue.edu<mailto:laddb at purdue.edu>, Managing Director, EMBRIO Institute, Biomedical Engineering, College of Engineering
Nissa Larson, larso124 at purdue.edu<mailto:larso124 at purdue.edu> , Ph.D. Student, Biomedical Engineering, College of Engineering. Course Instructor.
Alejandra Magana, admagana at purdue.edu<mailto:admagana at purdue.edu>,  W.C. Furnas Professor in Enterprise Excellence, Computer & Information Technology, Polytechnic Institute, and Professor, Engineering Education
Soumi Mukherjee, mukher42 at purdue.edu ,  Ph.D Student, Biological Sciences, College of Science. Course Instructor.
Elsje Pienaar, epienaar at purdue.edu<mailto:epienaar at purdue.edu>, Associate Professor, Biomedical Engineering, College of Engineering.
Aby Abasiafak Udosen, audosen at purdue.edu<mailto:audosen at purdue.edu> , Ph.D. Student, Computer & Information Technology, Polytechnic Institute. Course Instructor.

Synopsis: “Computational Understanding of Biological Systems and Data”
Computational techniques are so central to the understanding of life that the next modern synthesis in biology will be driven by mathematical, computational, and statistical methods. Thus, biological training must integrate computational thinking as a cross-cutting practice for connecting the natural and engineered worlds. Many students in biology majors have limited prior computational exposure and are often math averse. There is a gap in available courses and training to support this critical need of providing a foundational “on ramp” for students to succeed in integrating computational thinking.
The aim of the course is to move students into the transdisciplinary space bringing knowledge and skills of computational modeling of complex cell biology processes. The result will be students with improved skills, knowledge, and conceptual understanding, in which students with foundational knowledge in biology will understand the modeling and simulation methods enabling them to collaborate with engineers to gain a deeper understanding of the complex processes of their chosen biological system.
We’ve developed graduated exercises that employ a recognizable biological context and data the students can best conceptualize. Using biology case studies, the online modules will incorporate a gradual introduction to the coding and conceptual understanding of modeling biological phenomena. Students will work in small teams toward progressively more complex computational models. The course will be delivered following an inverted-classroom approach where the introduction of new concepts and methods will be delivered online (in the form of a pre-lab assignments and video recordings) facilitated via a computational cognitive apprenticeship. Then, during the in-person class periods, students will engage in collaborative work in interdisciplinary teams to solve computational exercises and projects.


Brent T. Ladd, Senior Research Program Manager, EMBRIO Institute<https://www.purdue.edu/research/embrio/>
Weldon School of Biomedical Engineering, Purdue University
Office: Hall for Discovery Learning and Research, Ste. 203
207 S. Martin Jischke Drive
West Lafayette, IN 47907
laddb at purdue.edu

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