BE.180

BE.180 -- Biological Engineering Programming

BE.180 is a new course that will be offered for the first time in the Spring of 2006. This is a required course for second semester sophomores who are majoring in Biological Engineering. Drew Endy is leading the development of the course.

The current course description is: "Example problems from biological engineering are used to develop structured computer programming skills and explore the theory and practice of complex systems design and construction."

After thinking a bit, talking with Tom Knight, and thinking some more, the theme of the course is starting to focus on the idea of designing and coding the CAD environment for Biological Engineering (aka, Engineering of Biology. aka, "synthetic biology: an engineering technology based on living systems." The way this might work is for a different CAD environment feature to be used each week as a motivating problem for exploring concepts in structured system design and implementation, and computer programming. As a result of this approach, there may not be any *single* language used in the course -- we'll use the languages best suited to the problems.

Current Tasks

1. Collect list of features that can serve as motivating examples
2. Prioirtize list of features, evaluating on coverage of concepts, fun factor, and feasibility

Next Planning Meeting

1. TBA & TBD (October 2005)

Feature Sandbox (add features ideas here, no idea is bad in the sandbox)

1. Analysis of Sequence Data for Patterns / Features
   • Manipulation of data/text
   • Pattern Recognition (regular expressions), Logic
2. Tuning Codon Usage
   • Codon tables
   • Expression optimization
   • Watermarking/Sign your work
   • Restriction site removal/addition
3. Some sort of graphing/visual depiction
4. Some sort of modeling/dynamic systems
5. Biological information representation (note, this is a half-baked idea, please contribute/revise - RS)
   • There are hierarchies of biological components (parts, devices and systems) and associated information. There are hierarchical data structures. How should biological information be represented? How do you search this information? Such a topic could conceivably cover topics/concepts like data structures, searching, object-oriented programming etc.
6. Search part-part junctions for secondary structure (e.g., ORF/RBS/Operator junctions)
   • Call-out to external tool
7. Clustering of parts, devices and systems
   • How do you group or categorize parts? How do you measure "distances" between systems? This becomes important as the registry gets bigger and as we move to a network of registries. I want to find all BioBricks that are "similar" to mine.
   • clustering methods
   • distance measures
8. Homology modeling (useful for synthetic transcription factors or designing linkers?)
   • Call-out to external tool
   • Simulated annealing, energy minimization, MD

Concepts in system design and implementation, and computer programming

In parallel with developing a features list, it may be appropriate to generate a list of fundamentals that students should take away from the course. (Credit to Bree for also suggesting this.) Features could be matched with concepts from CS (and lessons from biology) as appropriate. Started brainstorming a list here. -- RS

I think that it's important to make the teaching of programming concepts the primary goal, and the applications to biological engineering should be secondary. So students should all take away how to program, and in the process they may develop interesting and/or useful tools. Maybe the way to do it is to decide on the relevant programming concepts, and then come up with features as teaching examples and assignments that cover these concepts (not the other way around). I think that there is nothing wrong with teaching it like a normal introductory programming course, but using all biologically relevant examples and problems along the way. -- TMT

1. Data structures: linked lists, trees, stacks etc. Classes and inheritance?
2. Searching: depth-first, breadth-first, heuristic
3. Sorting
4. Computation: FSM's, Turing machines etc.

Prioritized Feature List

(vote for features here. HINT: use your intitials)