MIT OpenCourseWare

Browse materialsMIT 20.181 · Fall 2006

Computation for Biological Engineers

Subjects: Biology · Engineering · Science

Art: PSM V09 D115 Pasteur apparatus for germ studies, 1876 · Public domain

Instructors: Prof. Eric Alm, Prof. Andrew Endy
Term: Fall 2006
Level: Undergraduate
What's inside: 1 lecture note · 43 other files · 4 web pages
Materials open: MIT OCW

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About this course

Source: MIT OpenCourseWare 20.181 Computation for Biological Engineers, Fall 2006, Prof. Eric Alm, Prof. Andrew Endy — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.

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Materials by section

Grouped by section, as MIT organized them. Not sequenced or ordered.

Lecture Notes

17 files

Assignments

22 files

Exams

Exam 3 with SolutionPDF Download

Study Materials

MIT OpenCourseWare, Prof. Eric Alm, Prof. Andrew Endy, 20.181 Computation for Biological Engineers, Fall 2006.

License: CC BY-NC-SA 4.0 · Edition: Fall 2006 · Open the original course on OCW ↗

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Computation for Biological Engineers

Before you start

What's here, and what isn't

Not included here

Materials by section

Lecture Notes

Assignments

Exams

Study Materials

Lecture 1: Course Overview Introduction to Phylogenetic Inference; Case Studies; Phylogenetic Trees; Quick Review of Recursion ( PDF )

Lecture 2: Review of UPGMA; Purpose of Phylogenetics; Newick Notation ( PDF )

Lecture 3: Phylogenetic Trees: Overview, Possible Trees Python®: Trees; Data Structure, Parsing Function ( PDF )

Lecture 4: Parsimony; Sankoff Downpass Algorithm ( PDF )

Lecture 5: Downpass (cont.); Fitch’s Up Pass ( PDF )

Lecture 6: Up Pass (cont.) ( PDF )

Lecture 7: Parsimony (cont.); Overall Strategy; Maximum Likelihood (ML); Jukes-Cantor; Evolutionary Model ( PDF )

Lecture 8: Greedy Algorithm for Trying Trees Review ( PDF )

Lecture 9: Exam 1

Lecture 10: Introduction to The Protein Design Problem. What Makes Proteins Fold? Entropy ( PDF )

Lecture 11: MM/PD Lecture 2

Lecture 12: MM/PD Lecture 3

Lecture 13: Dihedrals, Build Order ( PDF ) (Courtesy of Mike Yee. Used with permission.)

Lecture 14: MM/PD Lecture 5

Lecture 15: MM/PD Lecture 6

Lecture 16: MM/PD Lecture 7

Lecture 17: MM/PD Lecture 8

Lecture 18: Exam 2

Lecture 19: When to Use Computational Methods vs. Exact Methods; The Physics Model Underlying Exact Methods ( PDF )

Lecture 20: Physics Model Underlying Exact Methods (cont.); Using Physics Model to Compute When a Reaction will Take Place. ( PDF )

Lecture 21: Review of How Physics Model Leads to Computational Method; The Complete Computational Method (Gillespie’s Direct and First Reaction Methods) ( PDF )

Lecture 22: Difference Between Reaction Rate and Reaction Propensity; Achieving Faster Computation ( PDF )

Lecture 23: Next Reaction Method Algorithm; Application to Genetic Memory (Latch) ( PDF )

Lecture 24: Review of Key Concepts ( PDF 1 ) ( PDF 2 )

Lecture 25: Exam 3