Courses:

Computation for Biological Engineers >> Content Detail



Syllabus



Syllabus



Prerequisites


20.180



Assignments and Exams


There will be short assignments distributed at almost every lecture. We expect that all assignments will be turned in by midnight on the day they are due. You may discuss assignments with your classmates but we expect that you will submit your own work. Late assignments (up to one week late) will be given 1/2 credit; solutions for assignments will be posted at the posted due date. A family crisis or severe illness requiring attention from the infirmary and prohibiting you from all your coursework are acceptable reasons for missing an exam; every effort will be made to accommodate you in these exceptional circumstances. More information regarding academic integrity is available here.



Grading



ACTIVITIESPERCENTAGES
Problem Sets (Equally Weighted)60%
Exam 110%
Exam 210%
Exam 310%
Class Participation10%



Calendar


The course is divided into three modules, with exams at the end of each module.

Module 1: Phylogenetic Inference (Lec #1-8)

Module 2: Molecular Modeling / Protein Design (Lec #10-17)

Module 3: Discrete Reaction Event Network Modeling (Lec #19-24)

Each module covers the following general topics:

  1. Data Structure
  2. Optimization Problem
  3. Algorithms

LEC #TOPICSKEY DATES
Module 1: Phylogenetic Inference (PI) (Instructor: Prof. Alm)
1

Course Overview

Introduction to Phylogenetic Inference; Case Studies; Phylogenetic Trees; Quick Review of Recursion

2Review of UPGMA; Purpose of Phylogenetics; Newick Notation
3

Phylogenetic Trees: Overview, Possible Trees

Python®: Trees; Data Structure, Parsing Function

Homework 1 due
4Parsimony; Sankoff Downpass AlgorithmHomework 2 due one day after Lec #4
5Downpass (cont.); Fitch's Up PassHomework 3 due
6Up Pass (cont.)Homework 4 due
7Parsimony (cont.); Overall Strategy; Maximum Likelihood (ML); Jukes-Cantor; Evolutionary Model
8

Greedy Algorithm for Trying Trees

Review

Homework 5 due five days after Lec #8
9Exam 1
Module 2: Molecular Modeling / Protein Design (MM/PD) (Instructor: Prof. Alm)
10Introduction to The Protein Design Problem. What Makes Proteins Fold? EntropyHomework 6 due
11MM/PD Lecture 2
12MM/PD Lecture 3
13Dihedrals, Build OrderHomework 7 due two days after Lec #13
14MM/PD Lecture 5
15MM/PD Lecture 6
16MM/PD Lecture 7Homework 8 due
17MM/PD Lecture 8
18Exam 2Homework 9 due two days after Exam 2
Module 3: Discrete Reaction Event Network Modeling (DRENM) (Instructor: Prof. Endy)
19When to Use Computational Methods vs. Exact Methods; The Physics Model Underlying Exact Methods
20Physics Model Underlying Exact Methods (cont.); Using Physics Model to Compute When a Reaction will Take Place
21Review of How Physics Model Leads to Computational Method; The Complete Computational Method (Gillespie's Direct and First Reaction Methods)
22Difference Between Reaction Rate and Reaction Propensity; Achieving Faster ComputationHomework 10 due five days after Lec #22
23Next Reaction Method Algorithm; Application to Genetic Memory (Latch)
24Review of Key ConceptsHomework 11 (optional) due
25Exam 3

 








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