Applications in Bioinformatics
ENG BF 527 / Fall 2009
Course Description:
The field of Bioinformatics is concerned with the management and analysis of
large biological datasets (such as the human genome) for the purpose of
improving our understanding of complex living systems. This course
introduces graduate students and upper-level undergraduate students to the
core problems in bioinformatics, along with the databases and tools that
have been developed to study them. Computer labs emphasize the
acquisition of practical bioinformatics skills for use in students’ research.
Familiarity with basic molecular biology is a prerequisite; no prior
programming knowledge is assumed. Specific topics will include the analysis
of biological sequences, structures, and networks.
Course Times and Location:
Lecture: Tue & Thu 3:00 – 4:00 PM in LSEB 105
Lab: Tue & Thu 4:00 – 5:00 PM in LSEB B03
Labs and Programming:
Labs will involve applying concepts learned during the lecture to practical
bioinformatics problems. Students will learn to use the major bioinformatics
databases as well as on- and off-line tools. Python programming will be
taught during lab, leading to the creation of small but useful bioinformaticsoriented programs. Homework assignments will be focused on practicing
skills introduced during labs.
Textbook:
There is no required text book. All reading materials will be provided in class
or through open access websites.
Instructor Information:
Eric Franzosa (franzosa@bu.edu) & Jignesh Parikh (jparikh@bu.edu)
Office location: LSEB 101
Office hours: Tue & Thu 1:30 – 2:30 PM
*NOTE* When sending general email, please put “BF527” in the subject line
Grading Policy:
Homework: 60% (written and computational)
Midterm: 15% (1 hour, Thursday, Oct 15th)
Participation: 10% (lecture and lab)
Final Exam: 15% (1 hour, Thursday, Dec 10th)
Incompletes will not be given
Collaboration / Academic Honesty:
Students may discuss homework with each other, but must not share
answers or code. All course participants must adhere to the CAS Academic
Conduct Code. All instances of academic dishonesty will be reported to the
academic conduct committee.
Homework Policy:
There will be a total of 6 homework assignments, distributed roughly once
every two weeks (four lectures). Assignments 1-5 are due one week after
they are assigned unless otherwise noted. Each assignment must be
submitted electronically before 3 PM on the due date. Late assignments will
be docked ten percentage points per day late (1% of the final grade). The
last homework (HW 6) will be a mini-project and *must* be turned in the
day of the final.
Course Schedule: #
1
2
Date
Thursday, September 03
Tuesday, September 08
3
Thursday, September 10
4
Tuesday, September 15
5
Thursday, September 17
6
Tuesday, September 22
7
8
9
Thursday, September 24
Tuesday, September 29
Thursday, October 01
10
11
Tuesday, October 06
Thursday, October 08
12
Tuesday, October 13
13
14
15
16
17
Thursday, October 15
Tuesday, October 20
Thursday, October 22
Tuesday, October 27
Thursday, October 29
18
Tuesday, November 03
19
Thursday, November 05
20
21
Tuesday, November 10
Thursday, November 12
22
Tuesday, November 17
23
Thursday, November 19
24
Tuesday, November 24
25
26
Thursday, November 26
Tuesday, December 01
Lecture
Class Introduction
Biological Sequences and
Sequencing Technology
Sequence Similarity and
Dot Plots
Global Alignment and
Dynamic Programming
Local and Semiglobal
Alignment, Scoring
Schemes
Statistics and Probability
Primer
Practical BLAST
BLAST Theory
Multiple Sequence
Alignment
Phylogenetic Trees
Machine Learning
Overview/ Midterm Review
NO CLASS: Monday
Schedule
MIDTERM EXAM
Gene Ontology
Gene Finding
TBA / Protein Domains
Transcription Factor
Binding Analysis
Microarray Technology and
Data
Protein Expression
Technology and Data
RNA Folding
Protein Structure
Technology and Data
Biological Network
Technology and Data
Network Statistics and
Motifs
Directed Networks I,
Signaling
NO CLASS: Fall Break
Directed Networks II,
27
Thursday, December 03
28
29
Tuesday, December 08
Thursday, December 10
Metabolic
TBA / Mini Project
(Homework 6)
TBA / Final Review
FINAL EXAM