GCB/CIS 535: Introduction to Bioinformatics
(Spring 2013)
Course Directors:
Stephen Master, MD, PhD
Department of Pathology and Laboratory Medicine
613A Stellar-Chance Labs
215-898-8198
srmaster@mail.med.upenn.edu
Benjamin F. Voight, PhD
Department of Pharmacology
Department of Genetics
10-126 Smilow Center for Translational Research (SCTR)
3400 Civic Center Blvd
215-746-8083
bvoight@upenn.edu
TAs:
Varun Aggarwala
Yih-Chii Hwang
avarun@mail.med.upenn.edu
yihhwang@mail.med.upenn.edu
Guest Lecturers:
Logan Everett
Shane Jensen
Kim Sharp
Li-San Wang
Maja Bucan
loganje@mail.med.upenn.edu
stjensen@wharton.upenn.edu
sharpk@mail.med.upenn.edu
lswang@mail.med.upenn.edu
bucan@mail.med.upenn.edu
Location/Time:
MW 10-11 AM
F
10-11 AM
Lecture
Lab
Office Hours:
Steve
Ben
Varun
Yih-Chii
Wed 11-12p
Tue 12-1 PM
By appointment
Wed 4-5 PM
By appointment
Mon 3-4 PM
By appointment
11-146 SCTR
11-146 SCTR
613A Stellar-Chance Labs
10-146 SCTR
10-146 SCTR
10-120 SCTR
1406 Blockley
Course web site:
Available through Blackboard (https://courseweb.library.upenn.edu/)
Course Description:
The course provides a broad overview of bioinformatics and computational biology as
applied to biomedical research. Course material will be geared towards answering
specific biological questions ranging from detailed analysis of a single gene through
whole-genome analysis, transcriptional profiling, and systems biology. The relevant
principles underlying these methods will be addressed at a level appropriate for biologists
without a background in computational sciences. This course should enable students to
integrate modern bioinformatics tools into their research program.
Should I take the course?
This course will emphasize hands-on experience with application to current biological
research problems. However, it is not intended for computer science students who want
to learn about biologically motivated algorithmic problems; GCB/CIS/BIO536 would be
more appropriate for such individuals. The course will assume a solid knowledge of
modern biology. An advanced undergraduate course such as BIO421 or a graduate course
in Biology such as BIOL526 (Experimental Principles in Cell and Molecular
Biology), BIOL527 (Advanced Molecular Biology and Genetics), BIOL528
(Advanced Molecular Genetics), BIOL540 (Genetic Systems), or equivalent, is a
prerequisite.
Equipment prerequisite: IMPORTANT
To accommodate for an increasing demand for this class, we now require that all students
bring a laptop to the lab session on Fridays. TAs will provide help with the material but
you should be well versed with your own laptop and should be willing/capable to
download and install free software off the internet.
Grading:
3 HW (45%); Labs (15%); Project (30%); Class participation (10%)
To be fair to all, late submission will be penalized: up to 2 days (10% off), up to 1 week
(30% off) after 1 week (80% off).
Reference Texts:
As this is still a rapidly moving field, there is no textbook required for this course. We
will rely on a combination of online material, lecture notes and powerpoint slides. Your
best bet for any topic is often to see if there has been a recent tutorial published in a
journal like PLOS Computational Biology. A link to these articles can be found at:
http://www.ploscollections.org/article/browseIssue.action?issue=info:doi/10.1371/issue.pcol.v03.
i02
In addition, the following books and online sources can serve as references:
1. Bioinformatics for Biologists, eds. Pavel Pevzner and Ron Shamir, Cambridge
University Press, 2011.
2. Bioinformatics and Functional Genomics by Jonathan Pevsner
(www.bioinfbook.org/). This compiles material used for a course at Johns Hopkins.
3. Bioinformatics for Dummies, by Jean-Michel Claverie, Cedric Notredame.
This is a hands-on reference for bioinformatics analysis without any description of
methods.
Date 9-­‐Jan 14-­‐Jan 16-­‐Jan Type Lecture Schedule Lecturer Lecture Intro/Databases Lecture Stats for Bioinformatics Lecture Sequence Alignment HW1 Distributed HW1 Due, HW2 Distributed 21-­‐Jan MLK -­‐ No Class 23-­‐Jan 28-­‐Jan 30-­‐Jan 4-­‐Feb 6-­‐Feb 11-­‐Feb 13-­‐Feb Lecture Next-­‐Gen Sequencing Technologies and Principles of Design Lecture Sequence Alignment for Next-­‐Gen Data Lecture Multiple Sequence Alignment Lecture Comparative Genomics Lecture Tree reconstruction Lecture Genomic Variation and its Discovery Lecture Analysis of Genetic Variation Voight Wang Wang Bucan Wang Voight Voight 18-­‐Feb Lecture Gene Expression Analysis -­‐ I Master 20-­‐Feb 25-­‐Feb 27-­‐Feb Lecture Gene Expression Analysis -­‐ II Lecture Functional Analysis Lecture Proteomics Master Master Master -­‐ Due Dates Master Jensen Voight SPRING BREAK 11-­‐Mar Lecture Protein Domains and families Master 13-­‐Mar Lecture Protein Structure Visualization Sharp 18-­‐Mar 20-­‐Mar 25-­‐Mar 27-­‐Mar 1-­‐Apr 3-­‐Apr 8-­‐Apr 10-­‐Apr 15-­‐Apr 17-­‐Apr 19-­‐Apr 22-­‐Apr Lecture Lecture Lecture Lecture Lecture Lecture Lecture Lecture Lecture Lecture Lab Lecture Motif Discovery Detecting cis regulatory Modules Transcription Regulation Analysis Everett Everett Everett microRNA informatics Systems Biology -­‐ I Systems Biology -­‐ II Data Management for Informatics Student Presentations Student Presentations Student Presentations Student Presentations Student Presentations Voight Master Master Master -­‐ -­‐ -­‐ -­‐ -­‐ Date Type Lab Schedule 11-­‐Jan 18-­‐Jan 25-­‐Jan 1-­‐Feb 8-­‐Feb 15-­‐Feb 22-­‐Feb Lab Lab Lab Lab Lab Lab Lab #1: Seeking biological information online #2: Introduction to R #3: Looking for functional SNPs #4: Alignment, BLAST, Finding homologs/orthologs #5: Building phylogenies from alignments #6: Tools for the analysis of Genetic Variation #7: Interpreting gene expression data, Introduction to Mev 1-­‐Mar Lab Project Meeting 15-­‐Mar Lab #8:Deducing protein structures 22-­‐Mar Lab #9: Discovering novel motifs in promoters 5-­‐Apr 12-­‐Apr Lab Lab #10: microRNAs and their targets #11: Constructing regulatory networks HW2 Due, HW3 Distributed HW3 Due #11 Lab HW Due Project Due Due Dates -­‐ #1 Lab HW Due #2 Lab HW Due #3 Lab HW Due #4 Lab HW Due #5 Lab HW Due #6 Lab HW Due #7 Lab HW Due, Prelim Project Proposal -­‐ #8 Lab HW Due, Project Approval #9 Lab HW Due #10 Lab HW Due HW1 includes – Alignment, data bases, tree reconstruction HW2 includes – Gene expression, functional analysis, protein structure/proteomics HW3 includes – Motif discovery, microRNAs, networks