341: Introduction to Bioinformatics, Spring 2013
Department of Computing, Imperial College London
Course Overview
Instructor Information
E-mail: natasha [at] imperial [dot] ac [dot] uk
Office: 407 C Huxley
Time and Location
Lecture time: Fridays, 3 – 6 pm (2 hours of lecture and 1 hour of tutorial)
Location: 144 Huxley
Office hours: Fridays after class, 407 C Huxley
Course Summary
The course will cover basic biological concepts related to the issues of sequence analysis and alignment, microarray data analysis, biological networks, fundamental graph theoretic algorithms, computational complexity and challenges in network analysis, existing post-genomic approaches for analyzing, modeling, and comparing biological networks, and applications of these approaches to understanding biological function, disease, and evolution. For more details, see the course syllabus below.
Practical work will be part of the coursework assignment and will include individual work on either: (a) development of code for a bioinformatics algorithm, or (b) data analysis. You will choose which option you will do. Completing only one of these two options will result in full marks. If you do both, both will be marked and you will be given the higher grade of the two.
Course Syllabus
For information about course goals, topics, organization, grading scheme, textbooks and readings, etc., please see the course syllabus.
There will be no Android programming taught in 2013.
Class Materials
Lecture Notes:
- Lecture 1: Course overview and Introduction to Biology. (in pdf)
- Lecture 2: Sequencing and Genomics (Prof. Guo)
- Lecture 3: Sequence Analysis (Prof. Guo). (in pdf)
- Lecture 4: Sequence Analysis (Prof. Guo). (in pdf)
- Tutorial 1 questions; Tutorial 1 answers.
- Lecture 5: Functional Genomics and Microarray Analysis (Prof. Guo). (in pdf)
- Lecture 6: Functional Genomics and Microarray Analysis continued (Prof. Guo). (in pdf)
- Tutorial 2 questions; Tutorial 2 answers.
- Lectures 7 and 8: Introduction to graph theory. (in pdf)
- OPTIONAL: Review of more graph algorithms; after slide 11 is optional reading and will not be assessed.
- Tutorial 3 questions; Tutorial 3 answers.
- Lectures 9 and 10: Protein 3D structure.
- Tutorial 4: questions and answers.
- Coursework – given out on Feb 20, due on Thursday, March 7, 2013 by 5pm.
- Lectures 11 and 12: Introduction to biological networks. (in pdf)
- Tutorial 5: NCBI, Uniprot, BLAST; Cytoscape.
- Lectures 13, 14 and 15: Network properties. (in pdf)
- Tutorial 6 questions; Tutorial 6 answers. GraphCrunch Tutorial.
- Lectures 15 and 16: Network properties and models. (in pdf)
- Tutorial 7: Questions; Answers.
- Lectures 17 and 18: Network comparisons and alignments. (in pdf)
- Lecture 18a: Software tools for network analysis and modeling
- Tutorial 8: Coursework model answers; Course review.
- Optional Lectures 17 and 18: Graph clustering; interplay of network topology and biological function. (in pdf)
Recommended readings:
Additional Readings
- Survey: “Graph-theoretic approaches for studying biological networks“, Tijana Milenkovic, PhD advancement, Univeristy of California, Irvine, 2008.
- Natasa Przulj and Tijana Milenkovic, “Computational Methods for Analyzing and Modeling Biological Networks“, a chapter in “Biological Data Mining”, edited by Jake Chen and Stefano Lonardi, Chapman & Hall/CRC; 1 edition, September 1, 2009.
- Sequence alignment (pdf, doc)
Useful Links
Coursework
- Coursework (Given out on February 20, 2013. Due on March 7, 2013 by 5pm.)
- Sample solution to coursework -- to be posted.
- Exam (Date to be determined.)
