Intelligent systems in bioinformatics

1. Intelligent systems in bioinformatics Introduction to the course

2. Contact details Dr. Karen Page Computer Science - Room G50a Tel: 020 7679 3683 (internal: 33683) Email: k.page@cs.ucl.ac.uk http://www.cs.ucl.ac.uk/staff/K.Page

3. Lecture format • Monday and Thursday afternoons (2-5pm) – Pearson Lecture Theatre (Mon.) & Rm 229 (Thurs.) • We will take one or two 10/15-minute breaks, so typically the lecture might be split: 50-10-50-10-50 or 80-15-75

4. Coursework & Homework • Coursework: • 1 piece • 15% of total mark • towards end of course • Homework: • Each week (doesn’t contribute to course grade) • Attach cover sheet (http://www.cs.ucl.ac.uk/teaching/cwsheet.htm) • Give to JJ Giwa (G07) by 12pm on due date

5. Exam • Written exam • 15th March • 85% of total mark

6. Newsgroups/ Mailing list • All communication concerning this course will be done via the email list. • Please join by sending an email with Subject: join • to gi10-request@cs.ucl.ac.uk or local.cs.gi10 or 4c58-request@cs.ucl.ac.uk or local.cs.4c58

7. Useful Books • Alberts et al- Molecular Biology of the Cell • Stryer- Biochemistry • Baldi and Brunak – Bioinformatics – a machine learning approach • Durbin, Eddy, Krogh and Mitchison – Biological sequence analysis • Kanehisa - Post genome informatics • Lesk- Introduction to bioinformatics • Orengo, Jones and Thornton - Bioinformatics

8. The Course- motivation for biological material • Modern molecular biology and especially genomics has led to vast quantities of data: DNA/ protein sequence, gene expression. • This mainly consists of vast strings/ matrices of letters/ numbers, which in their raw form are not very interesting. • What’s needed now is synthesis of data and mining of data for patterns. • Intelligent systems techniques are very good for extracting useful patterns.

9. Motivation • In order to extract useful information, it is necessary to understand biological principles involved. • In this course we will introduce some basic molecular biology/ genomics and look at ways in which computers can be used to analyse it (bioinformatics), with a particular focus on intelligent systems techniques.

10. Course material content • I will give five three-hour blocks of lectures towards the start of the course. • Prof. David Jones will give the rest of the lectures. • Will now give a brief summary of the content of my lectures and a very brief one of his.

11. Content • Block 1: Biology • Introduction to course • Basic molecular biology • Cells, DNA, RNA, proteins, central dogma • Sequencing • Block 2: Genomics • History of genomics • Introduction to bioinformatics • Gene prediction

12. Content • Block 3: Microarrays • Microarray technology • Statistics • Analysis of microarray data • Block 5: Guest lectures (Systems biology and Gene networks) • Intelligent systems and software for systems biology (Dr. Peter Saffrey, UCL) • Bayesian networks (Dr. Lorenz Wernisch, Birkbeck) • Reverse engineering of gene networks from microarray data (Dr. Lorenz Wernisch)

13. Content • Block 8: Gene networks and Computational biology • Continuation of analysis of microarray data • Signalling pathways • Reverse engineering of networks from microarray data • Evolutionary games and evolutionary algorithms (if time)

14. Content • Below is a rough outline of what Prof. Jones will cover: Blocks 4,6,7,9 & 10: • Gene finding and basic sequence comparisons • Sequence comparisons; Hidden Markov Models; proteins • Databases; agent technology • Protein structure; structure classification; structure prediction • Protein structure prediction; drug discovery