Bioinformatics G53BIO

1. BioinformaticsG53BIO Dr. Jaume Bacardit http://www.cs.nott.ac.uk/~jqb/G53BIO/

2. What is Bioinformatics? • Several definitions exist. Michael Liebman proposed a quite elegant definition: • “The study of the information content and information flow in biological systems and processes” (Michael Liebman) • Information content: genome project • Information flow: molecular transport • Biological systems: cells, organisms, … • Biological processes: metabolic networks • Bioinformatics is the science of using information to understand aspects of Biology. That is, a discipline where techniques such as applied mathematics, computer science, statistics, artificial intelligence, etc. are integrated to solve biological problems

3. Information, information, information As we know there have been major advances in the field of molecular biology These have been coupled with advances in laboratory (post)genomic technology This has led to an explosive growth in the collection of biological information This deluge of information has led to an absolute requirement for • Computerized databases to store, organise and index the data • For specialized tools to view and analyse the data • Specialized tools to infer new knowledge from the data

4. Areas of research(taxonomy of the Bioinformatics Journal) Genome Analysis Sequence Analysis Phylogenetics Structural Bioinformatics Gene Expression Genetics and Population Analysis Systems Biology Data and Text Mining Databases and Ontologies Bioimage Informatics

5. Educational Aims: • To introduce you to basic biological knowledge. • To demonstrate the importance of computer science, and its impact, in modern biological and biomedical challenges. • To understand the computational aspects of biological and biomedical problems. • To introduce the goals and challenges of research in the computational and mathematical aspects of bioinformatics and computational biology

6. What are the aims of this module? To entice you to develop analytical skills as to be able to tackle an inherent multi-disciplinary field. The successful completion of the module will endow you with: • Entry-level understanding of biological problems such as DNA sequencing and mapping, secondary and tertiary protein structure prediction, protein structure comparison, protein sequencing, philogenetics, gene expression, metabolic pathways. • Understanding of the computational problems associated with these biological problems from the point of view of modelling, computational complexity and algorithms. • Familiarity with the operation, and principles behind, bioinformatics public web-servers, open source projects and other bioinformatics tools that are available in the public domain.

7. Module Activities: • Lectures: ~ 20 total, 1 two-hour lecture per week. • Labs: ~ 20 total, 1 two-hour lab per week. • Self-learning:15 hours for thematic survey background reading and discussions with students and staff. • Thematic survey: 15 hours for the preparation of a written report on thematic survey. • Project: 30 hours for individual project. Assessment details: This module is 100% assessed by coursework that involves: Survey Report = 50% Experimental project = 50% DEADLINE : • The coursework has to be submitted by December 13th at 16:00

8. Survey 50% Project 50% Research and Learning Portfolio to be submitted as a package before the Christmas break. DEADLINE : The coursework has to be submitted by December 13th at 16:00 • The survey will be dedicated to the study of network motifs in systems and synthetic biology (SSB) • The project will be dedicated to the bioinformatics of proteins

9. Timetable • Lectures: Wednesdays from 9:00 to 11:00 • JC-BSSOUTH-A07 • Labs: Thursdays from 16:00 – 18:00 • JC-COMPSCI-B52 • Use the labs to weekly develop your portfolio! • The Coursework details will be published soon in the module’s web page • Labs start on 18/10

10. How to contact me? • At lectures and lab sessions • My office is B81 in the Computer Science building. However, if you randomly pop by the chances that I cannot attend you are high • Thus, the preferred contact method is email: jaume.bacardit@nottingham.ac.uk

11. Module Content • Introduction and learning outcomes • Introduction to Molecular Biology • Executable Biology • Genome Databases • DNA and Protein Sequence Alignment • Protein Structure Prediction • Phylogenetic Trees • Structural Databases • Comparing Protein Structures • Biological Data Mining Module Website: www.cs.nott.ac.uk/~jqb/G53BIO

12. Lectures and lab modality • We (joint with the guest lecturers) will use a set of lectures adapted from material created by the best researchers/teachers in the world. • Each topics by a different scholar hence different styles. Each the best in the topic. Beware, the slides *will* have different styles because of this! • We thank them for making this excellent teaching material available! • The labs are there for you to work on your project and general portfolio. This is a self-driven module

13. Recommended Readings • The module’s web site contains a detailed list of readings: http://www.cs.nott.ac.uk/~jqb/G53BIO/resources.html • Including • Books • Journals • Other electronic resources • At every lecture we will add specific recommended readings