Bioinformatics is an interdisciplinary field that merges biology, computer science, and information technology. It is applied in areas like genomics, proteomics, and systems biology. While some basic analysis can be done through user-friendly tools, truly customized work requires programming skills and an understanding of underlying algorithms. Bioinformatics is not just a service field but rather involves scientific experimentation throughout the entire analysis process from experimental design to evaluation. It is a dedicated field of research in its own right, not a quick or interchangeable task.

1. Introduction to Bioinformatics A tale of myths and legends [Freevector] June 16, 2011

2. June 16, 2011 “Bioinformatics is the field of science in which biology, computer science, and information technology merge to form a single discipline.” National Center for Biotechnology Information (NCBI)

3. Areas where bioinformatics is applied Genomics Genomic feature prediction Sequencing data analysis Proteomics Protein 3D structure modeling Drug design Systems Biology Gene set enrichment Pathway analysis Phenotype Image analysis Integration June 16, 2011

4. Approach Biological Question Generate Data Translate into a computer solvable task Develop an algorithm Implement algorithm Run algorithm Condense result in human readable form Answer Biological Question Example Genes regulated by protein X ChIP-Seq data “Align reads and identify clusters in the genome” Choose data structures Write source code Align reads Write script to summarize results genome wide Report protein’s binding sites June 16, 2011 “Bioinformatics is the field of science in which biology, computer science, and information technology merge to form a single discipline.” NCBI

5. The challenges in bioinformatics Acceptance by biological collaborators when all that matters for the publication is the biology Retaining quality work Workflows poorly annotated in papers Programs poorly written No reproducibility Keeping up-to-date New programs are published every week New formats because no time to evaluate existing standards New databases because existing ones full of noise June 16, 2011

6. Bioinformatics a mythical creature? June 16, 2011 Christos Ouzounis Head of the Computational Genomics Group at the European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Cambridge UK

7. Myth #1: Anybody can do it! Assumption: Most bioinformatics analysis can be done by using web applications and commercial programs with GUIs June 16, 2011 http://www.broadinstitute.org/cancer/software/genepattern/index.html http://main.g2.bx.psu.edu/ Ouzounis C. Two or three myths about bioinformatics. Bioinformatics. 2000 Mar;16(3):187-9. PubMed PMID: 10869011.

9. Myth #2: Bioinformatics is a service Assumption: Bioinformatics merely supports the experimental research and can be a disconnect service June 16, 2011 Traditional Biology Hypothesis Experiment Eyeballing Experimental Design Evaluation Biology High Throughput Biology (assumption) Experiment Biology Hypothesis Experimental Design Evaluation Data analysis Bioinformatics

11. Myth #4: Bioinformatics is quick Assumption: bioinformatics analysis can be done quickly because computers are involved. June 16, 2011 http://www.ads-links.com/images/wp/keyboard-fast.gif

12. Bioinformatics analysis is a scientific experiment in itself Bioinformatics is faster than manual work, however Quick tasks accumulated take a long time Task: Map 15 million reads of 76 bp length against the complete human genome (hg18) Manual: couple of decades Brute-Force: couple of years BLAST (1995): couple of days Modern Aligners: BWA ~ 4 h Bioinformatics is a proper scientific experiment in itself requires time for experimental design, development of controls, parameter tuning, evaluation, and summarizing. June 16, 2011 ! Bao S, Jiang R, Kwan W, Wang B, Ma X, Song YQ. Evaluation of next-generation sequencing software in mapping and assembly. J Hum Genet. 2011 Apr 28. PubMed PMID: 21525877.

13. Myth #5: All dry-lab research does the same Assumption: bioinformatics is interchangeable with other dry lab research area because they all “analyze data”. Assumption: All biological research areas are interchangeable because they all “work with samples”. June 16, 2011

14. Three things to remember Bioinformatics requires dedication and continuity Bioinformatics data analysis is a full research experiment in itself We get the most out of our research if we work as a interdisciplinary research team throughout June 16, 2011 Experiment Analysis Evaluation Experimental Design Hypothesis

15. Next week: June 16, 2011 Abstract: An introduction to second generation sequencing will be given with focus on the production informatics: The basic approach of read-mapping and feature extraction will be introduced and challenges associated with sequencing errors discussed. http://web.qbi.uq.edu.au/labs/gseq/analysis/bioinformatics-seminar-series/

16. TIP Puts several images in one file convert -adjoin unicorn.pngunicorn.pngunicorn.pngadjoin.pdf Joins several images into one image convert –append unicorn.pngunicorn.pngunicorn.pngappend.pdf June 16, 2011