1. Integrating the Bioinformatic Technology Group into your research programme Introduction People and Skills Examples Integrating the BTG Contacts BHRC Away day, Jan 2011

2. Introduction Group of quantitative researchers We are biologists that use a different set of tools Collaborate with you to answer biological questions Enable you to cross technical boundaries Enable you to ask data intensive questions

3. People and Skills Lee Hazelwood (Group Leader) David Westhead (Director) Binbin Liu Andy Bulpitt (Dep- Director) Michael Bentley Biology: TF binding sites, sequence alignment, RT-PCR, microarray analysis, CHip-Seq, RNA-seq, pathways, enzyme kinetics, electrophysiology, protein conformation, metabolic and development pathways, drug target discovery, multi- scale and tissue modelling … Computational: High throughput, machine learning, hidden markov models, power calculations, data mining, image analysis, molecular dynamics, simulations, Physical processes: Cell signalling and organisation, reaction kinetics, binding, structural biology, statistical physics of soft matter

4. Examples: Standard problem Bioinformatics Black box List HT Experiment Data Method Genome sequence analysis Gene expression analysis using sequencing and array methods ChIP on chip and ChIP-seq Copy number analysis Gene network analysis Point mutations and SNPs Comparative genome studies Protein structure prediction Analysis of protein microarrays High throughput mass spectrometry data Protein-Protein docking Protein Interaction Simulation of cellular subsystems to analyze pathways and regulatory/signalling networks Not usually straightforward! Multiple methods and parameters Need to understand the biology and the question

5. Bioinformatics Black box List Cell phenotype Data P values (very small) Path1 Great! Wait! Question: Can we identify related genes using known pathways and siRNA cell phenotype screens?

6. How did you identify the phenotype? Bioinformatics Black box List P values Path1a Protocol Analysis Other Technology Groups Cell phenotype P values (not so small) Cell area Not so small Important to know how the error is carried through

7. Question: Identify TF binding sites and genes using Chip-Seq data Bioinformatics Black box Peak Overlaps List of related TFs or genes CHip-Seq Data

8. You are really interested in cell fate! List Decision tree Multi-faceted problem Pheno Novel area of research

9. BTG involvement depends on your question? To maximise our potential contribution you need to think outside the black box!

10. How to integrate us into your research? Aim: Build long term successful research collaborations Talk science Meet to discuss possible projects Invite us to your group meetings Take forward Write joint grants Carry out pilot projects BHRC pump prime funding  Develop a project proposal with help from BTG

11. Contacting the group Based at FBS (Garstang, Level 10) and LIMM (Brenner, Level 7). Email Lee David Hazelwood L.D.Hazelwood@leeds.ac.uk Take a look at the website www.bhrc.ac.uk (click on technology groups) Questions?