JM Introduction to Bioinformatics: Lecture I An Overview of the Course Jarek Meller Jarek Meller Division of Biomedical Informatics, Children’s Hospital Research Foundation & Department of Biomedical Engineering, UC

JM - Outline of the outline lecture Bioinformatics as hypothesis generator for biomedical research in the postgenomic era Bioinformatics at the University of Cincinnati & Children’s Hospital Research Foundation: research and resources Introduction to Bioinformatics course: problems and case studies, web and Protein Modeling Lab resources, syllabus and some practical issues

JM - Bioinformatics as hypotheses generator Making sense of massive amounts of genomic, proteomic etc. information in order to facilitate further experiments by data mining and inference, modeling and computer simulations.

JM - Some more “precise” definitions “Roughly, bioinformatics describes any use of computers to handle biological information” “In practice the definition used by most people is narrower; bioinformatics to them is a synonym for "computational molecular biology“ -- the use of computers to characterize the molecular components of living things.” “The mathematical, statistical and computing methods that aim to solve biological problems using DNA and amino acid sequences and related information.” More:

JM - Other “definitions” Subject or body of research – e.g. google bioinformatics and simply digest the 2 ML (1 ML= 10 6 Links) or so … Methods and approaches: computational paradigm in molecular biology and biomedical research Institutional boundaries – take a body of research from all the scientific institutions having “bioinformatics” in their name Let us have look at local bioinformatics resources

JM Bioinformatics at the UC and CHRF: Research and Resources

JM - Pneumocystis Genome Project Sequencing the genome of a fungal pathogen causing Pneumocystis pneumonia: towards novel drug targets and therapies. Melanie Cushion (VA/UC) George Smulian (VA/UC) JM UC/CHRF sequencing core:

JM - Microarray-based gene expression studies Numerous studies on genome-wide expression profiles to identify interesting targets and elucidate protein pathways. Bruce Aronow (CHRF) Mario Medvedovic (UC/CHRF) Yizong Cheng (UC) CHRF Affymetrix GeneChip core UC Genomics and Microarray Lab

JM - Clustering algorithms for expression profiles Medvedovic M and Sivaganesan S; Bayesian infinite mixture model based clustering of gene expression profiles, Bioinformatics 2002 Medvedovic M, Yeung KY, Bumgarner RE; Bayesian mixture model based clustering of replicated microarray data, to appear in Bioinformatics 2004 GIMM (Gaussian Infinite Mixture Models) Software (M. Medvedovic)

JM - Computational studies of transcription regulation Jegga AG, Sherwood SP, Carman JW, Pinski AT, Phillips JL, Pestian JP, Aronow BJ; Detection and visualization of compositionally similar cis-regulatory element clusters in orthologous and coordinately controlled genes, Genome Research 2002 Detection of Transcription Factors binding sites  TRAFAC server

JM - Proteomics Studying protein expression, structure, interactions, pathways etc. Rashmi Hedge (CHRF) Mark Rance (UC) Patt Limbach (UC) Bruce Aronow (CHRF) Michael Wagner (CHRF) JM

JM - Protein expression profiling Wagner M, Naik D, Pothen A; Protocols for disease classification from mass spectrometry data, Proteomics 9 (2003) Wagner M, Naik D, Pothen A, Kasukurti S, Devineni R, Adam B, Semmes O and Wright Jr G; Computational Protein Biomarker Prediction: A Case Study for Prostate Cancer, to appear in BMC Bioinformatics (2004) Searching for disease fingerprints in mass spec profiles 

JM - Structural and functional annotations for proteins R. Adamczak, A. Porollo and J. Meller; Accurate Prediction of Solvent Accessibility Using Neural Networks Based Regression, Proteins: Structure, Function and Bioinformatics, to appear (2004) A. Porollo, R. Adamczak and J. Meller; Polyview: A Flexible Visualization Tool for Structural and Functional Annotations of Proteins, Bioinformatics, to appear (2004) SABLE server POLYVIEW server

JM - Machine learning and pattern recognition JM Michael Wagner Rafal Adamczak Mario Medvedovic Fishing for patterns and fingerprints that correlate with phenotypes and biological processes

JM - Genomic fingerprints of disease states

JM - Perspectives and future directions Integration of individual projects and systems biology approach Predictive medicine using multi-dimensional fingerprints of disease states, risks and optimal treatments Infrastructure challenges: the Center for Computational Medicine as a regional hub for biomedical research

JM - Summary of current resources UC Center for Genomics and Bioinformatics UC NMR Core UC/CHRF Proteomics Core UC and CHRF sequencing cores UC and CHRF microarrays cores CHRF computational infrastructure

JM - Web resources and materials for the course  Protein Modeling Lab  Remote access to PML and the Citrix software  All lectures and other materials available electronically from the PML servers  Electronic tests and homework, web submission interfaces  The web site for the Introduction to Bioinformatics course  Updates