9/30/2004TCSS588A Isabelle Bichindaritz1 Introduction to Bioinformatics

9/30/2004TCSS588A Isabelle Bichindaritz2 Introduction to Class Syllabus Schedule Web-site Assignments: –An application to genetics –An application to proteomics –… Project – project teams (proposal due next week)

9/30/2004TCSS588A Isabelle Bichindaritz3 Introduction to Class 1. Biological foundations. 2. Machine learning algorithms and applications to biology/life sciences. 3. Neural networks. 4. Hidden Markov Models. 5. Graphical models. 6. Case Based Reasoning. 7. Phylogenetic trees induction. 8. Microarrays and gene expression. 9. Image understanding and mining. 10. Biometrics.

9/30/2004TCSS588A Isabelle Bichindaritz4 Introduction to Class

9/30/2004TCSS588A Isabelle Bichindaritz5 Course Learning Objectives Understand biological concepts and set of problems. oUnderstand scientific framework for bioinformatics in statistics, complexity, and information theory. oUnderstand machine learning methods for bioinformatics. oUnderstand innovative algorithms and methods for bioinformatics. oProgram using available bioinformatics tools. oLearn familiarity with statistical learning, concept learning, hidden Markov models, case based reasoning, neural networks, knowledge-based systems and ontologies, genetic algorithms, stochastic grammars and linguistics, grid computing, and semantic Web. oDesign and develop new computer systems for bioinformatics.

9/30/2004TCSS588A Isabelle Bichindaritz6Outline Informatics / Medical Informatics / Bioinformatics / Computational Biology Project examples –Care Partner –Telemakus –Phylsyst –Human Genome Project Introduction to biology

9/30/2004TCSS588A Isabelle Bichindaritz7 Informatics / Medical Informatics Informatics is “The science of rational and computerized processing of information as it supports human knowledge and communication in scientific, technical, economical, and social domains.”. Often associated with health care and medical research applications  medical informatics Interdisciplinary field involving medicine, biology, computer science, mathematics, information science, and statistics.

9/30/2004TCSS588A Isabelle Bichindaritz8 Medical Informatics Computer Applications in Health Care

9/30/2004TCSS588A Isabelle Bichindaritz9 Bioinformatics Bioinformatics is the discipline that develops technologies for supporting information management in fields like biology. Target domains: biology, medicine, pharmacology, agriculture … Interdisciplinary field. Main tasks: analyze biological sequence data, genome content, and arrangement, predict the function and structure of macromolecules.

9/30/2004TCSS588A Isabelle Bichindaritz10 Computational Biology Computational biology provides algorithms for bioinformatics. Target applications: –Genomics DNA  genes –Proteomicsproteins –Phylogenetics evolutionary classifications

9/30/2004TCSS588A Isabelle Bichindaritz11 Care Partner System Description A decision support system for stem cell post transplant care: –comprehensive knowledge-base (scientific literature, monographs, clinical guidelines, clinical pathways, clinical cases) –available on the WWW –learns from experience

9/30/2004TCSS588A Isabelle Bichindaritz12 Knowledge-Base

9/30/2004TCSS588A Isabelle Bichindaritz13 Knowledge-Base

9/30/2004TCSS588A Isabelle Bichindaritz14

9/30/2004TCSS588A Isabelle Bichindaritz15 Telemakus Goal of the Telemakus System: –to enhance the knowledge discovery process by developing retrieval, visual and interaction tools to mine and map research findings from the research literature. Objective of the research: –to create, test and validate an infrastructure to permit the automation of the creation and maintenance of a searchable database that generates knowledge maps via query tools and concept mapping algorithms. –to apply natural language processing models and information analysis methods to ultimately speed up the scientific discovery process.

9/30/2004TCSS588A Isabelle Bichindaritz16 Telemakus

9/30/2004TCSS588A Isabelle Bichindaritz17 Phylsyst

9/30/2004TCSS588A Isabelle Bichindaritz18 Phylsyst Example – Phylsyst built cladogram

9/30/2004TCSS588A Isabelle Bichindaritz19 Human Genome Project Goal of the Human Genome Project: –identify all the approximate 30,000 genes in human DNA, –determine the sequences of the 3 billion chemical base pairs that make up human DNA, –store this information in databases, –improve tools for data analysis, –transfer related technologies to the private sector, and –address the ethical, legal, and social issues (ELSI) that may arise from the project. Completed in 2003

9/30/2004TCSS588A Isabelle Bichindaritz20 Human Genome Program, U.S. Department of Energy, Genomics and Its Impact on Medicine and Society: A 2001 Primer, 2001

9/30/2004TCSS588A Isabelle Bichindaritz21 The Human Genome Project

9/30/2004TCSS588A Isabelle Bichindaritz22 The Visible Human Project Image understanding – the Visible Human Project