Bioinformatics (Globex, Summer 2015) Lecture 1
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1 Bioinformatics (Globex, Summer 2015) Lecture 1 Course Overview Li Liao Computer and Information Sciences University of Delaware
2 Dela-where? 2
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5 Administrative stuff Syllabus and tentative schedule Workload 4 homework assignments (40%) Mid-term exam (20%) Final exam (40%) Late policy: Only one day delay is allowed; subject to 15% penalty.
6 Bioinformatics Books Markketa Zvelebil and Jeremy Baum, Understanding Bioinformatics, Garland Science, Dan E. Krane & Michael L. Raymer, Fundamental Concepts of Bioinformatics, Benjamin Cummings 2002 R. Durbin, S. Eddy, A. Krogh, and G. Mitchison. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press, João Meidanis & João Carlos Setubal. Introduction to Computational Molecular Biology. PWS Publishing Company, Boston, Peter Clote and Rolf Backofen, Computational Molecular Biology: An Introduction, Willey Dan Gusfield. Algorithms on String, Trees, and Sequences. Cambridge University Press, P. Baldi and S. Brunak, Bioinformatics, The Machine Learning Approach, The MIT press, D.W. Mount, Bioinformaics: Sequence and Genome Analysis, CSHLP 2004.
7 Molecular Biology Books Free materials: Kimball's biology Lawrence Hunter: Molecular biology for computer scientists DOE s Molecular Genetics Primer Books: Instant Notes series: Biochemistry, Molecular Biology, and Genetics Molecular Biology of The Cell, by Alberts et al
8 Bioinformatics - use and develop computing methods to solve biological problems The field is characterized by an explosion of data Big data!!! difficulty in interpreting the data a large number of open problems until recently, relative lack of sophistication of computational techniques (compared with, say, signal processing, graphics, etc.)
9 Why is this course good for you? Expand your knowledge base Bioinformatics is a computational wing of biotechnology. Computational techniques in bioinformatics are widely useful elsewhere - Cybergenomics: detect, dissect malware Big data!!! Job market is strong
10 Industry is moving in IBM: BlueGene, the fastest computer with 1 million CPU Blueprint worldwide collects all the protein information Bioinformatics segment will be $40 billion in 2004 up from $22 billion in 2000 GlaxoSmithKline Celera Merck AstraZeneca
11 Computing and IT skills Algorithm design and model building Working with unix system/web server Programming (in PERL, Java, etc.) RDBMS: SQL, Oracle PL/SQL
12 People International Society for Computational Biology ( ~ 3400 members (as of 2015) Severe shortage for qualified bioinformatians / bioinformaticists
13 Conferences ISMB (Intelligent Systems for Molecular Biology) started in 1992 RECOMB (International Conference on Computational Molecular Biology) started in 1997 PSB (Pacific Symposium on Biocomputing) started 1996 ACM-BCB BIBM...
14 Journals Bioinformatics BMC Bioinformatics PLOS Computational Biology Journal of Computational Biology Genome Biology Genomics Genome Research Nucleic Acids Research...
15 A short history after human genome:
16 Human Genome at Ten:
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18 Human Genome at Ten:
19 Human Genome at Ten:
20 Human Genome at Ten:
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26 It is much easier to teach people with those skills about biology than to teach biologists how to code well.
27 Tree of Life
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29 Organisms: three kingdoms -- eukaryotes, eubacteria, and archea Cell: the basic unit of life Chromosome (DNA) > circular, also called plasmid when small (for bacteria) > linear (for eukaryotes) Genes: segments on DNA that contain the instructions for organism's structure and function Proteins: the workhorse for the cell. > establishment and maintenance of structure > transport. e.g., hemoglobin, and integral transmembrane proteins > protection and defense. e.g., immunoglobin G > Control and regulation. e.g., receptors, and DNA binding proteins > Catalysis. e.g., enzymes
30 Bioinformatics in a cell
31 Central Dogma of Molecular Biology Genetic Information Flow:
32 Cellular processes are programmed, regulated, and yet are stochastic
33 Small molecules: > sugar: carbohydrate > fatty acids > nucleotides: A, C, G, T --> DNA (double helix, hydrogen bond, complementary bases A-T, G-C) four bases: adenine, cytosine, guanine, and thymidine (uracil) 5' end phosphate group 3' end is free 1' position is attached with the base double strand DNA sequences form a helix via hydrogen bonds between complementary bases hydrogen bond: - weak: about 3~5 kj/mol (A covalent C-C bond has 380 kj/mol), will break when heated - saturation: - specific:
34 Hack the life atcgggctatcgatagctatagcgcgatatatcgcgcgtatatgcgcgcatattag tagctagtgctgattcatctggactgtcgtaatatatacgcgcccggctatcgcgct atgcgcgatatcgcgcggcgctatataaatattaaaaaataaaatatatatatatgc tgcgcgatagcgctataggcgcgctatccatatataggcgctcgcccgggcgcga tgcatcggctacggctagctgtagctagtcggcgattagcggcttatatgcggcga gcgatgagagtcgcggctataggcttaggctatagcgctagtatatagcggctagc cgcgtagacgcgatagcgtagctagcggcgcgcgtatatagcgcttaagagcca aaatgcgtctagcgctataatatgcgctatagctatatgcggctattatatagcgca gcgctagctagcgtatcaggcgaggagatcgatgctactgatcgatgctagagca gcgtcatgctagtagtgccatatatatgctgagcgcgcgtagctcgatattacgcta cctagatgctagcgagctatgatcgtagca.
35 Genetic Code: codons
36 Information Expression 1-D information array 3-D biochemical structure
37 Challenges in Life Sciences Understanding correlation between genotype and phenotype Predicting genotype <=> phenotype Phenotypes: drug/therapy response drug-drug interactions for expression drug mechanism interacting pathways of metabolism
38 Profiling 14 Structure Prediction Credit:Kellis & Indyk
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41 Topics Mapping and assembly Sequence analysis (Similarity -> Homology): Pairwise alignment (database searching) Multiple sequence alignment, profiling Gene prediction Pattern (Motif) discovery and recognition Phylogenetics analysis Character based Distance based Structure prediction RNA Secondary Protein Secondary & tertiary Network analysis: Gene expression Regulatory networks
42 How much should I know about biology? - Apparently, the more the better - The least, Pavzner's 3-page "All you need to know about Molecular biology". - Chapters 1 & 2 of the text. - We adopt an "object-oriented" scheme, namely, we will transform biological problems into abstract computing problems and hide unnecessary details. So another big goal of this course is learn how to do abstraction.
43 Goals? At the end of this course, you should be able to - Describe the main computational challenges in molecular biology. - Implement and use basic algorithms. - Describe several advanced algorithms. Sequence alignment using dynamics programming Hidden Markov models Hierarchical clustering K-means Gradient descent optimization - Know the existing resources: Databases, Software,
CISC 436/636 Computational Biology &Bioinformatics (Fall 2016) Lecture 1
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2 strands, has the 5-carbon sugar deoxyribose, and has the nitrogen base Thymine. The actual process of assembling the proteins on the ribosome is called? DNA translation Adenine pairs with Thymine, Thymine
90 Algorithms in Bioinformatics I, WS 06, ZBIT, D. Huson, December 4, 2006
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