1 CAP5510 – Bioinformatics Fall 2009 Tamer Kahveci CISE Department University of Florida

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CAP5510 – BioinformaticsFall 2009

Tamer Kahveci

CISE Department

University of Florida

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Vital Information

• Instructor: Tamer Kahveci

• Office: E436

• Time: Mon/Wed/Thu 3:00 - 3:50 PM

• Office hours: Mon/Wed 2:00-2:50 PM

• TA: TBA

• Course page: – http://www.cise.ufl.edu/~tamer/teaching/fall2009

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Goals

• Understand the major components of bioinformatics data and how computer technology is used to understand this data better.

• Learn main potential research problems in bioinformatics and gain background information.

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This Course will

• Give you a feeling for main issues in molecular biological computing: sequence, structure and function.

• Give you exposure to classic biological problems, as represented computationally.

• Encourage you to explore research problems and make contribution.

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This Course will not

• Teach you biology.

• Teach you programming

• Teach you how to be an expert user of off-the-shelf molecular biology computer packages.

• Force you to make a novel contribution to bioinformatics.

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Course Outline

• Introduction to terminology• Biological sequences • Sequence comparison

– Lossless alignment (DP)– Lossy alignments (BLAST, etc)

• Substitution matrices, statistics • Multiple alignment • Phylogeny • Protein structures and function (primary, secondary, etc.) • Structure alignment • Structure prediction ?• Pathways

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Grading

• Homeworks (35 %) • Project (50 %)

– Contribution (2.5 % bonus)

• Survey (15 %)

How can I get an A ?

Bioinformatics DailyFirst homework is posted

First homework is posted

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Expectations

• Require– Data structures and algorithms.– Coding (C, Java)

• Encourage – actively participate in discussions in the classroom– read bioinformatics literature in general– attend colloquiums on campus

• Academic honesty

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Text Book

• Not required, but recommended.• Class notes + papers.

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Where to Look ?

• Journals– Bioinformatics– Genome Research– Nucleic Acid Research– Journal of Computational Biology– Protein Science

• Conferences– RECOMB– ISMB– PSB– CSB– VLDB, ICDE, SIGMOD

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What is Bioinformatics?• Bioinformatics is the field of science in which biology, computer

science, and information technology merge into a single discipline. The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned. There are three important sub-disciplines within bioinformatics:– the development of new algorithms and statistics with which to assess

relationships among members of large data sets – the analysis and interpretation of various types of data including

nucleotide and amino acid sequences, protein domains, and protein structures

– the development and implementation of tools that enable efficient access and management of different types of information.

From NCBI (National Center for Biotechnology Information)http://www.ncbi.nlm.nih.gov/Education/BLASTinfo/milestones.html

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Does biology have anything to do with computer science?

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Challenges 1/6

• Data diversity– DNA

(ATCCAGAGCAG)– Protein sequences

(MHPKVDALLSR)– Protein structures– Microarrays– Pathways– Bio-images– Time series

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Challenges 2/6

• Database diversity– GenBank, SwissProt, …– PDB, Prosite, …– KEGG, EcoCyc, MetaCyc, …

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Challenges 3/6• Database size

– GeneBank : As of August 2009, there are over 85,759,586,764 bases.

– 400 K protein sequences, each about 300 long

– 50K protein structures in PDB. 400K in Modbase.

Genome sequence now accumulate so quickly that, in less than a week, a single laboratory can produce more bits of data than

Shakespeare managed in a lifetime, although the latter make better reading.

-- G A Pekso, Nature 401: 115-116 (1999)

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• Moore’s Law Matched by Growth of Data• CPU vs Disk

– As important as the increase in computer speed has been, the ability to store large amounts of information on computers is even more crucial

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Protein DomainStructures

Challenges 4/6

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Challenges 5/6

• Deciphering the code– Within same data type: hard– Across data types: harder

caacaagccaaaactcgtacaaatatgaccgcacttcgctataaagaacacggcttgtggcgagatatctcttggaaaaactttcaagagcaactcaatcaactttctcgagcattgcttgctcacaatattgacgtacaagataaaatcgccatttttgcccataatatggaacgttgggttgttcatgaaactttcggtatcaaagatggtttaatgaccactgttcacgcaacgactacaatcgttgacattgcgaccttacaaattcgagcaatcacagtgcctatttacgcaaccaatacagcccagcaagcagaatttatcctaaatcacgccgatgtaaaaattctcttcgtcggcgatcaagagcaatacgatcaaacattggaaattgctcatcattgtccaaaattacaaaaaattgtagcaatgaaatccaccattcaattacaacaagatcctctttcttgcacttgg

atggcaattaaaattggtatcaatggttttggtcgtatcggccgtatcgtattccgtgcagcacaacaccgtgatgacattgaagttgtaggtattaacgacttaatcgacgttgaatacatggcttatatgttgaaatatgattcaactcacggtcgtttcgacggcactgttgaagtgaaagatggtaacttagtggttaatggtaaaactatccgtgtaactgcagaacgtgatccagcaaacttaaactggggtgcaatcggtgttgatatcgctgttgaagcgactggtttattcttaactgatgaaactgctcgtaaacatatcactgcaggcgcaaaaaaagttgtattaactggcccatctaaagatgcaacccctatgttcgttcgtggtgtaaacttcaacgcatacgcaggtcaagatatcgtttctaacgcatcttgtacaacaaactgtttagctcctttagcacgtgttgttcatgaaactttcggtatcaaagatggtttaatgaccactgttcacgcaacgact

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Challenges 6/6

• Inaccuracy

• Redundancy

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What is the Real Solution?

We need better computational methods

•Compact summarization•Fast and accurate analysis of data•Efficient indexing

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A Gentle Introduction to Molecular Biology

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Goals

• Understand major components of biological data– DNA, protein sequences, expression arrays,

protein structures

• Get familiar to basic terminology

• Learn commonly used data formats

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Genetic Material: DNA

• Deoxyribonucleic Acid, 1950s– Basis of inheritance– Eye color, hair color,

…

• 4 nucleotides – A, C, G, T

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Chemical Structure of Nucleotides

Purines

Pyrmidines

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Making of Long Chains

5’ -> 3’

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DNA structure

• Double stranded, helix (Watson & Crick)

• Complementary– A-T– G-C

• Antiparallel– 3’ -> 5’ (downstream)– 5’ -> 3’ (upstream)

• Animation (ch3.1)

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Base Pairs

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Question

• 5’ - GTTACA – 3’

• 5’ – XXXXXX – 3’ ?

• 5’ – TGTAAC – 3’

• Reverse complements.

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Repetitive DNA

• Tandem repeats: highly repetitive – Satellites (100 k – 1 Gbp) / (a few hundred bp)– Mini satellites (1 k – 20 kbp) / (9 – 80 bp)– Micro satellites (< 150 bp) / (1 – 6 bp)– DNA fingerprinting

• Interspersed repeats: moderately repetitive– LINE– SINE

• Proteins contain repetitive patterns too

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Genetic Material: an Analogy

• Nucleotide => letter• Gene => sentence• Contig => chapter• Chromosome => book

– Gender, hair/eye color, …– Disorders: down syndrome, turner syndrome, …

• http://gslc.genetics.utah.edu/units/disorders/karyotype/– Chromosome number varies for species

• http://www.web-books.com/MoBio/Free/Ch1C2.htm– We have 46 (23 + 23) chromosomes

• http://www.web-books.com/MoBio/Free/Ch1C5.htm

• Complete genome => volumes of encyclopedia• Hershey & Chase experiment show that DNA is the

genetic material. (ch14)

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Functions of Genes 1/2

• Signal transduction: sensing a physical signal and turning into a chemical signal

• Structural support: creating the shape and pliability of a cell or set of cells

• Enzymatic catalysis: accelerating chemical transformations otherwise too slow.

• Transport: getting things into and out of separated compartments– Animation (ch 5.2)

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Functions of Genes 2/2

• Movement: contracting in order to pull things together or push things apart.

• Transcription control: deciding when other genes should be turned ON/OFF– Animation (ch7)

• Trafficking: affecting where different elements end up inside the cell

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Central Dogma

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Introns and Exons 1/2

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Introns and Exons 2/2

• Humans have about 35,000 genes = 40,000,000 DNA bases = 3% of total DNA in genome.

• Remaining 2,960,000,000 bases for control information. (e.g. when, where, how long, etc...)

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Central dogma

ProteinPhenotype

DNA(Genotype)

Gene expression

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Gene Expression

• Building proteins from DNA– Promoter sequence: start of a gene 13 nucleotides.

• Positive regulation: proteins that bind to DNA near promoter sequences increases transcription.

• Negative regulation

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Microarray

Animation on creating microarrays

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Amino Acids

• 20 different amino acids– ACDEFGHIKLMNPQRSTVWY but not BJOUXZ

• ~300 amino acids in an average protein, ~400 K known protein sequences

• How many nucleotides can encode one amino acid ?– 42 < 20 < 43

– E.g., Q (glutamine) = CAG– degeneracy– Triplet code (codon)

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Triplet Code

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Molecular Structure of Amino Acid

Side Chain

•Non-polar, Hydrophobic (G, A, V, L, I, M, F, W, P)•Polar, Hydrophilic (S, T, C, Y, N, Q)•Electrically charged (D, E, K, R, H)

C

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Peptide Bonds

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Direction of Protein Sequence

Animation on protein synthesis (ch15)

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Data Format

• GenBank

• EMBL (European Mol. Biol. Lab.)

• SwissProt

• FASTA

• NBRF (Nat. Biomedical Res. Foundation)

• Others– IG, GCG, Codata, ASN, GDE, Plain ASCII

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Primary Structure of Proteins

phi1

psi1

phi2

2N angles

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Secondary Structure: Alpha Helix

• 1.5 A translation• 100 degree rotation• Phi = -60• Psi = -60

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anti-parallel parallel

Secondary Structure: Beta sheet

Phi = -135Psi = 135

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Ramachandran Plot

Sample pdb entry ( http://www.rcsb.org/pdb/ )

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• 3-d structure of a polypeptide sequence– interactions between non-local atoms

tertiary structure ofmyoglobin

Tertiary Structure

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• Arrangement of protein subunits

quaternary structure of Cro

human hemoglobin tetramer

Quaternary Structure

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• 3-d structure determined by protein sequence

• Prediction remains a challenge

• Diseases caused by misfolded proteins– Mad cow disease

• Classification of protein structure

Structure Summary

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STOP

Next Week:•Basic sequence comparison•Dynamic programming methods

–Global/local alignment–Gaps