CS369 Computational Biology

University of Auckland

Course coordinator: Alexei Drummond

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CS369 Computational Biology

• This course provides an overview of algorithms and scientific computing techniques in computational biology and bioinformatics.

• A hands-on introduction to topics including– Dynamic programming and string algorithms,– Markov models, Hidden Markov models, – Heuristic search algorithms, – Pairwise and multiple sequence alignment,– Phylogenetic Reconstruction– Gene finding and secondary structure prediction

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Your lecturers

Alexei Drummond

Coordinator

Michael Dinneen

Algorithmics

Patricia Riddle

Learning and pattern discovery

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Recommended Texts

• Bioinformatics: Sequence and Genome analysis, 1st & 2nd Editions– by David W Mount (2001; 2004)– 1st Edition is available as an E-book in the library– 2nd edition is available on short term loan

• Biological sequence analysis– by Durbin, Eddy, Krogh and Mitchinson (1998)– Available on short term loan

• Algorithm Design– by Kleinberg J. and Tardos E (2006)

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Assessment

• 2 x 2 hour labs (3rd April and 29th May)– 5% each

• 1 assignment (1st May handout)– 20%

• 1 Mid-semester test– 10%

• 1 Exam– 60%

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Lecture schedule - first half

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Lecture schedule - second half

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What is computational biology?

• Computers and biology?

• the organization and the analysis of biological data with computers?

• The new biology of the 21st century?

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What is bioinformatics?

• Rapidly growing biological databases contain information about– Cellular and molecular biology

– Ecology and Evolutionary biology

– Microbiology

– Genomics

– Proteomics

• The application of computational biology to understand this data.

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What is computational biology?

• Computational biology combines the tools and techniques of – mathematics,– statistics,

– computer science,– biology

• in order to understand the masses of biological data

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and the tree of lifeComputational biology

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The human 18S gene QuickTime™ and aTIFF (Uncompressed) decompressor

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The frog 18S gene QuickTime™ and aTIFF (Uncompressed) decompressor

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Pairwise alignment of human and frog

Humans and Frogs are 94% similar!

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Pairwise sequence alignment

Sequences

x = a c g g t sy = a w g c c t t

Alignment

x = a – c g g – t sy = a w – g c c t t

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Dynamic programming algorithm

• computation is carried out bottom-up • store solutions to subproblems in a table • all possible subproblems solved once each, beginning

with smallest subproblems • work up to original problem instance • only optimal solutions to subproblems are used to

compute solution to problem at next level • DO NOT carry out computation in recursive, top-down

manner – same subproblems would be solved many times

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Auckland

Te Kuiti

Wellington

Principle of Optimality

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Scoring

• Numeric score associated with each column• Total score = sum of column scores• Column types:

(1) Identical (+ve) (2) Conservative (+ve)

(3) Non-conservative (-ve) (4) Gap (-ve)

x = a – c g g – t sy = a w – g c c t t

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Comparing many species

This is called a “multiple sequence alignment”

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Tree of 3000 species

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Molecular tracking of the Southern Saltmarsh Mosquito

GTGAATGCCATTGCA

extract multiply

decode

alignbuild tree

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Bioinformatics and genome evolution

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Computational biology and disease

• Bacterial infection can causes serious illnesses, e.g.– Necrotising Fasciitis

(“Flesh eating disease”)– Toxic Shock Syndrome

(TSS)• (e.g. the illness Lana Cockroft

got from the cut in her foot during “Celebrity Treasure Island”).

T: Staphylococcus aureus

B: Streptococcus pyogenes,

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Computational biology and Disease

Necrotizing fasciitis

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Computational biology and Disease

Identify protein structure of superantigens - so that potential drug targets can be uncovered.

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Computational biology and sequencing technology

• “Old” Technology– 1977– Small Scale– Slow– Length: long ≈ 700bp

• New Technology: 454– 2003– Large scale: Whole genome– Fast– Length: short ≈ 100bp– http://www.454.com

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Africa

n Mam

mot

h Indian

Bring the mammoth back

Using this new sequencing technology and bioinformatics to compare the sequences to the African elephant genome, scientists sequenced 28 million nucleotides of the mammoth genome from frozen bones!

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Where does the DNA come from?

• Scientists Sequence DNA of Woolly Mammoth (extinct 10,000 years ago)– http://

www.science.psu.edu/alert/Schuster12-2005.htm QuickTime™ and a

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Conclusion

• Computational biology and bioinformatics are fast becoming central to the biological sciences– Ecology– Evolutionary biology (tree of life)– Health and disease (flesh-eating bacteria)– Molecular biology and cell biology– Personalized medicine

• Computational biology is heavily algorithmic and often statistical, drawing from the ‘hard-as-in-rock’ sciences like mathematics, computer science and statistics - this type of knowledge is becoming increasingly important in biology.

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Reading

• Chapter 1 “Biological Sequence Analysis”, Durbin et al

• Chapter 1 of Mount– Don’t worry about any biological terms that you

don’t immediately understand! This chapter is more to give you a sense of where we are going to go. The pertinent details will be explained along the way.

Biomolecules and the Central Dogma of Molecular Biology

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The central dogma of molecular biology

DNA RNA ProteinTranscription Translation

Replication

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What is a macromolecule?

• A chain molecule made up of a large number of repeating units.– Homo-polymers are made up of the same units– Hetero-polymers are made up of a number of different

units

• Nylon, Polyester, DNA (poly-nucleotide) and Protein (poly-amino acid) are examples

• Macromolecular 3D structure is a question conformational change rather than breaking and forming strong bonds.

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Biomolecular sequences

5’-ACGATCGACTGGTATATCGATGCT-3’

5’-ACGAUCGACUGGUAUAUCGAUGCU-3’

DNA

RNA

Protein

€

X i ∈ {A,C,G,T}

€

X i ∈ {A,C,G,U}

MFINRWLFSTNHKDIGTLYLLFGAW

€

X i ∈ {A,R,N,D,C,E,Q,G,H,I,L,K,M,F,P,S,T,W ,Y,V}

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DNA5’-ACGATCGACTGGTATATCGATGCT-3’3’-TGCTAGCTGACCATATAGCTACGA-5’

In nature DNA exists in a double helix of two complementary sequences.

A - T

G - C

Watson-CrickBase pairing

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RNA5’-ACGAUCGACUGGUAUAUCGAUGCU-3’RNA

A - U

G - C

G - U

3 H bonds

2 H bonds

1 H bonds

3D structure Secondary structure

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Proteins

• Proteins are hetero-polymers made up of 20 standard amino acids and are “coded for” by genes.

• They form 3D molecular structures that do work in the cell.

• An open problem is to determine structure computationally from the primary sequence of amino acids.

A cartoon of the 3D structure of the myoglobin protein

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The genetic codeAmino acids

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The genetic code

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