1_introduction to bioinformatics

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341: Introduction to Bioinformatics

Dr. Nataa Prulj & Prof. Yike Guo

Department of Computing

Imperial College London

[email protected]

Winter 2011

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Course overview

Explosion in the availability of biological data: Sequences and microarrays (Prof. Guo)

Networks: expected to be as useful as the sequence data inuncovering new biology (Dr. Prulj)

The goal of systems biology: Systems-level understanding of biological systems, e.g. the cell

Analyze not only individual components, but their interactions aswell and its functioning as a whole

E.g.: Learn new biology from the topology of such interaction

networks However, biological network research faces considerable

challenges Incomplete and noisy data

Computational infeasibility of many graph theoretic problems2


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Course overviewWe will cover:

1. Biological aspects: Basic biological concepts (e.g., DNA, genes, proteins, gene expression, ) Different types of biological networks Experimental techniques for acquiring the data and their biases Public databases and other sources of biological network data

2. Sequence analysis (Prof. Yi-Ke Guo)3. Microarray analysis (Prof. Yi-Ke Guo)4. Graph theoretic aspects:

Fundamental topics in graph theory (e.g. basic graph notation, graph representation, andspecial graph types)

Basic graph algorithms (e.g., graph search/traversal algorithms and running time analysis) Important computational complexity concepts (e.g., complexity classes, subgraph

isomorphism, and NP-completeness) which pose challenges on analyzing biological nets

5. Existing approaches for analyzing and modeling biological networks: Structural properties of large networks

Network models Network clustering Graph alignment Software tools for network analysis

6. Applications: interplay of topology and biology Learn how the above methods have been applied Discuss valuable insights that have been learned: into biological function, evolution,

complex diseases (e.g., cancer) and drug discovery3


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Course overview

Grading scheme: Two homework assignments

Each assignment worth equally

Due at the beginning of the class

Written exam

Standard College Grading Scheme will be used

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Course overview

Course organization:1. Lectures

Relevant theoretical concepts and examples

2. Tutorials Exercises covering concepts covered in class

3. Two homework assignments

Opportunity to solve practical problems using the methods learned in class

4. Written exam Testing students understanding of the concepts learned in lectures

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Course overview

Textbooks and readings Recommended textbooks:

Junker and Schreiber, Analysis of Biological Networks, Wiley, 2008. West, Introduction to graph theory, 2nd edition, Prentice Hall, 2001or T. Cormen et al., Analysis of Algorithms, 3rd eddition, MIT press, 2009. A list of up-to-date research papers selected by the instructor.

Recommended readings: F. Kepes (Author, Editor), Biological Networks (Complex Systems and

Interdisciplinary Science), World Scientific Publishing Company; 1stedition, 2007.

Bornholdt and Schuster (Editors), Handbook of Graphs and Networks:From the Genome to the Internet, Wiley, 2003.or

Dorogovtsev and Mendes (Authors), Evolution of Networks: FromBiological Nets to the Internet and WWW (Physics), Oxford UniversityPress, 2003.

Chapter 17 from: Chen and Lonardi (Editors), Biological Data Mining,Chapman and Hall/CRC press, 2009.

Chapter 4 from: Jurisica and Wigle (Editors), Knowledge Discovery inProteomics, CRC Press, 2005.

LEDA: A Platform for Combinatorial and Geometric Computing, by Kurt

Mehlhorn, Stefan Nher, Cambridge University Press, 1999. 6


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Course overview

When and where:

Fridays, 2 5 pm (2 hours of lecture, 1 hour tutorail)

145 Huxley

Contact:

E-mail: [email protected]

Subject: 341 Bioinformatics

Office hours:

Fridays after class, 5 pm

Office: 407 A Huxley

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Course overview

Prerequisites: none

Basic programming skills are desirable

Introduction into biological concepts will be provided

Course website (curriculum, class material, etc.):

http://www.doc.ic.ac.uk/~natasha/course/index.html

Academic code of honor

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Topics Introduction: biology (Dr. Przulj)

Sequence analysis (Prof. Guo, 2 lectures)Microarray analysis (Prof. Guo, 3 lectures)

Network biology (Dr. Przulj):

Introduction to graph theory

Network properties

Network/node centralities

Network motifs

Network models

Network/node clustering

Network comparison/alignment

Software tools for network analysis

Interplay between topology and biology 9


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Course overview

Any questions so far?

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Course overview

About you

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Introduction: biology

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Cell- the building block of life

Cytoplasm and organelles separated by membranes:

Mitochondria, nucleus, etc.

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Distinguish between:

ProkaryotesSingle-celled, no cell nucleus or any other

membrane-bound organelles The genetic material in prokaryotes is not membrane-bound

The bacteriaand the archaea

Model organism: E.coli

EukaryotesHave "true" nuclei containing their DNA

May be unicellular, as in amoebae

May be multicellular, as in plants and animals

Model organism: S. cerevisiae (bakers yeast) 14


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Nucleus contains DNA

Deoxyribonucleic acid

DNA nucleotides: A and T, C and G

DNA structure: double helix

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Chromosomes

RNA:similar to DNA, except T U and single stranded

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Main role of DNA: long-term storage of genetic information

Genes: DNA segments that carry this information

Intron: part of gene not translated into protein, spliced out of mRNA

Exon: mRNA translated into protein consists only of exon-derivedsequences

Genome: total set of (unique) genes in an organism

Every cell (except sex cells and

mature red blood cells) contains

the complete genome of an organism

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Codons: sets of three nucleotides

4 nucleotides 43=64 possible codons

Each codon codes for an amino acid

64 codons produce 20different amino acidsMore than one codon stands for one amino acid

Polypeptide:

String of amino acids, composed from a 20-character alphabet

Proteins: String composed of one or more polypeptides (70-3000 amino acids)

Sequence of amino acids is defined by a gene

Gene expression: information transmission from DNA to proteins

Proteome: total set of proteins in an organism


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The 20 amino acids

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Levels of protein

structure:

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Genes vs. proteins

Genes passive; proteins active

Protein synthesis: from genes to proteins

Transcription(in nucleus)Splicing(eukaryotes)

Translation (in cytoplasm)

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Transcription(in nucleus)

RNA polymeraseenzyme builds an RNA strandfrom a gene (DNA is "unzipped)

The gene is transcribed to messenger RNA(mRNA)

Transcription is regulated by proteins called

transcription factors

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Translation(in cytoplasm)

Ribosomes synthesize proteins from mRNA

mRNA is decoded and used as a template to guide the

synthesis of a chain of amino acids that form a proteinTranslation: the process of converting the mRNA codon

sequences into an amino acid polypeptide chain

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Microarrays:

Measure mRNA abundance for each gene

The amount of transcribed mRNA correlates with

gene expressionThe rate at which a gene produces the corresponding protein

It is hard to measureprotein level directly!

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Every cell* contains the complete genome of an organism

How is the variety of different tissues encoded andexpressed?

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-ome and omics

Genome and genomics

Proteome and proteomics

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