Bioinformatics Methods and Applications

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BioinformaticsMethods and Applications

• Dr. Hongyu Zhang
• Ceres Inc.

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Goals of the talk

• The major battle fields in Bioinformatics
  research
• The most popular weapons used in the battle

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History

• Human genome project
• Overlapping with other branches
• Computational Biology
• Biocomputing
• Biostatistics
• Cheminfomatics

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The Central Dogma ofMolecular Biology
Transcription
Translation
DNA
RNA
Protein
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Major battle fields in bioinformatics

• DNA
• Genome sequencing
• Gene discovery
• mRNA
• Micro-array analysis
• Sequencing
• Protein
• Structure modeling and prediction
• Proteomics

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Major weapons

• Computational algorithm
• Hash method
• Dynamic algorithm
• String and Tree (binary, suffix)
• Clustering
• Probability and Statistical theory and methods
• Bayesian theorem, Markov chain (HMM), Principle
  component
• Monte Carlo simulation
• Neural Network
• Physical chemistry
• Functions to describe the physical chemistry
  interactions in bio-molecules
• Molecular mechanics, Molecular dynamics algorithm
• Data storage and access
• Database Oracle, MySQL etc.
• Web interface

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Genome sequencing Celera shotgun assemblyVenter
et al. 2001
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Gene discoverybased on sequence comparison

• Finding new genes based on their sequence
  similarity and evolution relationship with known
  genes
• Methods
• Hash-based database search method, like BLAST
  (PSI-BLAST), FASTA, BLAT etc.
• Sequence alignment using Dynamic Programming
  algorithm

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BLAST database search (http//www.ncbi.nih.gov/BL
AST/)
Query sequence
Database sequences
Query
database
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Sequence alignment

• Example

BLAST BLA-T

• Programs
• CLUSTALW
• DIALIGN

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Dynamics algorithm
Sequence A (A1, A2, , Ai, ..., Am) Sequence B
(B1, B2, , Bj, , An)
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Ab initio gene prediction methods

• Statistics based gene prediction
• Nucleotides distribution frequencies in the
  coding regions
• Exon/Intron boundary signal
• Examples
• GenScan, Burge and Karlin 1997
• Fgenesh, Solovyev and Salamov 1994

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Hybrid gene prediction method

• Example Celera Otto program
• BLAST against Refseq database
• BLAST against EST database, other genomic
  sequences etc.
• Genscan, Fgenesh

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Problems in Gene discovery

• Example Given a cDNA sequence, find its true
  location in the genome map among lots of
  alternatives

Query transcript/protein
Genomic component
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Two-step solution

1. BLAST search of the cDNA sequence against the
   whole genome map
2. Using an LIS algorithm to find the correct
   genomic component hit

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Phylogenetic analysis

• Goal study the function and evolution
  relationship among a group of genes
• Divide homologous genes into function families
• Find the evolution relationship between the
  ortholog genes belonging to different species
  (e.g., the theory of Out of Africa)
• Methods
• Hierarchical Clustering
• Neighbore-joining etc.
• PHYLIP program, Univ. of Washington

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(No Transcript)
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Micro-array analysis

• Expression-genomics
• Primary goals
• Look for the genes with different expression
  levels between experiments, which are candidates
  of functional genes
• Look for the group of genes that have correlated
  gene expression levels, which could suggest that
  they are in the same biological pathway

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• Methods
• General probability and statistics methods
• Dimension reduction
• Principle components
• Lowess
• Clustering
• Tools
• S-plus, R

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Example

• Herbicide
• Plants was treated with herbicide to observe the
  gene expression profiles in a series of time
  steps.
• The genes that appeared right before plant dies
  (12 hours) are the possible death genes
• If we knock down the death genes in the normal
  plants, they could last longer time than the
  herbs.

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Protein structure prediction

• Why is protein structure important?
• The functions of a gene depend on its translated
  protein structure
• Protein binding with its ligands
• Protein-protein interactions
• A protein molecule usually keeps one stable
  structure under normal physiological conditions
  (Anfinson, 1960es)
• Drug design
• Docking and high throughput drug screening.

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Sequence
Bioinformatics
Protein structure
Function
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Protein structure prediction methods
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Homology modeling procedure
Protein sequence
Database search
Select template structure
Sequence alignment
Build conserved regions first
Loop modeling
Build side-chains
Optimizing
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Homology modeling programs

• Academic software
• MODELER, Sali A.
• COMPOSER, Blundell T.
• SWISS-MODEL
• Rasmol (graphics)
• Commercial software
• QUANTA, MSI inc.
• SYBYL, TRIPOS inc.

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Threading

• Find the best fold candidates among a limited
  number of choices
• Add 3D information to the score function of
  dynamic programming

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Ab initio protein structure principle
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• Threading programs
• Topits, Eisenberg D.
• Threader, Jones D.
• ProSup, Sipple M
• 123D, Alexandra N.
• Ab initio programs
• Rosetta, David Baker

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Current status in the protein structure
prediction field

• Moult J., CASP (Critical Assessment of Techniques
  for Protein Structure Prediction).
• Homology modeling is very mature already
• Threading and Ab initio method have been used in
  industry
• Structure genomics

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Large scale computing platform

• Hardware
• Super-computers
• Cray/SGI
• DEC/Compaq
• Intel
• Linux clusters
• Blade
• Software
• Parallel computing (MPP, PVM etc.)
• Linux
• Grid computing the Globus Project

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Linux clusters
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Data storage and access

• Bioinformatics is producing huge amount of data
  each day
• How to organize and store data
• How to access data
• Database software
• Commercial
• Oracle, DB2, Sybase
• Freeware
• MySQL, PostgreSQL

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Data store and access

• Bioinformatics is producing huge amount of data
  each day
• How to organize and store data
• How to access data
• Database software
• Commercial
• Oracle, DB2, Sybase
• Freeware
• MySQL, PostgreSQL
• Current popular database
• DNA, protein sequence, like Genbank, SwisProt,
  PIR etc.
• Protein structure, like PDB, Scop
• DNA, mRNA, protein function, like GO, PFAM

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Database example Gene Ontology (GO)
Molecular function
Biological process
Cellular component
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Data access

• Web interface
• Protocol
• CGI, JSP, ASP
• Computer languages
• Perl, Java, C/C, Visual Basic, Visual C

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Forth looking

• Where are the markets
• Develop new programs
• Assemble current programs to build more efficient
  data mining pipelines
• Data storage and access
• Integrate the current database to use them more
  effectively
• Computing platform, including hardware, software
  support, consulting etc.
• What we can offer
• Multi-talents
• Team work
• Networking

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http//www.hongyu.org/paper/bioinformatics.ppt