Basic Overview of Bioinformatics Tools and Biocomputing Applications I

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Basic Overview of Bioinformatics Tools and
Biocomputing Applications I

• Dr Tan Tin Wee
• Director
• Bioinformatics Centre

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Software Tools

• Data stored in retrievable forms in database
  systems
• Data generated by machines, DNA / Protein
  sequencers, automated systems

AutomatedMachines
ResearchLabs
Biological Data
Analytical Tools
Databases
New Knowledge
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Common Computational Analyses

• Sequence Assembly
• Simple sequence analysis
• Translation and reverse Complement, ORF
• Composition statistics (protein DNA)
• Molecular mass
• Total charge and pI local hydropathy
• Simple determination of secondary structures
• Restriction site analysis
• Internal repeat analysis
• Detection of active sites, functional residues,
  characteristic structures, substrates, and
  processing signals

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Common Computational Analyses

• Database sequence search
• Multiple alignment
• 2 and 3 Structure prediction transmembrane
  helix detection
• Structure modeling
• Docking prediction and design
• Hidden Markov model searches

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Sequence Assembly

• Fragmented data from DNA sequencers
• Detection of Overlap
• Merging of Contigs
• Assembly into continuous sequence

3'
5'
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Sequence Format Interconversion

• DNA/Protein and other sequence data come in
  different formats.
• Annotations
• Different programs use different formats
• Interconversion utility tools
• eg. READSEQ, TOGCG, TOSTADEN, etc

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Simple Sequence Analysis
1. Linear Sequence eg. DNA/ Protein
2. Open a Window - n 1 n
variable n sliding
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Some Simple Sequence Analysis Applications

• DNA complementary strand eg. COMPLEMENT REVERSE
• Open window size 1
• A---gtT
• C ---gtG
• T ---gt A
• G ---gt C
• Slide to next Window of 1
• Proceed to end of sequence
• Reverse order of complement
• 5' ...ATCTCGATACTACTACG...3'
• 3' ...TAGAGCTATGATGATGC...5'

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Some Simple Sequence Analysis Applications

• DNA to Protein sequence translation, e.g.
  TRANSLATE
• Open window of 3 bases
• Look up Codon Usage table
• Assign Amino acid residue
• Slide window to next 3 bases
• Proceed till stop codon detected.
• Repeat whole procedure for six frames

ATACTACTGAGATCTAGGCTAGTACTGCGTGCG
Frame 1 Frame 2 Frame 3
Complement - Frames 4-6
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Some Simple Sequence Analysis Applications

• Detect Open Reading Frame e.g.ORF
• Translate sequence, report long stretches of
  start and stop codons
• Compositional analysis
• eg. Calculate total A, T, G, C
• eg. Calculate total molecular mass of protein,
  analysis percentages of amino acids
• eg. Total Charge composition, pI

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Some Simple Sequence Analysis Applications

• Simple prediction of secondary structure of
  Protein sequence
• decide a window size
• compute for each window of amino acids
  statistical potential to form helix, beta sheet,
  turn, etc. Chou-Fasman, GOR etc algorithms
• use a statistical potential chart
• plot potentials in graphical or pictorial format

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Some Simple Sequence Analysis Applications

• Restriction Mapping eg. MAP, MAPPLOT,MAPSORT,
  PLASMIDMAP etc
• Table of Restriction Enzymes and cut siteseg.
  EcoRI, BamHI AluIand their cut sites eg.
  GAATTC , AATT
• Take a DNA sequence
• Pattern match against the list of cut sites
• For each match, assign Restriction enzyme
• Calculate distance between cut sites
• Display in table, graphical, or restriction map,
  etc

gel
Plasmidmap
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Some Simple Sequence Analysis Applications

• Protein sequence Motifs pattern matching eg.
  PROSITEMAP, MOTIFS, BLOCKS etc
• Table/Database of Sequence Patterns/Motifs and
  their signature sequence eg. Arg-Gly-Asp (RGD)
  or consensus sequence (eg. PROSITE, BLOCKS db)
• Take Protein sequence
• Pattern match against the list of signature sites
• For each match, assign potential function
  according to database
• Display in table or graphically, or hyperlinked

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Some Simple Sequence Analysis Applications

• Peptide Cleavage Maps eg. PEPTIDESORT, PEPTIDE
  MAP
• Table of Protease vs Cleavage sites eg. Trypsin,
  chymotrypsin, and Chemical cleavage sites
  cyanogen bromide
• Pattern match with entire protein sequence
• Calculate size of peptide fragments
• Sort and Map, Plot as electrophoretic patterns on
  a log-linear simulated digest.
• Compute Partial Digest patterns

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Some Simple Sequence Analysis Applications

• DOTPLOT- selfcomparison
• Take a Window size
• Compare against entire length of own sequence
• Report matches above a threshold
• Plot on Graph
• Slide window, repeat till end of sequence
• Detection of Internal repeats
• Pairwise comparison - detection of homology

Sequence A
Sequence A
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Some Simple Sequence Analysis Applications

• RNA secondary structure analysis
• Mfold, PlotFold, FoldRNA, Squiggles, Circles,
  Domes, Mountains, StemLoop
• Folding of RNA into stems, loops
• Calculation of energy - prediction of stability
  of structure
• Display of structure and alternatives

AUCG U G G A
AUGC
UACG
---- -- --
...AUCGA
AUCUC...
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Database Searching

• Text-based Database Searching -using a text
  string to match an annotation in a sequence
  database record, ie. Keyword search
• Sequence-based Database Searching -using a
  biological sequence to match its whole or parts
  of its sequence to the sequences of every
  sequence database records

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Text-Based Database Searching

• Examples Entrez, SRS, DBGET, AceDB- common
  integrated database systems
• Search Concepts
• Boolean Search - AND, OR, NOT
• Broadening Search
• Narrowing the Search
• Proximity searching, soundex
• Wild Card, Stemming eg. Thala for thalasemia,
  thalassemia, thalassemic
• Use standard string search algorithms and boolean
  operations, vocabulary matches

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Text-based Database Searching

• Example To find the human homolog of the
  Drosophila per gene
• Procedure
• Web to Entrez
• All Fields enter "human" "per"
• Hits returned, irrelevant - broaden search
• "human" "period" - more hits
• check every one, find the human RIGUI gene
• Hit and miss, clever guess work, free form or
  controlled vocabulary (MeSH terms)?Use Boolean
  searches?

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Sequence-based Database Searching

• Homology Search
• Global or Local Sequence Alignment
• Needleman-Wunch Algorithm
• Smith-Waterman Algorithm
• Lipman - Pearson FASTA
• Altschul's BLAST
• Take a sequence, pairwise comparison with each
  sequence in the database

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Sequence-based Database Searching

• Basic Assumptions
• Sequences of homologous Genes/Protein diverge
  over time even though structure and/or function
  change little
• Significant sequence similarity inferred as
  potential structural /functional similarity or
  common evolutionary origin
• Based on well-characterised protein, infer the
  function of an unknown sequence at gene or
  protein sequence level.

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Sequence-based Database Searching

• Global Alignmentforces complete alignment of the
  pairwise comparison of the two input sequences
• Local Alignmentlooks for local stretches of
  similarity and tries to align the most similar
  segments
• Algorithms used may be similar, but output
  different, statistics needed to assess results

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Sequence-based Database Searching

• Alignment Scoring
• Substitution score and substitution matrixPAM,
  BLOSUM
• affine gap costs/gap penalty and gap scores
• Optimal alignments, dynamic programmingNeedleman-
  Wunsch algorithm,Smith-Waterman algorithm
  (SSEARCH)
• Additional heuristics - FASTA, BLAST