Bioinformatics Tools

1

• Bioinformatics Tools

2
What is Bioinformatics

• The use of computers to collect, analyze, and
  interpret biological information at the molecular
  level.
• "The mathematical, statistical and computing
  methods that aim to solve biological problems
  using DNA and amino acid sequences and related
  information."
• A set of software tools for molecular sequence
  analysis

3
Major Types of Tools

• Database design and query tools for biology
• String alignment (pairwise multiple)
• Similarity searching
• (scoring alignments vs. hash tables)
• Pattern searching
• finding genes in genomes
• promoters - combinatorial regulators
• functional regions of proteins
• Clustering
• phylogenetics (evolutionary trees)
• gene expression profiling
• genetic profiling

4
GenBank

• All DNA sequence data is stored in a database
  called GenBank managed by the National Center for
  Biotechnology Information (NCBI)
• The NCBI is a branch of the National Library of
  Medicine, which is part of the NIH (National
  Institutes of Health).
• http//ncbi.nlm.nih.gov

5
(No Transcript)
6
Entrez is a Tool for Finding Sequences

• NCBI has created a Web-based tool called Entrez
  for finding sequences in GenBank.
• Each sequence in GenBank has a unique accession
  number.
• Entrez can also search for keywords such as gene
  names, protein names, and the names of orgainisms
  or biological functions

7

8
Finding Genes in GenBank

• GenBank contains approximately 10 billion bases
  in 8.2 million sequence records (as of December
  2000).
• These billions of G, A, T, and C letters would be
  almost useless without descriptions of what genes
  they contain, the organisms they come from, etc.
• All of this information is contained in the
  "annotation" part of each sequence record.

9
(No Transcript)
10
Flatfile Relational

• GenBank itself is a flatfile database with
  keywork delimited fields.
• GenBank is also indexed into a much larger
  relational database that has links to published
  papers, protein structures and much more.

11
(No Transcript)
12
Entrez is Internally Cross-linked

• DNA and protein sequences are linked to other
  similar sequences
• Medline citations are linked to other citations
  that contain similar keywords
• 3-D structures are linked to similar structures

13
(No Transcript)
14
Pairwise Alignment

• The alignment of two sequences (DNA or protein)
  is a relatively straightforward computational
  problem.
• The best solution seems to be an approach called
  Dynamic Programming.

15
(No Transcript)
16
(No Transcript)
17
Multiple Alignments

• Aligning a large number of sequences using
  dynamic programming is essentially impossible
• The problem increases exponentially with the
  number of sequences involved
• Current multiple alignment programs use a
  progressive method that makes pairwise
  alignments, then adds new sequences one at a time
  to these aligned groups.

18
(No Transcript)
19
Similarity Searching

• There are a variety of computer programs that are
  used for making comparisons between DNA
  sequences.
• The most popular is called BLAST (Basic Local
  Alignment Search Tool)
• BLAST is free at the NCBI website
• BLAST compares your sequence to all of the
  sequences in GenBank and finds the best matches.

20
(No Transcript)
21

• gtgbBE588357.1BE588357 194087 BARC 5BOV Bos
  taurus cDNA 5'.
• Length 369
• Score 272 bits (137), Expect 4e-71
• Identities 258/297 (86), Gaps 1/297 (0)
• Strand Plus / Plus
• 
  
• Query 17 aggatccaacgtcgctccagctgctcttgacgactccac
  agataccccgaagccatggca 76
• 
  
• Sbjct 1 aggatccaacgtcgctgcggctacccttaaccact-cgc
  agaccccccgcagccatggcc 59
• 
  
• Query 77 agcaagggcttgcaggacctgaagcaacaggtggagggg
  accgcccaggaagccgtgtca 136
• 
  
• Sbjct 60 agcaagggcttgcaggacctgaagaagcaagtggagggg
  gcggcccaggaagcggtgaca 119
• 
  
• Query 137 gcggccggagcggcagctcagcaagtggtggaccaggcc
  acagaggcggggcagaaagcc 196

22
BLAST is Complex

• Similarity searching relies on both alignment and
  distance between pairs of sequences.
• Distances can only be measured between aligned
  sequences (match vs. mismatch at each position).
• A similarity search is a process of scoring the
  alignment of a query sequence with every sequence
  in a database.

23
BLAST is Approximate

• BLAST makes similarity searches very quickly
  because it takes shortcuts.
• It also makes errors
• missing some important similarities
• making many incorrect matches

24
Gene Finding

• How can we find genes on chromosomes (sequenced
  genomic DNA)?
• Genome project data is just huge chunks of DNA.
• Does automatic annotation work?

25
Raw Genome Data
26
Finding Genes is Not Easy

• About 1 of human DNA encodes functional genes.
• Genes are interspersed among long stretches of
  non-coding DNA.
• Repeats, pseudo-genes, and introns confound
  matters

27
Pattern Finding Tools

• It is possible to use DNA sequence patterns to
  predict genes
• promoters
• translational start and stop codes (ORFs)
• intron splice sites
• codon bias

28
Similarity to Known Genes

• It is also possible to scan new DNA sequence for
  known genes
• Can look for annotated genes/proteins
• Or just for RNAs (ESTs)

29
(No Transcript)
30
Patterns in Proteins
31
Motifs

• Some structures can be recognized as sequence
  patterns
• transmembrane domains
• coiled coils
• helix-turn-helix
• signal peptides

32
Functional Motifs

• Other functional portions of proteins can be
  recognized by their sequence, even if their 3-D
  structure is not known.
• There are many databases of protein
  motifs/domains ProSite, Pfam, ProDom, etc.

33
(No Transcript)
34
Protein 3-D Structure
35
Structure Function

• Proteins function by 3-D interactions with other
  molecules (i.e. physical chemistry).
• So for a protein, 3-D structure is function.
• But we cant accurately determine 3-D structure
  from gene sequence.

36
Structure Prediction

• Predicting a proteins 3-D structure from its
  amino acid sequence is incredibly complex
• proteins are polypeptides (long chains of amino
  acids)
• can fold and rotate around bonds within each
  amino acid as well as the bonds between them
• it is not possible to evaluate every possible
  folding pattern for an amino acid sequence

37
Chemical Properties

• Some chemical properties of a protein can be
  calculated from its amino acid sequence
• molecular weight
• charge/pH
• hydrophobicity

38
Secondary Structure

• The local structure of the amino acids in a
  protein can also be predicted to some extent.
• Each amino acid has a tendency to form either an
  alpha helix or a beta sheet

39
Threading

• Rather than computing a 3-D structure from
  scratch, it may be possible to find a similar
  structure
• Must have 25 aa sequence identity
• Uses a process called threading to create a new
  structure based on a known structure

40
(No Transcript)
41
Protein Data Base

• There is a database of all known protein
  structures called the PDB.
• These have been determined by X-ray
  crystalography and/or NMR.
• Anyone download and view these structures with a
  PDB viewer program.

42
Clustering

• Clustering is used in many different ways in
  biology
• Grouping things based on shared properties is a
  fundamental aspect of biology
• There are many different clustering algorithms
  it is not at all clear which ones perform best
  for the various applications.

43
Phylogenetics

• Evolution mutation of DNA (and protein)
  sequences
• Can we define evolutionary relationships between
  organisms by comparing DNA sequences
• is there one molecular clock?
• phenetic vs. cladisitic approaches
• lots of methods and software, what is the
  "correct" analysis?

44
(No Transcript)
45
(No Transcript)
46
(No Transcript)
47
Computer Exercise

• Now you will have a chance to try out some of
  these bioinformatics tools
• Use Entrez to search for sequence and journal
  articles
• Find genes in human DNA
• Use BLAST to search for similar sequences
• Look at a family of protein sequence in a motif
  database
• Think about how these tools are built -
  underlying databases and algorithms, interface,
  etc.