The Poor Beginners

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The Poor Beginners Guide to Bioinformatics
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What we have and dont have...

• a computer connected to the Internet (incl. Web
  browser)
• a text editor (Notepad or better)
• public databases of genomic sequences
• public databases of cDNA EST
• public databases of protein sequences, structures
  and motifs
• money for specialised software packages
• public servers capable of (almost) anything we
  wish to do

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Dealing with a sequence model tasks

• basic (DNA) sequence manipulation restriction
  analysis, translation
• sequence similarity and pattern/motif searches
• gene building modelling exon-intron structures
• protein domain searches,structure analysis
• construction and interpretation of sequence
  alignments

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Notes on basic sequence handling

• Make sure you have the correct format.
• FASTA format is (almost) always correct.
• gtsequencename
• thisisasequenceinfastaformat
• If not, you can always use raw data.
• If things dont work, check for gaps in sequence,
  empty lines, and file extension.
• BEWARE OF MICROSOFT!

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Model tasks continued

• basic (DNA) sequence manipulation restriction
  analysis, translation
• sequence similarity and pattern/motif searches
• gene building modelling exon-intron structures
• protein domain searches,structure analysis
• construction and interpretation of sequence
  alignments

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Defining a gene family

• By overall domain structure
• By domain sequence
• Based on a peptide motif

L-X-X-G-N-X-ML-N
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Sequence comparison-based searches

• Entrez related sequences
• easy identification of false starts
• no organism selection
• BLAST/FASTA
• all DNA/protein combinations
• taxonomy selection possible
• statistical data provided
• domain structure comparison available
• divergent motifs may be missed

Two methods are better than one.
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Notes on all sequence comparisons, searches,
alignments

• Start with defaults (the authors know what they
  are doing)
• BUT dont be afraid to vary the parameters
• Chose a reasonable scoring matrix
• Distant sequences low BLOSUM, high PAM
• Closely related sequences low PAM, high BLOSUM

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Motif-based searches

• sensitive
• no statistics
• only protein databases can be searched
• TAIR PatMatch
• Arabidopsis - specific
• Problematic user interface
• ISREC - INSECTS
• admirable technology
• access to SwissProt and TrEMBL
• no organism selection

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Model tasks continued

• basic (DNA) sequence manipulation restriction
  analysis, translation
• sequence similarity and pattern/motif searches
• gene building modelling exon-intron structures
• protein domain searches,structure analysis
• construction and interpretation of sequence
  alignments

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Some genes are more alike than others

• A number of splicing prediction servers available
• Agreement of different methods is a good sign but
  no absolute measure
• Always align ESTs if possible
• Beware of non-conventional intron boundaries
  (GC-AG instead of GT-AG)
• Plant data for transcription start/factor binding
  sites prediction are limited

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Model tasks continued

• basic (DNA) sequence manipulation restriction
  analysis, translation
• sequence similarity and pattern/motif searches
• gene building modelling exon-intron structures
• protein domain searches,structure analysis
• construction and interpretation of sequence
  alignments

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Searching for known domains/motifs

• Searching for PROSITE patterns allowing
  ambiguities
• PROSITE and Pfam profile searches
• SMART, CDsearch (domains and more)

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Predicting protein localisation

• predicting signal peptides/anchors
• 2 methods available
• possibility to predict organelle localisation

• transmembrane segments prediction

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Model tasks continued

• basic (DNA) sequence manipulation restriction
  analysis, translation
• sequence similarity and pattern/motif searches
• gene building modelling exon-intron structures
• protein domain searches,structure analysis
• construction and interpretation of sequence
  alignments

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Alignment manual or automated?

• objective results
• a number of servers available
• recommended for well-conserved proteins
• empiric parameters (e.g. gap penalties)
• bad for divergent sequences

• locally installed, free, for Mac and PC
• interactive domain definition
• statistical data provided
• may produce false-positive blocks (read the
  on-line manual!)

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Phylogenetic analyses

• Two methods are better than one.
• Your phylogeny cannot be better than your
  alignment.
• Gaps are no data.
• Allways do bootstrapping (100-500 cycles)
• Certain questions cannot be answered from an
  unrooted tree.

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Points to take off...

• go to the Bioinformatics page http//www2.rhul.ac.
  uk/ujba110/Bioinfo.htm
• select your exercise (A,B,C,D,E)
• and enjoy it!
• If you mean it seriously
• create your own bookmarks (seed provided on the
  course web page)

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