using_webbased_tools.ppt
- 1. Bioinformatics Resources and Tools on the Web: A Primer Joel H. Graber Center for Advanced Biotechnology Boston University
- 2. Outline • Introduction: What is bioinformatics? • The basics – The five sites that all biologists should know • Some examples – Using the tools in a somewhat less-than-naïve manner • Questions/comments are welcome at all points • Much of this material comes from the Boston University course: BF527 Bioinformatic Applications (http://matrix.bu.edu/BF527/)
- 4. Examples of Bioinformatics • Database interfaces – Genbank/EMBL/DDBJ, Medline, SwissProt, PDB, … • Sequence alignment – BLAST, FASTA • Multiple sequence alignment – Clustal, MultAlin, DiAlign • Gene finding – Genscan, GenomeScan, GeneMark, GRAIL • Protein Domain analysis and identification – pfam, BLOCKS, ProDom, • Pattern Identification/Characterization – Gibbs Sampler, AlignACE, MEME • Protein Folding prediction – PredictProtein, SwissModeler
- 5. Things to know and remember about using web server-based tools • You are using someone else’s computer • You are (probably) getting a reduced set of options or capacity • Servers are great for sporadic or proof-of- principle work, but for intensive work, the software should be obtained and run locally
- 6. Five websites that all biologists should know • NCBI (The National Center for Biotechnology Information; – http://www.ncbi.nlm.nih.gov/ • EBI (The European Bioinformatics Institute) – http://www.ebi.ac.uk/ • The Canadian Bioinformatics Resource – http://www.cbr.nrc.ca/ • SwissProt/ExPASy (Swiss Bioinformatics Resource) – http://expasy.cbr.nrc.ca/sprot/ • PDB (The Protein Databank) – http://www.rcsb.org/PDB/
- 7. NCBI (http://www.ncbi.nlm.nih.gov/) • Entrez interface to databases – Medline/OMIM – Genbank/Genpept/Structures • BLAST server(s) – Five-plus flavors of blast • Draft Human Genome • Much, much more…
- 8. EBI (http://www.ebi.ac.uk/) • SRS database interface – EMBL, SwissProt, and many more • Many server-based tools – ClustalW, DALI, …
- 9. SwissProt (http://expasy.cbr.nrc.ca/sprot/) • Curation!!! – Error rate in the information is greatly reduced in comparison to most other databases. • Extensive cross-linking to other data sources • SwissProt is the ‘gold-standard’ by which other databases can be measured, and is the best place to start if you have a specific protein to investigate
- 10. A few more resources to be aware of • Human Genome Working Draft – http://genome.ucsc.edu/ • TIGR (The Institute for Genomics Research) – http://www.tigr.org/ • Celera – http://www.celera.com/ • (Model) Organism specific information: – Yeast: http://genome-www.stanford.edu/Saccharomyces/ – Arabidopis: http://www.tair.org/ – Mouse: http://www.jax.org/ – Fruitfly: http://www.fruitfly.org/ – Nematode: http://www.wormbase.org/ • Nucleic Acids Research Database Issue – http://nar.oupjournals.org/ (First issue every year)
- 11. Example 1: Searching a new genome for a specific protein • Specific problem: We want to find the closest match in C. elegans of D. melanogaster protein NTF1, a transcription factor • First- understanding the different forms of blast
- 12. The different versions of BLAST
- 13. 1st Step: Search the proteins • blastp is used to search for C. elegans proteins that are similar to NTF1 • Two reasonable hits are found, but the hits have suspicious characteristics – besides the fact that they weren’t included in the complete genome!
- 14. 2nd Step: Search the nucleotides • tblastn is used to search for translations of C. elegans nucleotide that are similar to NTF1 • Now we have only one hit – How are they related?
- 15. Conclusion: Incorrect gene prediction/annotation • The two predicted proteins have essentially identical annotation • The protein-protein alignments are disjoint and consecutive on the protein • The protein-nucleotide alignment includes both protein-protein alignments in the proper order • Why/how does this happen?
- 16. Final(?) Check: Gene prediction • Genscan is the best available ab initio gene predictor – http://genes.mit.edu/GENSCAN.html • Genscan’s prediction spans both protein- protein alignments, reinforcing our conclusion of a bad prediction
- 17. Ab initio vs. similarity vs. hybrid models for gene finding • Ab initio: The gene looks like the average of many genes – Genscan, GeneMark, GRAIL… • Similarity: The gene looks like a specific known gene – Procrustes,… • Hybrid: A combination of both – Genomescan (http://genes.mit.edu/genomescan/)
- 18. A similar example: Fruitfly homolog of mRNA localization protein VERA • Similar procedure as just described – Tblastn search with BLOSUM45 produces an unexpected exon • Conclusion: Incomplete (as opposed to incorrect) annotation – We have verified the existence of the rare isoform through RT-PCR
- 19. Another example: Find all genes with pdz domains • Multiple methods are possible • The ‘best’ method will depend on many things – How much do you know about the domain? – Do you know the exact extent of the domain? – How many examples do you expect to find?
- 20. Some possible methods if the domain is a known domain: • SwissProt – text search capabilities – good annotation of known domains – crosslinks to other databases (domains) • Databases of known domains: – BLOCKS (http://blocks.fhcrc.org/) – Pfam (http://pfam.wustl.edu/) – Others (ProDom, ProSite, DOMO,…)
- 21. Determination of the nature of conservation in a domain • For new domains, multiple alignment is your best option – Global: clustalw – Local: DiAlign – Hidden Markov Model: HMMER • For known domains, this work has largely been done for you – BLOCKS – Pfam
- 22. If you have a protein, and want to search it to known domains • Search/Analysis tools – Pfam – BLOCKS – PredictProtein (http://cubic.bioc.columbia.edu/predictprotein/predictprotein.html)
- 23. Different representations of conserved domains • BLOCKS – Gapless regions – Often multiple blocks for one domain • PFAM – Statistical model, based on HMM – Since gaps are allowed, most domains have only one pfam model
- 24. Conclusions • We have only touched small parts of the elephant • Trial and error (intelligently) is often your best tool • Keep up with the main five sites, and you’ll have a pretty good idea of what is happening and available