1. Future Challenges in Bioinformatics
RRX Pharma-Bioinformatics

2. Introduction Introduction: How RRX got involved …
Life sciences context: How bioinformatics came to be important…
The past half century: How bioinformatics has “evolved”…
RRX Pharma-Bioinformatics

3. Introduction Categories of Bioinformatics Tools
Why We Need Supercomputers
Software Development Issues
Future Challenges
Tools for Biotech Projects
Summary
RRX Pharma-Bioinformatics

4. How RRX got involved …
Submitted a Canadian Foundation for Innovation (CFI) proposal for Advanced Bioinformatics Collaborative Computing (ABioCC)
RRX Pharma-Bioinformatics

5. How RRX got involved … Developed an SVG based visualization front end
Paper will be presented at SVG Open 2003 in Vancouver on July 17th
RRX Pharma-Bioinformatics

6. How bioinformatics came to be important…
After the structure of DNA was reverse engineered with X-Ray diffraction in 1953 focus shifted to nucleic acid sequence analysis
DNA/RNA/protein sequence data accumulated using computer programs for storage and analysis
RRX Pharma-Bioinformatics

7. How bioinformatics came to be important…
Bioinformatics algorithms in development for the last half century came into wide spread use by researchers
The ability to compare sequences created a homology context for unknown sequences of interest leading to advances…
RRX Pharma-Bioinformatics

8. How bioinformatics came to be important…
Improved sequencing technology enabled the complete deciphering of the human genome >>> 1999
About 3.18 billion base pairs
Celera used 300 PE Biosystems ABI Prism 3700 DNA Analysers
RRX Pharma-Bioinformatics

9. How bioinformatics has “evolved”…
Central dogma of molecular biology –
DNA sequences are transcribed into mRNA sequences, mRNA sequences are translated into protein sequences, which fold 3D creating structures with functions statistically survival selected >>> affecting the prevalence of the underlying DNA sequences in a population
RRX Pharma-Bioinformatics

10. How bioinformatics has “evolved”…
This created a supporting information flow
Organization and control of genes in the DNA sequence
Identification of transcriptional units in the DNA sequence
Prediction of protein structure from sequence
Analysis of molecular function
RRX Pharma-Bioinformatics

11. How bioinformatics has “evolved”…
Another covariant information flow was created based on the scientific method
Create hypothesis wrt biological activity
Design experiments to test the hypothesis
Evaluate resulting data for compatibility with the hypothesis
Extend/modify hypothesis in response
RRX Pharma-Bioinformatics

12. How bioinformatics has “evolved”…
IT used to handle explosion of data from high throughput techniques, too complex for manual analysis
X-ray diffraction
RRX Pharma-Bioinformatics

13. How bioinformatics has “evolved”…
Automated DNA sequencing
Amersham Biosciences
Applied Biosystems
Beckman Coulter
LI-COR
SpectruMedix Corp.
Visible Genetics Corp.
RRX Pharma-Bioinformatics

14. How bioinformatics has “evolved”…
Microarray expression analysis
RRX Pharma-Bioinformatics

15. How bioinformatics has “evolved”…
Rapid emergence of 3D macromolecular structure databases
New sub discipline: structural bioinformatics
Atomic and sub cellular spatial scales
Representation/physics
Storage/retrieval/source data correlation/interpretation
Analysis/simulation
Display/visualization
RRX Pharma-Bioinformatics

16. How bioinformatics has “evolved”…
RRX Pharma-Bioinformatics

17. Categories of Bioinformatics Tools…
Databases >>> search/compare
Sequence Analysis - Clusters
Genomics
Phylogenics
Structure Prediction
Molecular Modelling
Microarrays
Packages, Misc Apps, Graphics, Scripts
RRX Pharma-Bioinformatics

18. Categories of Bioinformatics Tools…
Database >>> search/compare
aceperl
BLAST
Blastall
Blastpgp
BLAT
Blimps
Entrez
FASTA
fastacmd
formatdb
getz
HMMER
IMPALA
InterProScan
PHI-BLAST
ProSearch
PSI-BLAST
PSI-BLASTN
Seguin
Swat
tace
xace
RRX Pharma-Bioinformatics

19. Sequence Analysis Artemis Bl2seq BLAST Clustal W, X consed/autofinish
Cross_match
Dotter
EMBOSS
FASTA
Glimmer
HMMER
InterProScan
MEME
View
Paracel Transcript Assem
Phrap
Phred
Primers
ProSearch
Readseq2
Rnabob
RRTree
SAPS
seals
Seqsblast
STADEN
Swat
T-Coffee
RRX Pharma-Bioinformatics

20. Genomics Calc_primers Cross_match FPC GENSCAN Glimmer Image Mzef Phrap
Phred
STADEN
Swat
tace
tace_celegans
tRNAscan-SE
xace
xace_celegans
RRX Pharma-Bioinformatics

21. Phylogenics Clustal W Clustal X MOLPHY MrBayes PHYLIP RRTree T-Coffee
TREE-PUZZLE
TreeViewX
RRX Pharma-Bioinformatics

22. Structure Prediction EMBOSS MEME Modeller Mzef PHI-BLAST
RRX Pharma-Bioinformatics

23. Molecular Modelling Modeller Rasmol Raster3D (publishing images) X3DNA
homology modeling an alignment of a sequence to be modeled with known related structures
Rasmol
a molecular graphics program intended for 3D visualisation of proteins and nucleic acids
Raster3D (publishing images)
X3DNA
analyzing and rebuilding 3D structures
RRX Pharma-Bioinformatics

24. Microarrays Dapple OligoArray
a program for quantitating spots on a two-colour DNA microarray image..
OligoArray
a program that computes gene specific oligonucleotides that are free of secondary structure for genome-scale oligonucleotide microarray construction.
RRX Pharma-Bioinformatics

25. Packages, Useful Scripts/Source Code, Graphics, PERL
BioPERL
BioJava
boxshade
mvscf
seg
Split_fasta
povRay
Raster3D
MOLPHY
RRX Pharma-Bioinformatics

26. Why We Need Supercomputers…
Some commercial packages run on “supercomputers”
Accelrys: modeling and simulation
Materials Studio
Cerius2 (SGI Unix only)
Homology modeling to catalyst design
Insight II (SGI Unix only)
3D graphical environment for physics based molecular modeling
Catalyst (high end Unix servers)
database management valuable in drug discovery research
QUANTA (high end Unix servers)
crystallographic 2D/3D protein structure solution
Discovery Studio
RRX Pharma-Bioinformatics

27. Why We Need Supercomputers…
Supercomputer advantages
Multiple processors
Large shared memory
Handle very large files
Large/fast RAID arrays
Terabyte tape backup systems
Power backup systems
High performance networks
RRX Pharma-Bioinformatics

28. Why We Need Supercomputers…
Common bioinformatics requirements
Computationally intensive tasks
Large memory models
Intensive/complex database searches
Large experimental database sets
Large derived database sets
Large persistent intermediate data structures
Teamwork data sharing and visualization
RRX Pharma-Bioinformatics

29. Why We Need Supercomputers…
Network requirements
Driving gigE/10gigE NICs
Moving large files/data sets rapidly
Visualization streams/Access GRID
Coordinating Cluster/GRID computing
Dynamic provisioning of light paths
RRX Pharma-Bioinformatics

30. Why We Need Supercomputers…
RRX Pharma-Bioinformatics

31. Why We Need Supercomputers…
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RRX Pharma-Bioinformatics

32. Software Development Issues…
Collaboration contexts/barriers
Team work … collaboration spaces
Standards development … DTDs
Integration issues…
experimental data to homology to 3D model
platform issues…
network issues – 9k MTU - jumbo frames
Licensing issues – public vs. private
RRX Pharma-Bioinformatics

33. Future Challenges…
Creating developer infrastructure for building up structural models from component parts …
components from macromolecule libraries ported to object models
Understanding the design principles of systems of macromolecules and harnessing them to create new functions …
specialized molecular machines
RRX Pharma-Bioinformatics

34. Future Challenges…
Learning to design drugs efficiently and cost effectively based on knowledge of the target …
target generation automation
validation automation
Development of enhanced simulation models that give insight into context based function from knowledge of structure …
possible use of artificial intelligence to limit scope of search
RRX Pharma-Bioinformatics

35. How Tools might be used for Industry Biotech Projects
RRX Pharma-Bioinformatics

36. Summary Bioinformatics
well positioned to assist with application development
exploring novel bioinformatics software development
proceeding with supporting access GRID and optical switching technology
RRX Pharma-Bioinformatics

37. Questions/Comments… ? ;-)
RRX Pharma-Bioinformatics