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E-Science Tools For The Genomic Scale Characterisation Of Bacterial Secreted Proteins Tracy Craddock, Phillip Lord, Colin Harwood and Anil Wipat Newcastle.

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Presentation on theme: "E-Science Tools For The Genomic Scale Characterisation Of Bacterial Secreted Proteins Tracy Craddock, Phillip Lord, Colin Harwood and Anil Wipat Newcastle."— Presentation transcript:

1 e-Science Tools For The Genomic Scale Characterisation Of Bacterial Secreted Proteins Tracy Craddock, Phillip Lord, Colin Harwood and Anil Wipat Newcastle University

2 Outline  Computational challenges of bioinformatics  Secretion in Bacillus  Classification and analysis workflows  Results and discussion

3 Computational Challenges of Bioinformatics  New requirements from bioinformatics  3 major problems  Heterogeneity  Distribution  Autonomy  Experiments - series of workflows

4 my Grid and Taverna Scufl Simple Conceptual Unified Flow Language Taverna Writing, running workflows & examining results SOAPLAB Makes applications available Freefluo Workflow engine to run workflows Freefluo SOAPLAB Web Service Any Application Web Service e.g. DDBJ BLAST

5 Microbase  Grid-based system for microbial genome comparison and analysis  Information repository (and execution environment)  Pre-computed data

6 Outline  Computational challenges of bioinformatics  Secretion in Bacillus  Classification and analysis workflows  Results and discussion

7 Secretion in Bacillus  Predict characteristics & behavior of bacteria  Identify secreted proteins  Bacillus species diverse behaviour  Soil inhabitants  Harmful bacteria

8 Importance of Secretion  Mechanism of interaction with environment  Reveal capabilities of an organism  Pathogens are of great interest

9 Secretory Proteins Cytoplasm Medium Membrane Cell Wall Signal Peptide Lipoprotein Cell wall binding Transmembrane LPXTG

10 Outline  Computational challenges of bioinformatics  Secretion in Bacillus  Classification and analysis workflows  Results and discussion

11 Bioinformatic Tools Cytoplasm Medium Membrane Cell Wall Signal Peptide Lipoprotein Cell wall binding Transmembrane LPXTG Signalp TMHMM tmap MEMSAT LipoP ps_scan

12 Classification Workflow

13 Process of Analysis Putative secreted proteins Protein families Functional classification Relations

14 Analysis Workflow

15 Architecture  Custom-designed database  Provenance tracking  Analysis – computationally intensive  Architecture differs from other systems

16 Web Portal

17 Outline  Computational challenges of bioinformatics  Secretion in Bacillus  Classification and analysis workflows  Results and discussion

18 Classification Results

19 Functions of the Clusters Number of families

20 Biologist’s Outlook  Results available for subsequent analysis  Data and results are of great interest

21 eScientist’s Outlook  Microbase simplified data analysis But …  Autonomy - most services provided originally by external parties  Licensing – limits exposure of services  Distribution - difficulty came from the relatively large datasets

22 Future Enhancements  Use notification to automatically analyse recently annotated genomes  Migrate workflows to a remote enclosed environment?

23 Acknowledgments  Phillip Lord  Colin Harwood  Anil Wipat my Grid  Carole Goble  Tom Oinn … and the rest of the my Grid team Microbase  Yudong Sun  Anil Wipat  Matthew Pocock  Pete A. Lee  Paul Watson  Keith Flanagan  James T. Worthington


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