Integrative Information Management for Systems Biology

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The MCISB develops experimental and computational technologies in systems biology. It employs 9.5 multidisciplinary people to develop kinetic models of yeast metabolism using genome-scale SBML models annotated with MIRIAM standards. The modeling process involves identifying pathways to model, associating models with functions and parameter values, and analyzing/simulating resulting models.

Technology

Integrative Information Management for Systems Biology ,[object Object],[object Object],[object Object],[object Object]

The MCISB ,[object Object],[object Object],[object Object],[object Object],[object Object]

Models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Bottom-up systems biology ,[object Object],[object Object],[object Object],[object Object]

Bottom-up systems biology ,[object Object],[object Object],[object Object]

Automation of the process ,[object Object],[object Object],[object Object],[object Object]

Enzyme kinetics Quantitative metabolomics Quantitative proteomics SBML Model Parameters (K M , k cat ) Variables (metabolite, protein concentrations) PRIDE XML MeMo SABIO-RK Web service KRDB Web service

From instrument to result ,[object Object],[object Object],[object Object],[object Object]

Requirements ,[object Object],[object Object],[object Object],[object Object]

Data capture ,[object Object],[object Object],[object Object],[object Object],[object Object]

QconCAT PrideWizard eXist database PRIDE XML Identify QconCAT Pride Wizard Quantify Format Upload Web / web service Browser Mascot PRIDE XML PRIDE Converter mzData Pride

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Key Results Database ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Key Results Database ,[object Object],[object Object],[object Object]

Qualitative model construction Input: list of ORFs Output: SBML file 1. Get reaction info 3. Create species 2. Create compartments 4. Create reactions

Qual to quan: parameterisation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Model calibration ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

COPASI web service Design and Architecture of Web Services for Simulation of Biochemical Systems. Dada JO, Mendes P. Data Integration in the Life Sciences, Manchester, UK (2009).

SBRML ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Conclusion ,[object Object],[object Object],[object Object]

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Integrative Information Management for Systems Biology

3. Metabolism

8. Enzyme kinetics Quantitative metabolomics Quantitative proteomics SBML Model Parameters (K M , k cat ) Variables (metabolite, protein concentrations) PRIDE XML MeMo SABIO-RK Web service KRDB Web service

10.

11.

12. KineticsWizard

13. QconCAT PrideWizard

14. QconCAT PrideWizard eXist database PRIDE XML Identify QconCAT Pride Wizard Quantify Format Upload Web / web service Browser Mascot PRIDE XML PRIDE Converter mzData Pride

15. Web interfaces

16.

17.

18.

19.

20.

21. Key Results Database

22. KRDB structure

23. KRDB web interface

24. KRDB web interface

25.

26. Modelling infrastructure

27. Taverna http://taverna.sourceforge.net

28. Taverna

29. Modelling life-cycle workflows

30. Qualitative model construction Input: list of ORFs Output: SBML file 1. Get reaction info 3. Create species 2. Create compartments 4. Create reactions

31. Qualitative model construction

32.

33. Qual to quan: parameterisation

34. Model parameterisation

35.

36. COPASI web service Design and Architecture of Web Services for Simulation of Biochemical Systems. Dada JO, Mendes P. Data Integration in the Life Sciences, Manchester, UK (2009).

37. Model calibration

38.

39. Model simulation

40.

41. Model simulation

42.

43.

44. Thanks…

45.