Methods and systems to identify operational reaction pathways

• US 7,734,420 B2
• Filed: 02/14/2003
• Issued: 06/08/2010
• Est. Priority Date: 10/15/2002
• Status: Active Grant

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Covert, Markus W., Herrgard, Markus, Palsson, Bernhard O.
• Primary Examiner(s): Clow; Lori A
• Application Number:
  US10/367,248
• Publication Number:
  US 20040072723A1
• Time in Patent Office: 2,671 Days
• Field of Search: None
• US Class Current: 702/19
• CPC Class Codes: G01N 33/5005 involving human or animal cells immunoassay G01N33/56966; immunoassays of protozoa G01N33/56905; protozoa in screening assays C12Q1/025
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/10 Gene or protein expression profiling; Expression-ratio estimation or normalisation
• CPC Class Codes: G16B 40/00 ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• CPC Class Codes: G16B 40/30 Unsupervised data analysis
• CPC Class Codes: G16B 5/00 ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• CPC Class Codes: G16B 5/10 Boolean models

Abstract

The present invention provides a method for identifying an operational reaction pathway of a biosystem. The method includes (a) providing a set of systemic reaction pathways through a reaction network representing said biosystem; (b) providing a set of phenomenological reaction pathways of said biosystem, and (c) comparing said set of systemic reaction pathways with said set of phenomenological reaction pathways, wherein a pathway common to said sets is an perational reaction pathway of said biosystem. Also described is a method of refining a biosystem reaction network; a method of reconciling biosystem data sets; a method of determining the effect of a genetic polymorphism on whole cell function; and a method of diagnosing a genetic polymorphism-mediated pathology.

Claims

1. A method of identifying an operational reaction pathway of a biosystem, wherein the steps of said method are performed on a suitably programmed computer programmed to execute the steps comprising:

(a) providing a set of systemic reaction pathways through a reaction network representing said biosystem;

(b) providing a set of phenomenological reaction pathways of said biosystem;

(c) comparing said set of systemic reaction pathways with said set of phenomenological reaction pathways; and

(d) providing an output to a user of the selection of a pathway common to said set of systemic reaction pathways and said phenomenological reaction pathways of said biosystem, wherein said pathway common to said sets is an operational reaction pathway of said biosystem.

2. The method of claim 1, wherein said biosystem is a prokaryotic cell, or biological process thereof.

3. The method of claim 2, wherein said prokaryotic cell is selected from the group consisting of E. coli, B. subtilis, H. influenzae and H. pylori.

4. The method of claim 2, wherein said biological process is metabolism.

5. The method of claim 3, wherein said prokaryotic cell is E. coli.

6. The method of claim 3, wherein said prokaryotic cell is B. subtilis.

7. The method of claim 3, wherein said prokaryotic cell is H. influenzae.

8. The method of claim 3, wherein said prokaryotic cell is H. pylori.

9. The method of claim 1, wherein said biosystem is a eukaryotic cell, or biological process thereof.

10. The method of claim 9, wherein said eukaryotic cell is selected from the group consisting of S. cerevisiae and H. sapiens.

11. The method of claim 9, wherein said biological process is metabolism.

12. The method of claim 10, wherein said eukaryotic cell is S. cerevisiae.

13. The method of claim 10, wherein said eukaryotic cell is H. sapiens.

14. The method of claim 1, wherein step (a) comprises determining a set of extreme pathways of said reaction network.

15. The method of claim 1, wherein step (a) further comprises constructing an in silico model of said reaction network to produce said set of systemic reaction pathways.

16. The method of claim 15, wherein said constructing an in silico model comprises determining the sequence of a genome containing open reading frames.

17. The method of claim 16, wherein said constructing an in silico model comprises determining open reading frames of a sequence of a genome for identifying the function of said open reading frames.

18. The method of claim 17, wherein said constructing an in silico model comprises assigning biochemical functions to open reading frames of a genome, whereby a biochemical function of an open reading frame is included in said set of systemic reaction pathways of said in silico model.

19. The method of claim 1, wherein said set of phenomenological reaction pathways in step (b) is provided by a process comprising analyzing gene expression data to produce said set of phenomenological reaction pathways.

20. The method of claim 19, wherein said gene expression data is obtained by determining said gene expression.

21. The method of claim 1, wherein said set of phenomenological reaction pathways in step (b) is provided by a process comprising analyzing protein expression data to produce said set of phenomenological reaction pathways.

22. The method of claim 21, wherein said protein expression data is obtained by determining said protein expression.

23. The method of claim 1, wherein said set of phenomenological reaction pathways in step (b) is provided by a process comprising analyzing metabolite production data to produce said set of phenomenological reaction pathways.

24. The method of claim 23, wherein said metabolite production data is obtained by determining said metabolite production.

25. The method of claim 1, wherein said set of phenomenological reaction pathways in step (b) is provided by a process comprising analyzing reaction usage data to produce said set of phenomenological reaction pathways.

26. The method of claim 25, wherein said reaction usage data is obtained by determining said reaction usage.

27. The method of any of claims 19-26 wherein said data is analyzed using a method selected from the group consisting of clustering analysis, singular value decomposition, principal component analysis and multivariable time series analysis.

28. The method of claim 27, wherein said data is analyzed using singular value decomposition.

29. The method of claim 27, wherein said data is analyzed using clustering analysis.

30. The method of claim 27, wherein said data is analyzed using principal component analysis.

31. The method of claim 27, wherein said data is analyzed using multivariable time series analysis.