System and method for scientific information knowledge management

• US 8,275,737 B2
• Filed: 12/18/2006
• Issued: 09/25/2012
• Est. Priority Date: 12/16/2005
• Status: Active Grant

• Current Assignee: Illumina Incorporated
• Original Assignee: NextBio
• Inventors: Kupershmidt, Ilya, Su, Qiaojuan Jane, Andry, Francois
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): KENNEDY, ADRIAN L
• Application Number:
  US11/641,539
• Publication Number:
  US 20070162411A1
• Time in Patent Office: 2,108 Days
• Field of Search: None
• US Class Current: 706/60
• CPC Class Codes: G06F 16/21 Design, administration or maintenance of databases
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation

Abstract

The present invention relates to methods, systems and apparatus for capturing, integrating, organizing, navigating and querying large-scale data from high-throughput biological and chemical assay platforms. It provides a highly efficient meta-analysis infrastructure for performing research queries across a large number of studies and experiments from different biological and chemical assays, data types and organisms, as well as systems to build and add to such an infrastructure.

Claims

1. A computer-implemented method of providing data to a knowledge base of scientific information, the knowledge base including a plurality of pre-existing feature sets and pre-existing feature groups, the pre-existing feature sets each including a list of features and associated statistics indicating one or more of:

differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems, and the pre-existing feature groups each including a list of features related by structure or function, wherein the features are biological or chemical entities or units of biological or chemical information, the method comprising;

(a) correlating by one or more processors of a computer system an input feature set against a plurality or all of the pre-existing feature sets in the knowledge base, the input feature set including a list of features and associated statistics indicating one or more of;

differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems;

(b) correlating by one or more processors of the computer system the input feature set against one or more pre-existing feature groups in the knowledge base;

(c) storing on one or more storage devices correlation information generated in (a) and (b) for use in responding to queries involving feature groups or feature sets; and

prior to (a), mapping by one or more processors of the computer system each feature in the input feature set to one or more mapping identifiers in the knowledge base, wherein each mapping identifier represents a globally unique feature in the knowledge base.

2. The method of claim 1, wherein the features comprise genes of an organism.

3. The method of claim 1, wherein the features comprise chemical compounds and indications of responses are effect(s) of chemical compounds on biological systems.

4. The method of claim 1, wherein the correlating in (b) comprises performing a rank-based statistical algorithm.

5. The method of claim 1, wherein the correlating in (c) comprises performing a rank-based statistical algorithm.

6. The method of claim 1, wherein the features comprise SNPs.

7. The method of claim 1, wherein mapping each feature in the input feature set comprises mapping one or more feature identifiers associated with each feature in the input feature set to one or more mapping identifiers.

8. The method of claim 7, wherein at least some features are mapped based on established relationships between features and feature identifiers.

9. The method of claim 1, wherein at least some features are mapped based on genomic coordinates of the features.

10. The method of claim 1, wherein at least some features are mapped based on an indirect association of a feature to one or more pre-existing features in the knowledge base.

11. The method of claim 1, further comprising tagging the input feature set with terms in the knowledge base that are related to the input feature set.

12. The method of claim 11, wherein tagging comprises automatically associating terms in the knowledge base to the input feature set by one or more processors of the computer system.

13. The method of claim 1, further comprising, prior to (a), ranking the features in the input feature set by one or more processors of the computer system.

18. The method of claim 1 wherein the feature groups include at least one group of genes and/or proteins that all belong to the same signaling pathway.

19. The method of claim 1 wherein the feature groups provide collections of features having structural and/or functional characteristics in common without associated statistics.

36. The method of claim of claim 1, wherein the features of the input feature set and one or more of the pre-existing feature sets are units of genetic or phenotypic information.

14. A computer program product comprising a machine readable non-transitory medium on which is provided program instructions for providing data to a knowledge base of scientific information, the knowledge base including a plurality of pre-existing feature sets and pre-existing feature groups, the pre-existing feature sets each including a list of features and associated statistics indicating one or more of:

differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems, wherein the features are biological or chemical entities or units of biological or chemical information, the program instructions comprising;

(a) code for receiving an input feature set, the input feature set including a list of features and associated statistics indicating one or more of;

differential expression, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems;

(b) code for mapping each feature in the input feature set to one or more mapping identifiers in the knowledge base, wherein each mapping identifier represents a globally unique feature in the knowledge base;

(c) code for correlating the input feature set against a plurality or all of the pre-existing feature sets in the knowledge base;

(d) code for correlating the input feature set against one or more pre-existing feature groups in the knowledge base, wherein the feature groups provide collections of features having structural and/or functional characteristics in common; and

(e) code for storing correlation information generated in (c) and (d) for use in responding to queries involving feature groups or feature sets.

15. The computer program product of claim 14, wherein the code correlating in (c) or (d) comprises code for a rank-based statistical algorithm.

16. The computer program product of claim 14, further comprising code for tagging the input feature set with terms in the knowledge base that are related to the feature set.

17. The computer program product of claim 14, further comprising code for ranking the features in the input feature set.

38. The computer program product of claim of claim 14, wherein the features of the input feature set and one or more of the pre-existing feature sets are units of genetic or phenotypic information.

20. A computer-implemented method of providing data to a knowledge base of scientific information, the knowledge base including a plurality of pre-existing feature sets and pre-existing feature groups, the pre-existing feature sets each including a list of features and information about one or more of:

differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems, and each feature group providing a list of related features without associated statistics, wherein the features are biological or chemical entities or units of biological or chemical information, the method comprising;

(a) correlating by one or more processors of a computer system an input feature set against a plurality pre-existing feature sets in the knowledge base, the input feature set including a list of features and information about one or more of;

differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems;

(b) correlating by one or more processors of a computer system the input feature set against a plurality of pre-existing feature groups in the knowledge base, and

(c) storing on one or more storage devices correlation information generated in (a) and (b) for use in responding to queries involving feature groups or feature sets.

21. The method of claim 20, wherein the input feature set includes gene expression profile information of a patient.

22. The method of claim 20, wherein the features in the input feature set are SNPs.

23. The method of claim 20, wherein the features in the input feature set are chemical compounds.

24. The method of claim 20, wherein the features in the input feature set are proteins.

25. The method of claim 20, wherein the features in the input feature set are genes.

26. The method of claim 20, wherein (b) comprises correlating the input feature set to a feature group having gene features.

27. The method of claim 20, wherein at least one of (b) and (c) comprises performing a rank-based statistical algorithm.

37. The method of claim of claim 20, wherein the features of the input feature set and one or more of the pre-existing feature sets are units of genetic or phenotypic information.

28. A computer program product comprising a machine readable non-transitory medium on which is provided program instructions for providing data to a knowledge base of scientific information, the knowledge base including a plurality of pre-existing feature sets and pre-existing feature groups, the pre-existing feature sets each including a list of features and information about one or more of:

differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems, and each feature group providing a list of related features without associated statistics, wherein the features are biological or chemical entities or units of biological or chemical information, the program instructions comprising;

(a) code for correlating an input feature set against a plurality pre-existing feature sets in the knowledge base, the input feature set including a list of features and information about one or more of;

differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems;

(b) code for correlating the input feature set against a plurality of pre-existing feature groups in the knowledge base, and

(c) code for storing correlation information generated in (a) and (b) for use in responding to queries involving feature groups or feature sets.

29. The computer program product of claim 28, wherein the input feature set includes gene expression profile information of a patient.

30. The computer program product of claim 28, wherein the features in the input feature set are SNPs.

31. The computer program product of claim 28, wherein the features in the input feature set are chemical compounds.

32. The computer program product of claim 28, wherein the features in the input feature set are proteins.

33. The computer program product of claim 28, wherein the features in the input feature set are genes.

34. The computer program product of claim 28, wherein (b) comprises code for correlating the input feature set to a feature group having gene features.

35. The computer program product of claim 28, wherein at least one of (b) and (c) comprises code for performing a rank-based statistical algorithm.

39. The computer program product of claim of claim 29, wherein the features of the input feature set and one or more of the pre-existing feature sets are units of genetic or phenotypic information.