Method, system and computer software for providing genomic ontological data

• US 20040126840A1
• Filed: 12/23/2002
• Published: 07/01/2004
• Est. Priority Date: 12/23/2002
• Status: Abandoned Application

• Current Assignee: Affymetrix, Inc. (Thermo Fisher Scientific Incorporated)
• Original Assignee: A Corporation Organized Under The LAWS of Delaware, Affymetrix, Inc. (Thermo Fisher Scientific Incorporated)
• Inventors: Sun, Shaw, Cheng, Jill, Siani-Rose, Michael A.
• Application Number:
  US10/328,872
• Publication Number:
  US 20040126840A1
• Time in Patent Office: Days
• US Class Current: 435/69.1
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/20 Polymerase chain reaction [PCR]; Primer or probe design; Probe optimisation
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/10 Ontologies; Annotations
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 69/329 in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 Network security protocols

Abstract

A genomic web portal provides an ontological map having nodes and edges. The computer-implemented portal system makes use of information correlating one or more probe-set identifiers with a plurality of ontological categories or terms, thereby generating probe-set identifier association data. The probe-set identifiers are associated with one or more probe sets of one or more probe arrays that may be involved in microarray experiments. The system correlates the probe-set identifier association data with graph traversal data and displays an ontological map based on this correlation.

Claims

1. A genomic web portal for providing biological information constructed and arranged to execute a computer-implemented method for providing an ontological map having nodes and edges, wherein the method comprises the acts of:

correlating one or more probe-set identifiers associated with one or more probe sets of one or more probe arrays with a plurality of ontological categories or terms,.thereby generating probe-set identifier association data;

correlating the probe-set identifier association data with graph traversal data including associations among the nodes and edges; and

displaying the ontological map based, at least in part, on the correlation of the probe-set identifier association data and the graph traversal data;

wherein at least one of the probe arrays is constructed and arranged to detect or measure any one or any combination of biological, biochemical or genetic metrics including gene expression, genotype, SNP, haplotype, or targets including antibodies, cell membrane receptors, monoclonal antibodies and antisera reactive with specific antigenic determinants, drugs, oligonucleotides, nucleic acids, peptides, proteins, cofactors, lectins, sugars, polysaccharides, cells, cellular membranes, or organelles.

2. A genomic data processor constructed and arranged to provide an ontological map having edges and a plurality of nodes including a root node, comprising:

a map creator constructed and arranged to correlate probe-set identifier association data with graph traversal data, wherein the probe-set identifier association data includes correlations of one or more probe-set identifiers associated with one or more probe sets of one or more probe arrays with a plurality of ontological categories or terms, and wherein the graph traversal data includes associations among the nodes and edges; and

an output provider constructed and arranged to enable display of the ontological map based, at least in part, on the correlation of the probe-set identifier association data and the graph traversal data.

3. The processor of claim 2, wherein:

the probe sets are constructed and arranged to detect one or more biological molecule.

4. The processor of claim 2, wherein:

the one or more probe arrays comprise synthesized probe arrays or spotted probe arrays.

5. The processor of claim 2, wherein:

at least one of the probe arrays is constructed and arranged to detect or measure any one or any combination of biological, biochemical or genetic metrics including gene expression, genotype, SNP, haplotype, or targets including antibodies, cell membrane receptors, monoclonal antibodies and antisera reactive with specific antigenic determinants, drugs, oligonucleotides, nucleic acids, peptides, proteins, cofactors, lectins, sugars, polysaccharides, cells, cellular membranes, or organelles.

6. The processor of claim 2, wherein:

at least one of the probe arrays is constructed and arranged to diagnose a disease or medical condition.

7. The processor of claim 2, wherein:

at least one of the probe arrays is a custom probe array.

8. The processor of claim 2, wherein:

at least one of the probe arrays includes a substrate material of glass, silicon, silica, optical fibers, beads, resins, gels, or microspheres.

9. The processor of claim 2, wherein:

the probe-set identifier association data includes a Boolean representation of presence or absence of functional relatedness.

10. The processor of claim 2, wherein:

the map creator further is constructed and arranged to correlate the one or more probe-set identifiers with the plurality of ontological categories or terms, thereby generating the probe-set identifier association data.

11. The processor of claim 2, wherein:

the probe-set identifier association data is predetermined and stored in one or more databases.

12. The processor of claim 2, wherein:

the probe-set identifier association data is stored in a local genomic and/or product database of a genomic web portal.

13. The processor of claim 2, wherein:

the graph traversal data includes categories or terms pertinent to biological process, molecular function, cellular component, or experimental terms.

14. The processor of claim 2, further comprising

a weight assigner constructed and arranged to assign one or more weights to the edges based at least in part on the distance of an edge from the root node.

15. The processor of claim 14, further comprising:

a weight calculator constructed and arranged to calculate a maximal path weight based at least in part on the one or more weights assigned to the edges and a path that contains a maximum number of edges connecting the one or more nodes to the root node.

16. The processor of claim 15, further comprising:

a path selector constructed and arranged to select one or more paths including a plurality of nodes and at least one edge;

a statistical processor constructed and arranged to generate a normalization factor based at least in part on the one or more weights assigned to the edges in the one or more selected paths and the maximal path weight; and

a similarity generator constructed and arranged to generate similarity data based at least in part on the one or more weights assigned to the one or more edges and the normalization factor.

17. The processor of claim 16, wherein:

the similarity data comprises pair-wise similarity data.

18. The processor of claim 17, wherein:

the similarity generator determines the pair-wise similarity data based, at least in part, on the length of partial path shared by two nodes.

19. The processor of claim 2, wherein:

the plurality of ontological categories or terms includes GO categories or terms.

20. The processor of claim 2, wherein:

the plurality of ontological categories or terms includes categories or terms related to genes, gene fragments, gene consensus sequences, proteins, peptides, or experimental terms.

21. A computer readable medium having software modules for performing a method comprising the acts of:

correlating probe-set identifier association data with graph traversal data, wherein the probe-set identifier association data includes correlations of one or more probe-set identifiers associated with one or more probe sets of one or more probe arrays with a plurality of ontological categories or terms, and wherein the graph traversal data includes associations among the nodes and edges; and

enabling display of the ontological map based, at least in part, on the correlation of the probe-set identifier association data and the graph traversal data.

22. The medium of claim 21, wherein:

at least one of the probe arrays is constructed and arranged to detect or measure any one or any combination of biological, biochemical or genetic metrics including gene expression, genotype, SNP, haplotype, or targets including antibodies, cell membrane receptors, monoclonal antibodies and antisera reactive with specific antigenic determinants, drugs, oligonucleotides, nucleic acids, peptides, proteins, cofactors, lectins, sugars, polysaccharides, cells, cellular membranes, or organelles.

23. The medium of claim 21, wherein:

the probe-set identifier association data includes a Boolean representation of presence or absence of functional relatedness.

24. The medium of claim 21, wherein the method further comprises the act of:

correlating the one or more probe-set identifiers with the plurality of categories or terms including ontological categories or terms, thereby generating the probe-set identifier association data.

25. The medium of claim 24, wherein:

the probe-set identifier association data is stored in a local genomic and/or product database of a genomic web portal.

26. The medium of claim 21, wherein:

the graph traversal data includes categories or terms pertinent to biological process, molecular function, cellular component, or experimental terms.

27. A genomic portal system for providing information related to one or more probe sets, the system comprising:

(1) an application server comprising

(a) an input manager constructed and arranged to receive from a user a selection of one or more probe-set identifiers associated with one or more probe sets, and

(b) a genomic data processor constructed and arranged to provide an ontological map having edges and a plurality of nodes and wherein one or more of the edges or nodes are associated with one or more of the user-selected probe-set identifiers; and

(2) a network server comprising an output manager constructed and arranged to provide the ontological map to the user.

28. The portal system of claim 27, wherein:

the application server and the network server are a same computer server.

29. The portal system of claim 27, wherein:

the output manager provides the ontological map to the user via the Internet.

30. A method comprising the acts of:

correlating probe-set identifier association data with graph traversal data, wherein the probe-set identifier association data includes correlations of one or more probe-set identifiers associated with one or more probe sets of one or more probe arrays with a plurality of ontological categories or terms, and wherein the graph traversal data includes associations among the nodes and edges; and

enabling display of an ontological map based, at least in part, on the correlation of the probe-set identifier association data and the graph traversal data.

31. The method of claim 30, wherein the method further comprises the act of:

correlating the one or more probe-set identifiers with the plurality of ontological categories or terms, thereby generating the probe-set identifier association data.

32. A graphical user interface generated by a method comprising the acts of:

correlating probe-set identifier association data with graph traversal data, wherein the probe-set identifier association data includes correlations of one or more probe-set identifiers associated with one or more probe sets of one or more probe arrays with a plurality of ontological categories or terms, and wherein the graph traversal data includes associations among the nodes and edges; and

enabling display of an ontological map based, at least in part, on the correlation of the probe-set identifier association data and the graph traversal data.

33. The graphical user interface of claim 32, wherein the method further comprises the act of:

correlating the one or more probe-set identifiers with the plurality of ontological categories or terms, thereby generating the probe-set identifier association data.

34. A system, comprising:

an input receiver constructed and arranged to receive graph traversal data, probe-set identifier association data, and one or more biological entity identifiers; and

a map creator constructed and arranged to generate one or more maps based at least in part on correlations of biological entity identifiers to the graph traversal data and the probe-set identifier association data.

35. The system of claim 34, wherein:

the one or more biological entity identifiers includes probe-set identifiers.

36. The system of claim 34, wherein:

the graph traversal data includes one or more edges, one or more nodes, and one or more paths, wherein each edge connects at least one node to one other node in the graph traversal data and each path is comprised of at least one or more edges.

37. The system of claim 36, wherein:

the probe-set identifier association data is based at least in part on the correlation of one or more probe-set identifiers with the one or more nodes.

38. The system of claim 34, wherein:

the one or more maps includes an ontological map.

39. The system of claim 34, further comprising:

an output provider constructed and arranged to enable the one or more maps for display in a graphical user interface.

40. A system comprising;

an input receiver constructed and arranged to receive a plurality of sets of data and one or more biological entity identifiers;

a map creator constructed and arranged to generate one or more maps based at least in part on a correlation of the biological entity identifiers to the plurality of sets of data;

a weight assigner constructed and arranged to assign one or more weights to one or more elements of at least one set of data comprising the plurality of sets of data;

a path selector constructed and arranged to select at least one set of elements, to which one or more weights are assigned, from the at least one set of data, based at least in part on a plurality of elements in the at least one set of data;

a weight calculator constructed and arranged to calculate a maximal weight based at least in part on the one or more weights assigned to the one or more elements comprising the set of elements selected by the path selector and the set of elements that contains the maximum number of the one or moreelements connecting one or more other elements in the at least one set of data;

a statistical processor constructed and arranged to generate a normalization factor based at least in part on the one or more weights assigned to the one or more elements comprising the set of elements selected by the path selector and the maximal weight;

a similarity generator constructed and arranged to generate similarity data based at least in part on the one or more weights assigned to the one or more elements comprising the set of elements selected by the path selector and the normalization factor; and

an output provider constructed and arranged to enable one or more of the one or more maps, the maximal path weight, the normalization factor, and the similarity data for display in a graphical user interface.

41. The system of claim 40, wherein:

the one or more biological entity identifiers includes a probe-set identifier.

42. The system of claim 41, wherein:

the plurality of sets of data includes probe-set identifier association data.

43. The system of claim 42, wherein:

the plurality of sets of data includes graph traversal data.

44. The system of claim 43, wherein:

the graph traversal data includes one or more edges, one or more nodes and one or more paths, wherein each edge connects at least one node to one other node in the graph traversal data and each path is comprised of at least one or more edges.

45. The system of claim 44, wherein:

the probe-set identifier association data is based at least in part on the correlation of one or more probe-set identifiers with one or more nodes.

46. A system, comprising:

means for receiving graph traversal data, probe-set identifier association data, and one or more biological entity identifiers including probe-set identifiers, wherein the graph traversal data includes one or mote edges, one or more nodes, and one or more paths, wherein each edge connects at least one node to one other node in the graph traversal data and each path is comprised of at least one or more edges;

means for generating one or more ontological maps based at least in part on correlations of biological entity identifiers to the graph traversal data and the probe-set identifier association data; and

means for enabling the one or more maps for display in a graphical user interface.

47. A system comprising;

means for generating one or more maps based at least in part on a correlation of one or more probe-set identifiers to probe-set identifier association data;

means for assigning one or more weights to one or more elements of at least one set of data comprising the probe-set identifier association data;

means for selecting at least one set of elements, to which one or more weights are assigned, from the at least one set of data, based at least in part on a plurality of elements in the at least one set of data;

means for calculating a maximal weight based at least in part on the one or more weights assigned to the one or more elements comprising the selected set of elements and the set of elements that contains the maximum number of the one or more elements connecting one or more other elements in the at least one set of data;

means for generating a normalization factor based at least in part on the one or more weights assigned to the one or more elements comprising the selected set of elements and the maximal weight;

means for generating similarity data based at least in part on the one or more weights assigned to the one or more elements comprising the selected set of elements and the normalization factor; and

means for enabling one or more of the one or more maps, the maximal path weight, the normalization factor, and the similarity data for display in a graphical user interface.