Automated pathway recognition system

• US 6,876,930 B2
• Filed: 03/04/2002
• Issued: 04/05/2005
• Est. Priority Date: 07/30/1999
• Status: Expired due to Fees

• Current Assignee: AGY Therapeutics, Inc.
• Original Assignee: AGY Therapeutics, Inc.
• Inventors: Murray, Joseph, Hendrix, Donna, Chin, Daniel J
• Primary Examiner(s): Horlick, Kenneth R.
• Assistant Examiner(s): Kim, Young J.
• Application Number:
  US10/090,698
• Publication Number:
  US 20020168664A1
• Time in Patent Office: 1,128 Days
• Field of Search: 702/19, 702/27, 435/6, 536/23.1, 536/24.3, 706/45, 706/47, 712/200
• US Class Current: 702/19
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• 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 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search
• 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 40/20 Supervised data analysis
• CPC Class Codes: G16B 40/30 Unsupervised data analysis
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/20 Heterogeneous data integration
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99937 Sorting

Abstract

There is a pressing need for computer-implemented tools that can summarize and present the enormous amounts of public literature to facilitate analysis of gene expression data. The present invention provides techniques and systems for efficiently integrating public literature regarding gene function with data from gene expression profiling experiments. Information from literature databases relating to a particular set of DNA sequences of known expression pattern is retrieved, processed, cross-referenced and viewed to provide further information about a particular DNA sequence to facilitate its identification as a candidate gene.

Claims

1. A computer-implemented method of identifying candidate genes from a plurality of DNA sequences, the method comprising:

obtaining gene expression profile data for a plurality of DNA sequences, wherein the gene expression profile data describe behavioral patterns of gene expression;

identifying a group of DNA sequences for further analysis;

using information extraction algorithms to retrieve and extract pathway information from a database related to the group of DNA sequences;

cross-referencing said pathway information to said DNA sequences;

ranking the pathway information based on a ranking of a publication in a citation index;

viewing said cross-referenced information and said ranking; and

,

wherein viewing the cross-referenced information and said ranking facilitates the identification of candidate genes.

2. The computer-implemented method of claim 1, wherein the pathway information is stored in a database.

3. The computer-implemented method of claim 2, wherein the cross-referenced information is stored in a database.

4. The computer-implemented method of claim 1, wherein the cross-referenced information is viewed as a directed graph.

5. The computer-implemented method of claim 1, wherein identifying a group of DNA sequences further comprises clustering the gene expression profile data to form clusters.

6. The computer-implemented method of claim 5, wherein clustering is unsupervised clustering.

7. The computer-implemented method of claim 5, wherein clustering is supervised clustering.

8. The computer-implemented method of claim 5, wherein clustering is a combination of supervised and unsupervised clustering.

9. The computer-implemented method of claim 5, wherein the group of DNA sequences represents a cluster.

10. The computer-implemented method of claim 1, wherein the gene expression profile data is derived from microarray experiments.

11. The computer-implemented method of claim 1, wherein the information extraction is performed using natural language processing algorithms.

12. The computer-implemented method of claim 11, wherein the natural language processing algorithms include template filling or Hidden Markov-Models.

13. The computer-implemented method of claim 11, wherein an information extraction algorithm utilizes a text comparison algorithm.

14. The computer-implemented method of claim 1, wherein the information is extracted from one or more literature databases from the group consisting of MEDLINE, USPTO patent published patent database, USPTO issued patent database, the WIPO patent database, and the KEGG, MIPS and OMIM database.

15. A data processing system for identifying candidate genes from a plurality of DNA sequences of known expression pattern, comprising:

a processor; and

,

a memory coupled to the processor, wherein the memory has instructions for execution by the processor, the instructions comprising;

instructions for accessing and extracting pathway information from a literature database comprising a biomedical publication;

instructions for cross-referencing said pathway information to said candidate genes;

instructions for ranking the biomedical publication and instructions to assign a ranking score to the pathway information extracted from a biomedical publication based on the ranking of the biomedical publication; and

,

instructions for viewing said cross-referenced information and said ranking score.

16. The data processing system of claim 15, wherein said executable instructions further comprise instructions for storing said pathway information and said cross-referenced information in a database.

17. A data processing system for identifying candidate genes from a plurality of DNA sequences, comprising:

a processor; and

,

a memory coupled to the processor, wherein the memory has instructions for execution by the processor, the instructions comprising;

instructions for clustering the plurality of DNA sequences based on the behavioral patterns of the DNA sequences as described by gene expression profile data;

instructions for accessing and extracting pathway information from a literature database comprising a biomedical publication;

instructions for cross-referencing said pathway information to said candidate genes;

instructions for ranking the biomedical publication and instructions to assign a ranking score to the pathway information extracted from a biomedical publication based on the ranking of the biomedical publication; and

,

instructions for viewing said cross-referenced information and said ranking score.