Directional expression-based scientific information knowledge management

• US 8,364,665 B2
• Filed: 09/19/2008
• Issued: 01/29/2013
• Est. Priority Date: 12/16/2005
• Status: Active Grant

• Current Assignee: Illumina Incorporated
• Original Assignee: NextBio
• Inventors: Su, Qiaojuan Jane, Kupershmidt, Ilya
• Primary Examiner(s): NGUYEN, PHONG H
• Application Number:
  US12/234,435
• Publication Number:
  US 20090049019A1
• Time in Patent Office: 1,593 Days
• Field of Search: 707/603, 707/723, 707/758, 707/805, 707/954, 705/45, 705/924
• US Class Current: 707/723
• 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. In particular, aspects of the invention relate to integrating, organizing, navigating and querying “directional” data, such as gene expression profiles.

Claims

1. A computer-implemented method of integrating expression-based data into a knowledge base stored on one or more storage devices, knowledge base comprising at least one pre-existing bi-directional feature set, each bi-directional feature set comprising a list of a plurality of features and, for at least some of the listed features, up or down expression information relative to a control sample or normal state, the computer-implemented method comprising:

receiving a bi-directional input feature set comprising a list of a plurality of features and, for at least some of the listed features, up or down regulation expression information of the feature relative to a control sample or normal state; and

automatically correlating by one or more processors of a computer system the input feature set with a plurality or all other pre-existing bi-directional feature sets;

wherein automatically correlating the input feature set with a bi-directional pre-existing feature set comprises determining by the one or more processors multiple individual correlation scores and, from the multiple individual correlation scores, determining by the one or more processors an overall correlation score and a correlation direction,

wherein an up regulation expression information indicates a positive correlation score between the input feature set and the pre-existing feature set, a down regulation expression information indicates a negative correlation score between the input feature set and the pre-existing feature set, and

wherein the input feature set and the pre-existing feature sets are selected from the group consisting of differential expression of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems.

2. The computer-implemented method of claim 1 wherein the multiple individual correlation scores comprise one or more positive correlation scores and one or more negative correlation scores, wherein a positive correlation score indicates a degree of positive correlation between the input feature set and the pre-existing feature set and a negative correlation score indicates a degree of negative correlation between the input feature set and the pre-existing feature set.

3. The computer-implemented method of claim 2 wherein determining a correlation direction comprises comparing the one or more positive correlation scores with the one or more negative correlation scores.

4. The computer-implemented method of claim 2 wherein determining the one or more positive correlation scores comprises correlating the up-regulation expression information of the input feature set with the up-regulation expression information of the pre-existing feature set and/or correlating the down-regulation expression information of the input feature set with the down-regulation expression information of the pre-existing feature set.

5. The computer-implemented method of claim 2 wherein determining the one or more negative correlation scores comprises correlating the up-regulation expression information of the input feature set with the down-regulation expression information of the pre-existing feature set and/or correlating the down-regulation expression information of the input feature set with the up-regulation expression information of the pre-existing feature set.

6. The computer-implemented method of claim 1 wherein determining multiple individual correlation scores comprises performing rank based statistical algorithms.

7. The computer-implemented method of claim 1 further comprising storing on the one or more storage devices at least the overall correlation score and correlation directions for use in replying to user queries involving a feature set.

8. The computer-implemented method of claim 1 wherein the knowledge base comprises one or more non-directional feature sets and the input feature set is automatically correlated to a plurality or all of the non-directional feature sets.

9. The computer-implemented method of claim 8 wherein automatically correlating the input feature set to a non-directional feature set comprises determining multiple individual correlation scores and from the multiple individual correlation scores, selecting the score that indicates the best correlation of the input feature set with the non-directional feature set.

10. The computer-implemented method of claim 9 wherein determining the multiple individual correlation scores comprises correlating the up-regulation expression information of the input feature set with the non-directional feature set and correlating the down-regulation expression information of input feature set with the non-directional feature set.

11. The computer-implemented method of claim 1, wherein the features comprise genes of an organism, SNPs, or chemical compounds.

12. The computer-implemented method of claim 1, wherein at least one of the bi-directional feature sets comprises information about the feature expression signature of a disease.

13. The computer-implemented method of claim 1, wherein at least one of the bi-directional feature sets comprises information about feature expression response to a stimulus or compound.

17. The computer-implemented method of claim 1, wherein the input bi-directional feature set is a gene expression profile.

14. A computer implemented method of conducting a query in a knowledge base of chemical and/or biological information comprising a plurality of feature sets, each feature set comprising a list of a plurality of chemical or biological features and associated statistical information, the method comprising:

receiving a query identifying at least one feature set comprising up and down gene regulation expression information, wherein the query is received from a user input to a computer system;

using precomputed correlation scores between the at least one identified feature set and other content in the knowledge base to determine feature set rankings in reply to said query; and

presenting the user with a ranked list of feature sets as determined by the precomputed correlation scores, and, for at least some of the feature sets in the ranked list, an indication of whether the correlation of that feature set with the identified feature set is positive or negative; and

wherein an UP gene regulation expression information indicates a positive correlation score between the identified feature set and the feature set in the knowledge base, a down gene regulation expression information indicates a negative correlation score between the identified feature set and the feature set in the knowledge base, and

wherein the identified feature set and the feature set in the knowledge base are selected from the group consisting of differential expression of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems.

15. The computer implemented method of claim 14 further comprising presenting the user with information about the correlation between each of the up and down regulation expression information of the identified feature set and each of the up and down feature regulation expression information of at least one listed feature set.

18. The computer implemented method of claim 14 wherein the ranked list of features is outputted to a display of the computer system.

16. A method of providing data to a knowledge base of scientific information, the method comprising:

(a) receiving raw data from one or more samples, wherein the raw data includes information on one or more features with indications of the magnitude and direction of change of those features, relative to a normal state or control sample, in response to a treatment or stimulus;

(b) producing an input feature set from the raw data by removing or reorganizing information about at least some less relevant features;

(c) correlating by one or more processors of a computer system the input feature set against a plurality or all of the pre-existing feature sets in the knowledge base;

(d) correlating by one or more processors of a computer system the input feature set against one or more feature groups in the knowledge base, wherein the feature groups provide collections of features having structural and/or functional characteristics in common; and

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

wherein the features are selected from the group consisting of biological entities, chemical entities, biological information and chemical information, and

wherein the input feature set and the pre-existing feature sets are selected from the group consisting of differential expression of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems.