Sequence-centric scientific information management

1. A computer-implemented method of integrating a sequence-centric feature set into a knowledge base on a storage device comprising sequence-centric feature sets and gene-centric feature sets, the method comprising:

receiving by one or more processors of a computer system a sequence-centric feature set provided by a user, wherein the sequence-centric feature set comprises a plurality of sequence regions and associated statistics, wherein the plurality of sequence regions comprise one or more SNPs, methylated regions, or genomic variations;

mapping by the one or more processors of the computer system the plurality of sequence regions to genes within the knowledge base to provide a set of mapped genes for the received sequence-centric feature set, wherein the plurality of sequence regions and the genes within the knowledge base are related by genomic coordinate, physical proximity, haplotype, function, or phenotype;

mapping by the one or more processors of the computer system the plurality of sequence regions to other sequence regions within the knowledge base to provide a set of mapped sequence regions for the received sequence-centric feature set, wherein the plurality of sequence regions and the genes within the knowledge base are related by genomic coordinate, physical proximity, haplotype, function, or phenotype;

providing ranks of the set of mapped sequence regions in the received sequence-centric feature set and in other sequence-centric feature sets in the knowledge base, wherein the other sequence-centric feature sets comprise a plurality of sequence regions and associated statistics;

performing by the one or more processors of the computer system iterative rank based processes to calculate sequence-sequence scores indicating correlations between the received sequence-centric feature set and other sequence-centric feature sets in the knowledge base using the ranks of the set of mapped sequence regions;

providing ranks of the set of mapped genes in the received sequence-centric feature set and in the gene-centric feature sets in the knowledge base, wherein the gene-centric feature sets comprise one or more of genes ranked by activity and microarray-based gene expression data;

performing by one or more processors of the computer system iterative rank based processes to calculate sequence-gene scores indicating the correlations between the received sequence-centric feature set and the gene-centric feature sets using the ranks of the set of mapped genes;

storing the received sequence-centric feature set, the sequence-sequence scores, and the sequence-gene scores on the storage device;

receiving a query sequence region or a query gene as a query input; and

displaying information based on one or more sequence-sequence scores or one or more sequence-gene scores that correspond to the query sequence region or the query gene.

2. The computer-implemented method of claim 1 , wherein the gene-centric feature sets comprise microarray expression data and the plurality of sequence regions comprises SNPs.

3. The computer-implemented method of claim 1 , wherein the gene-centric feature sets comprise microarray expression data and the plurality of sequence regions comprises methylated regions.

4. The computer-implemented method of claim 1 , wherein the gene-centric feature sets comprise microarray expression data and wherein the plurality of sequence regions comprises genomic variations.

5. The computer-implemented method of claim 1 , wherein the gene-centric features sets comprise microarray expression data and wherein at last one sequence-centric feature set in the knowledge base comprises epigenetic profiling data.

6. The computer-implemented method of claim 1 , wherein sequence-sequence scores indicating a correlation between a received sequence-centric features set to thousands of other sequence-centric feature sets in the knowledge base are calculated.

7. The computer-implemented method of claim 1 , wherein sequence-gene scores indicating correlations between a received sequence-centric feature set to thousands ofgene-centric feature sets in the knowledge base are calculated.

8. The computer-implemented method of claim 1 , wherein at least one of the plurality of sequence regions is mapped to a gene based on being within the gene, overlapping the gene, being within a certain proximity of the gene, or covering the gene.

9. The computer-implemented method of claim 1 , wherein at least one of the plurality of sequence regions does not overlap with any gene in the knowledge base.

10. The computer-implemented method of claim 1 , further comprising displaying on a screen a graphical representation of a sequence region mapping.

11. A computer program product comprising a machine readable non-transitory medium on which is provided program instructions for integrating a sequence-centric feature set into a knowledge based on a storage device comprising sequence-centric feature sets and gene-centric feature sets, the program instructions comprising:

code for receiving a sequence-centric feature set provided by a user, wherein the sequence-centric feature set comprises a plurality of sequence regions and associated statistics, wherein the plurality of sequence regions comprise one or more SNPs, methylated regions, or genomic variations;

code for mapping the plurality of sequence regions to genes within the knowledge base to provide a set of mapped genes for the received sequence-centric feature set, wherein the plurality of sequence regions and the genes within the knowledge base are related by genomic coordinate, physical proximity, haplotype, function, or phenotype;

code for mapping the plurality of sequence regions to other sequence regions within the knowledge base to provide a set of mapped sequence regions for the received sequence-centric feature set, wherein the plurality of sequence regions and the genes within the knowledge base are related by genomic coordinate, physical proximity, haplotype, function, or phenotype;

code for providing ranks of the set of mapped sequence regions in the received sequence-centric feature set and in other sequence-centric feature sets in the knowledge base, wherein the other sequence-centric feature sets comprise a plurality of sequence regions and associated statistics;

code for performing iterative rank based processes to calculate sequence-sequence scores indicating correlations between the received sequence-centric feature set and other sequence-centric feature sets in the knowledge base using the ranks of the set of mapped sequence regions;

code for providing ranks of the set of mapped genes in the received sequence-centric feature set and in the gene-centric feature sets in the knowledge base, wherein the gene-centric feature sets comprise one or more of genes ranked by activity and microarray-based gene expression data;

code for performing iterative rank based processes to calculate sequence-gene scores indicating the correlations between the received sequence-centric feature set and the gene-centric feature sets using the ranks of the set of mapped genes;

code for storing the received sequence-centric feature set, the sequence-sequence scores, and the sequence-gene scores on the storage device;

code for receiving a query sequence region or a query gene as a query input; and

code for displaying information based on one or more sequence-sequence scores or one or more sequence-gene scores that correspond to the query sequence region or the query gene.

12. The computer program product of claim 11 , wherein the gene-centric feature sets comprise microarray expression data and the plurality of sequence regions comprises SNPs.

13. The computer program product of claim 11 , wherein the gene-centric feature sets comprise microarray expression data and the plurality of sequence regions comprises methylated regions.

14. The computer program product of claim 11 , wherein the gene-centric feature sets comprise microarray expression data and wherein the plurality of sequence regions comprises genomic variations.

15. The computer program product of claim 11 , wherein the gene-centric feature sets comprise microarray expression data and wherein at least one sequence-centric feature set in the knowledge base comprises epigenetic profiling data.

16. The computer program product of claim 11 , wherein the program instructions comprise code for calculating sequence-sequence scores indicating a correlation between a received sequence-centric feature set to thousands of other sequence-centric feature sets in the knowledge base.

17. The computer program product of claim 11 , wherein the program instructions comprise code for calculating sequence-gene scores indicating correlations between a received sequence-centric feature set to thousands of gene-centric feature sets in the knowledge base.

18. The computer program product of claim 11 , wherein the program instructions comprise code for mapping at least one of the plurality of sequence regions to a gene based on being within the gene, overlapping the gene, being within a certain proximity of the gene, or covering the gene.

19. The computer program product of claim 11 , wherein the program instructions comprise code for displaying on a screen a graphical representation of a sequence region mapping.

20. An apparatus for integrating a sequence-centric feature set into a knowledge base comprising sequence-centric feature sets and gene-centric feature sets, comprising:

a memory for storing a knowledge base of scientific information; and

one or more processors in communication with the memory and configured to:

receive sequence-centric feature set provided by a user, wherein the sequence-centric feature set comprises a plurality of sequence regions and associated statistics, wherein the plurality of sequence regions comprise one or more SNPs, methylated regions, or genomic variations;

map the plurality of sequence regions to genes within the knowledge base to provide a set of mapped genes for the received sequence-centric feature set, wherein the plurality of sequence regions and the genes within the knowledge base are related by genomic coordinate, physical proximity, haplotype, function, or phenotype;

map the plurality of sequence regions to other sequence regions within the knowledge base to provide a set of mapped sequence regions for the received sequence-centric feature set, wherein the plurality of sequence regions and the other sequence regions within the knowledge base are related by genomic coordinate, physical proximity, haplotype, function, or phenotype;

provide ranks of the set of mapped sequence regions in the received sequence-centric feature set and in other sequence-centric feature sets in the knowledge base, wherein the other sequence-centric feature sets comprise a plurality of sequence regions and associated statistics;

perform iterative rank based processes to calculate sequence-sequence scores indicating correlations between the received sequence-centric feature set and other sequence-centric feature sets in the knowledge base using the ranks of the set of mapped sequence regions;

provide ranks of the set of mapped genes in the received sequence-centric feature set and in the gene-centric feature sets in the knowledge base, wherein the gene-centric feature sets comprise one or more of genes ranked by activity and microarray-based gene expression data;

perform iterative rank based processes to calculate sequence-gene scores indicating the correlations between the received sequence-centric feature set and the gene-centric feature sets using the ranks of the set of mapped genes;

store the received sequence-centric feature set, the sequence-sequence scores, and the sequence-gene scores on the memory;

receive a query sequence region or a query gene as a query input; and

display information based on one or more sequence-sequence scores or one or more sequence-gene scores that correspond to the query sequence region or the query gene.