Disease-specific genomic analysis: identifying the signature of pathologic biology.

Disease-specific genomic analysis: identifying the signature of pathologic biology. Research Abstract Details 

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Disease-specific genomic analysis: identifying the signature of pathologic biology. Abstract Text:

Monica Nicolau,Robert Tibshirani,Anne-Lise ,Stefanie S Jeffrey,

MOTIVATION: Genomic high-throughput technology generates massive data, providing opportunities to understand countless facets of the functioning genome. It also raises profound issues in identifying data relevant to the biology being studied. RESULTS: We introduce a method for the analysis of pathologic biology that unravels the disease characteristics of high dimensional data. The method, disease-specific genomic analysis (DSGA), is intended to precede standard techniques like clustering or class prediction, and enhance their performance and ability to detect disease. DSGA measures the extent to which the disease deviates from a continuous range of normal phenotypes, and isolates the aberrant component of data. In several microarray cancer datasets, we show that DSGA outperforms standard methods. We then use DSGA to highlight a novel subdivision of an important class of genes in breast cancer, the estrogen receptor (ER) cluster. We also identify new markers distinguishing ductal and lobular breast cancers. Although our examples focus on microarrays, DSGA generalizes to any high dimensional genomic/proteomic data.

Disease-specific genomic analysis: identifying the signature of pathologic biology. Publishing Authors By Initials

M Nicolau,R Tibshirani,AL ,SS Jeffrey,

For similar biological factors: biological markers: tumor markers, biological research abstracts see: biological factors: biological markers: tumor markers, biological research

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Disease-specific genomic analysis: identifying the signature of pathologic biology. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: Bioinformatics (Oxford, England)

VOLUME: 23

Page Numbers: 957-65

Journal Abbreviation:

ISSN: 1460-2059

DAY: 3

MONTH: 02

YEAR: 2007

Disease-specific genomic analysis: identifying the signature of pathologic biology. Information

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LANGUAGE: eng

NlmUniqueID: 9808944

Disease-specific genomic analysis: identifying the signature of pathologic biology. Keywords Mesh Terms:

KEYWORDS: Tumor Markers, Biological

MESH TERMS: genetics

Chemical & Substance for Abstract: Disease-specific genomic analysis: identifying the signature of pathologic biology. Information

Substance Name: Tumor Markers, Biological

Registry Number: 0

Grant and Affiliation Information for Disease-specific genomic analysis: identifying the signature of pathologic biology.

AFFILIATION: Department of Surgery, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.

Country: England

AGENCY: United States NHLBI

GRANT: N01-HV-28183

ACRONYM: HV

MEDLINETA: Bioinformatics

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