e-journal

Outlier Analysis and Top Scoring Pair for Integrated Data Analysis and Biomarker Discovery

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Abstract—Pathway deregulation has been identified as a key driver of carcinogenesis, with proteins in signaling pathways serving as primary targets for drug development. Deregulation can be driven by a number of molecular events, including gene mutation, epigenetic changes in gene promoters, verexpression, and gene amplifications or deletions. We demonstrate a novel approach that identifies pathways of interest by integrating outlier analysis within and across molecular data types with gene set analysis. We use the results to seed the top-scoring pair algorithm to identify robust biomarkers associated with pathway deregulation. We demonstrate this methodology on pediatric acute myeloid leukemia (AML) data. We develop a biomarker in primary AML tumors, demonstrate robustness with an independent primary tumor data set, and show that the identified biomarkers also function well in relapsed pediatric AML tumors.
Index Terms—Genomics, data integration, statistical analysis, biomarker

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Informasi Detail

Judul Seri

IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS

No. Panggil

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Penerbit

New York : IEEE., 2014

Deskripsi Fisik

IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. 11, NO. 3, MAY/JUNE 2014

Bahasa

English

ISBN/ISSN

1545-5963

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

VOL. 11, NO. 3, MAY/JUNE 2014

Subjek

BIOLOGI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Yuli/Agus

Versi lain/terkait

Lampiran Berkas

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