This article is part of the supplement: The 2010 International Conference on Bioinformatics and Computational Biology (BIOCOMP 2010): Genomics

Open Access Research article

Maximizing biomarker discovery by minimizing gene signatures

Chang Chang1, Junwei Wang1, Chen Zhao1, Jennifer Fostel2, Weida Tong3, Pierre R Bushel4, Youping Deng5, Lajos Pusztai6, W Fraser Symmans6 and Tieliu Shi1*

Author Affiliations

1 The Center for Bioinformatics and the Institute of Biomedical Sciences, School of Life Science, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China

2 SRA Global Health Sector/NIEHS, Research Triangle Park, NC, 27709, USA

3 National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Road, Jefferson, AK 72079, USA

4 Biostatistics Branch, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA

5 Rush University Cancer Center, Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA

6 Department of Breast Medical Oncology and Department of Pathology, The University of Texas M. D. Anderson Cancer Center, PO Box 301439, Houston, TX 77230, USA

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BMC Genomics 2011, 12(Suppl 5):S6  doi:10.1186/1471-2164-12-S5-S6

Published: 23 December 2011

Additional files

Additional file 1:

Endpoint D probe level overlap matrix.

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Additional file 2:

Endpoint E probe level overlap matrix.

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Additional file 3:

Top probes (Similarity Analysis).

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Additional file 4:

Top 500 probes' differentially expressed probes analysis.

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Additional file 5:

Further analyses at probe level.

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Additional file 6:

Internal and external validation for endpoint E.

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Additional file 7:

Heatmaps for original models and swap models on training dataset and validation dataset.

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Additional file 8:

Top genes (Similarity Analysis).

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Additional file 9:

GO term enrichment for overlapping genes (Similarity Analysis).

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Additional file 10:

All pairs shortest path matrix counting for features before and after MFS.

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Additional file 11:

Datasets.

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Additional file 12:

All pCR models as the input of CAS_BR_D_4.

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Additional file 13:

All ER models as the input of CAS_BR_E_15.

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Additional file 14:

Bayesian-Decision Tree Method.

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Additional file 15:

Development of the Local Network Model (LNM) tool.

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Additional file 16:

MFS inputs.

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Additional file 17:

Features of the CAS_BR_D_4 and CAS_BR_E_15.

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