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atBioNet– an integrated network analysis tool for genomics and biomarker discovery

Yijun Ding1, Minjun Chen2, Zhichao Liu1, Don Ding1, Yanbin Ye1, Min Zhang23, Reagan Kelly1, Li Guo4, Zhenqiang Su1, Stephen C Harris2, Feng Qian1, Weigong Ge2, Hong Fang1*, Xiaowei Xu25* and Weida Tong2*

Author Affiliations

1 ICF International at FDA's National Center for Toxicological Research, 3900 NCTR Rd, Jefferson, AR, 72079, USA

2 Divisions of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA

3 Department of Lymphoma and Myeloma, University of Texas M D Anderson Cancer Center, Houston, TX, 77054, USA

4 State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, P. R. China

5 Department of Information Science, University of Arkansas at Little Rock, 2801 S. University Ave., Little Rock, AR, 72204-1099, USA

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BMC Genomics 2012, 13:325  doi:10.1186/1471-2164-13-325

Published: 20 July 2012

Additional files

Additional file 1:

Description of data: List of all seed genes using various IDs in all three case studies. The highlighted columns are the input gene ID at atBioNet.

Format: XLS Size: 48KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 2:

The 14 literature-identified potential SLE biomarkers in case study 2.

Format: XLS Size: 23KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data