Gerhard, D. S., Clemons, P. A., Shamji, A. F., Hon, C., Wagner, B. K., Schreiber, S. L., Krasnitz, A., Sordella, R., Sander, C., Lowe, S. W., Powers, S., Smith, K., Aburi, M., Iavarone, A., Lasorella, A., Silva, J., Stockwell, B. R., Califano, A., Boehm, J. S., Vazquez, F., Weir, B. A., Hahn, W. C., Khuri, F. R., Moreno, C. S., Johns, M., Fu, H., Nikolova, O., Mendez, E., Gadi, V. K., Margolin, A. A., Grandori, C., Kemp, C. J., Warren, E. H., Riddell, S. R., McIntosh, M. W., Gevaert, O., Kuo, C. J., Ji, H. P., Dhruv, H., Finlay, D., Kiefer, J., Kim, S., Vuori, K., Berens, M. E., Hangauer, M., Boettcher, M., Weissman, J. S., Bivona, T. G., Bandyopadhyay, S., McManus, M. T., McCormick, F., Aksoy, O., Simonds, E. F., Zheng, T., Chen, J., An, Z., Balmain, A., Weiss, W. A., Chen, K., Liang, H., Scott, K. L., Mills, G. B., Posner, B. A., MacMillan, J., Minna, J., White, M., Roth, M. G., Jagu, S., Mazerik, J. (July 2016) Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance. Mol Cancer Res. ISSN 1557-3125 (Electronic)1541-7786 (Linking)
Abstract
The Cancer Target Discovery and Development (CTD2) Network was established to accelerate the transformation of "Big Data" into novel pharmacological targets, lead compounds, and biomarkers for rapid translation into improved patient outcomes. It rapidly became clear in this collaborative network that a key central issue was to define what constitutes sufficient computational or experimental evidence to support a biologically or clinically relevant finding. This manuscript represents a first attempt to delineate the challenges of supporting and confirming discoveries arising from the systematic analysis of large-scale data resources in a collaborative work environment and to provide a framework that would begin a community discussion to resolve these challenges. The Network implemented a multi-Tier framework designed to substantiate the biological and biomedical relevance as well as the reproducibility of data and insights resulting from its collaborative activities. The same approach can be used by the broad scientific community to drive development of novel therapeutic and biomarker strategies for cancer.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics diseases & disorders > cancer bioinformatics > genomics and proteomics therapies bioinformatics > genomics and proteomics > datasets |
| CSHL Authors: | |
| Communities: | CSHL Cancer Center Program > Cancer Genetics CSHL labs > Krasnitz lab CSHL labs > Sordella lab CSHL Cancer Center Program > Cancer Genetics and Genomics Program CSHL Cancer Center Program > Cellular Communication in Cancer Program |
| Depositing User: | Matt Covey |
| Date: | 11 July 2016 |
| Date Deposited: | 22 Jul 2016 16:36 |
| Last Modified: | 26 Oct 2020 16:20 |
| PMCID: | PMC4987219 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/32971 |
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