The Jet Propulsion Laboratory, California Institute of Technology will host the Cancer Biomarkers Bioinformatics Workshop at the California Institute of Technology, Pasadena, California, April 29 through May 1, 2013.
To participate in the workshop, please register. There is no registration fee—it's free! All attendees are encouraged to submit a poster abstract on their work. Posters having high merit may be selected for oral presentations as space is available.
The workshop is intended to define and discuss the informatics needs for cancer biomarker discovery and validation. We anticipate a multi-disciplinary group of researchers spanning biomedical research and informatics. “Bench” researchers may provide case studies that reflect their informatics needs. Informatics personnel may introduce new tools or data resources to the audience. Community dialogue will be encouraged during discussion-panel sessions. A lively poster session will encourage participation of multiple researchers.
Significant progress has been made in informatics to improve the capture and analysis of scientific data. However, many of these techniques remain substantially ad hoc, with little standardization of methods for collecting and analyzing. Integration of data pipelines may lead to increased data access for meta-analysis, authenticated provenance for data sets and methods, scalable and sustainable infrastructure for storage and analysis, and assured quality assessment. Taken together, these improvements could have a substantial impact on cancer research.
This three-day workshop will highlight informatics resources, needs, and challenges for cancer biomarker research with a specific emphasis on the identification of future priorities and plans.
The following are a list of the planned sessions:
Session I: Informatics in Biomarker Discovery
The application of multiple biotechnologies to the development of cancer biomarkers is inextricably linked to the development of algorithms to support the analysis of complex data sets. This session will combine contributions from researchers who have identified key needs for support of experimental methodologies and from researchers who have developed needed algorithms for biomarker data capture, integration, and analysis.
Session 2: Informatics in Biomarker Validation
As new candidate biomarkers are reported in journals each week, the need to test and validate these biomarkers has become critical in the field. This session will combine case studies from researchers engaged in biomarker assessment that highlight the need for informatics improvements and from researchers who have developed new algorithms to assist in biomarker data evaluation.
Session 3: Quality-by-Design in Biomarker Research
The use of quality-by-design methodologies can make biomarker discovery and validation more rigorous, increasing the reproducibility of significant biomarker findings. This session will feature case studies, documentation tools, standards for minimum data to annotate, and algorithms in support of variability assessment for experimental methodology, the characterization of performance over time for methods, and the confidence associated with experimental results. By assisting in the introduction of quality-by-design concepts for biomarker research, this session will aid researchers in validating their platforms for reliable biomarker research.
Session 4: Data Integration and Biological Networks
The use of multiple biotechnologies introduces the challenge of integrating across multiple data types. Frequently, the incorporation of existing knowledge in the interpretation of an experiment implies organizing and evaluating results in accordance with existing biological network data. This session will include case studies and algorithmic developments addressing these two challenges;it will also seek to identify areas of research that are most likely to pay dividends in cancer biomarker research.
Session 5: Biomarker Informatics Infrastructure
This session will focus on supporting large-scale informatics systems for cancer research and other efforts. Examples will include large-scale data management, sharing, and discovery systems that support researchers for biomarker discovery, analysis and validation. It will also include the development of data and metadata standards to enable data capture, sharing and analysis. This session will attempt to point the way forward for cancer biomarker repositories and shared analysis architecture.
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