The Role of Ontology in Big Cancer Data
Date: May 12-13, 2015
Venue
- Day 1 (10am-5pm) will be in NCI's Shady Grove building (9609 Medical Center Dr, Rockville, MD, 20850), in Room 2W-32/34.
- Day 2 *9am-3pm) will be a public session in Balcony A, Natcher Conference Center, NIH Building 45, Bethesda, MD 20892
Goal of the meeting (to be expanded): To better understand the challenges involved in using big data for cancer research, and to explore the utility of ontologies in addressing these challenges.
Draft Partial Schedule
Session 1: Addressing Cancer Big Data Challenges through Imaging Ontologies
Tuesday, May 12 in NCI Shady Grove building (9609 Medical Center Dr, Rockville, MD, 20850), Room 2W-32/34
10:00 Barry Smith (Buffalo): The Cancer Research Ontology Space: An Introduction
10:45 Ilya Goldberg (NIA): The Role of Imaging Ontologies in Cancer Big Data
11:30 Metin Gurcan (Ohio) and John Tomaszewski (Buffalo): How Ontologies Can Help in Addressing the Big Data Challenges of Pathology Imaging?
12:15 TBD
13:00 Lunch
Session 2: Addressing Cancer Big Data Challenges with the Ontology for Biomedical Investigations (OBI)
14:00
Chris Stoeckert (Penn): Integration and alignment of ontologies for cancer metadata collection based on OBI
- addresses the challenge that cancer research is multidisciplinary and requires standard terminology from multiple domains.
- briefly describe OBI. Show how it has been used for collecting clinical and -omic metadata highlighting relevance to cancer data and integration of other ontologies for that purpose.
Gully Burns (UCSD): Applying OBI to cancer pathways via Knowledge Engineering from Experimental Design (KEfED)
- addresses the challenge that much of what is known about cancer is only available in publications and requires text mining including the experimental basis for that knowledge.
- application of OBI as semantic base for text mining and knowledge engineering.
Philippe Rocca-Serra: How can OBI contribute to unraveling cancer etiology? Scope, Gaps and Future Development of an interoperable semantic resource
- addresses the challenge that cancer big data is multi-scale and requires agents to analyze.
- demonstrate use of OBI in annotation and data discovery. Address alternatives to OBI and pros and cons.
Mathias Brochhausen (Arkansas): OBI-based integration of biobank data for cancer research
Session 3: Cancer Big Data and the Ontology of Disease
Wednesday, Mar 13 Morning in NCI Shady Grove building (9609 Medical Center Dr, Rockville, MD, 20850), Room 2W-32/34
- 9:00 Lindsay Cowell (UT Southwestern): TBD
- Lynn Schriml (Baltimore): TBD
Themes:
- IoM proposals for a new disease taxonomy
- Cancer clinical genomics
- The Human Disease Ontology
- The Human Phenotype Ontology
12:00 Lunch
Public Session
13:00-15:00, Wednesday, Mar 13 in Balcony A, Natcher
Barry Smith (Chair)
With presentations by
Cathy Wu: Ontology and the Precision Medicine Initiative: The Role of OBO Foundry Ontologies in Protein-Centric Cancer Knowledge Network Discovery
Mark Musen: CEDAR: Making it Easier to Use Ontologies to Author Clinical Metadata
Warren Kibbe: TBD
Sponsors
- National Cancer Institute Center for Biomedical Informatics and Information Technology (CBIIT)
- National Center for Biomedical Ontology (NCBO)
- National Center for Ontological Research (NCOR)
- Center for Expanded Data Annotation and Retrieval ([CEDAR)
Participants
will include:
- Evan Bolton (NIH / NLM / NCBI)
- Mathias Brochhausen (Biomedical Informatics, University of Arkansas for Medical Sciences)
- Gully Burns (Information Sciences Institute, University of Southern California)
- Sherri de Coronado (National Cancer Institute)
- Lindsay Cowell (UT Southwestern Medical Center)
- Peter Elkin (Department of Biomedical Informatics, University at Buffalo)
- Gilberto Fragoso (National Cancer Institute)
- Gang Fu (NIH / NLM / NCBI)
- Ilya Goldberg (Image Informatics and Computational Biology Unit, National Institute on Aging)
- Metin Gurcan (College of Medicine, Ohio State University)
- Warren Kibbe (National Cancer Institute / Disease Ontology)
- Raja Mazumder (Georgetown University / Protein Information Resource)
- Elvira Mitraka (University of Maryland, Baltimore)
- Susan Mockus, Jackson Laboratory for Genomic Medicine, Farmington, CT)
- Mark Musen (Stanford / National Center for Biomedical Ontology and Center for Expanded Data Annotation and Retrieval)
- Darren Natale (Georgetown University / Protein Ontology Consortium)
- Lynn Schriml (University of Maryland, Baltimore / Disease Ontology)
- Barry Smith (Buffalo / Open Biomedical Ontologies Foundry)
- John Tomaszewski (Pathology and Anatomical Sciences, Buffalo)
- Cathy Wu (Delaware / Protein Ontology)
- Wenjin J. Zheng (Center for Computational Biomedicine, University of Texas Health Science Center at Houston)