Seaport World Trade Center, 200 Seaport Boulevard, Boston, MA 02210
April 9-11, 2013
The 2013 Expo plans to unite 2,500+ life sciences, pharmaceutical, clinical, healthcare, and IT professionals from 30+ countries, and provides the perfect venue to share information and discuss enabling technologies that are driving biomedical research and the drug development process. Since its debut in 2002, the annual Bio-IT World Conference & Expo has established itself as a premier event showcasing the myriad applications of IT and informatics to biomedical research and the drug discovery enterprise. The 2013 program will feature compelling talks from industry and academia on new trends in data generation, knowledge management, and information technology in life sciences and drug development, including best practice case studies and joint partner presentations relevant to the technologies, research, and regulatory issues of life science, pharmaceutical, clinical and IT professionals. Bio-IT World Conference & Expo continues to expand with the addition of two new Tracks: Data Visualization and Clinical Omics. Spanning three days, the meeting includes 12 parallel conference tracks and 16 pre-conference workshops. Concurrent Tracks: - IT Infrastructure – Hardware Big Data Solutions and End-User Perspectives
- Software Development Technologies and Applications for Managing and Sharing Data
- Cloud Computing Riding the Cloud to Next-Generation Computing
- Bioinformatics Understanding Massive Quantities of -omic Information across Research Initiatives
- Next-Generation Sequencing Informatics NGS, Genome-Scale Screening and HTP Proteomics
- Systems Pharmacology Pathways to Patient Response
- eClinical Trials Solutions Innovative Management in Clinical Trials
- Data Visualization and Exploration Tools From Discovery to the Clinic
- Drug Discovery Informatics Thinking of Drugs Outside of the Box
- Clinical Omics Tools for Integrating and Interrogating Multiple Omic Data Sets
- Collaborations and Open Access Innovations Collaborative and Open Access Models for Advancing Research, Discovery and Personalized Medicine
- Cancer Informatics Applying Computational Biology to Cancer Research/Care
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