Biomedical Informatics

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Chief Informatics Officer, Executive Director of Biomedical Informatics:
David J. Foran, PhD

Cancer research continues to become increasingly data-driven and many investigative studies underway at Rutgers Cancer Institute of New Jersey rely upon analysis of multi-dimensional data sets, high-resolution imaging, next generation sequencing and other information-intensive technologies. The Biomedical Informatics shared resource (Bioinformatics) addresses these challenges through the use of high-throughput instrumentation, advanced data management systems, machine-learning technologies, high-performance cloud computing environments and state-of-the-art supercomputing capabilities.

The overarching mission of Bioinformatics is to provide leading-edge data acquisition and analysis tools, computational informatics expertise, data analysis, and intensive training to foster advances in research and discovery in investigative oncology.  Application of these activities to genomic data from patient samples is enhancing patient care and initiating and sustaining productive collaborations among Rutgers Cancer Institute investigators and throughout the clinical and basic research community.

To optimize the support we provide to our basic, clinical and population research programs, Bioinformatics is organized into the following sections:

  • Computational Imaging
  • Clinical and Research Information Technology (IT)
  • Chemical Informatics and Drug Discovery
  • Bioinformatics and Systems Biology.

Under the leadership of Dr. David J. Foran, the team’s deep background and experience provide Rutgers Cancer Institute members with innovative services and the ability to:

  • Design and perform next generation sequencing, analysis, and screening to identify putative cancer driver genes, classify tumors and identify oncogenes, tumor suppressors, and genetic pathways;
  • Design, develop and optimize high-throughput processing and modeling in large, high-dimensional, multi-modal biomedical data sets including combinations of digitized microscopy, radiologic imaging studies, genomics and clinical correlates through the use of cloud and supercomputing resources;
  • Automate extraction, mapping, warehousing and mining of data originating from distributed data sources including EMRs, clinical trials management systems, next generation sequencing devices and imaging (pathology and radiology) archives;
  • Leverage advanced multispectral imaging, color-decomposition, spectral classification and antibody/ antigen, quantum dot conjugate technology to facilitate whole-slide, fluorescent, and multi-spectral digital microscopy services;
  • Develop and optimize computational pathology and radiology imaging and cutting-edge decision support algorithms, methods and strategies to guide choices in treatment and therapy planning, while improving diagnostic and prognostic accuracy and personalizing the management of patients under our care;
  • Provide expert consultation to support molecular dynamics analyses and in silico screening studies to identify lead targets for design and development of novel therapeutics and facilitate drug discovery; and
  • Organize and provide support for advanced training, national workshops, and educational programs.

By providing these services, the shared resource will continue to provide insight into the underlying mechanisms of disease onset and progression while facilitating advances in cancer detection, diagnosis, prognosis, and treatment. 



The Biomedical Informatics shared resource of Rutgers Cancer Institute of New Jersey is a specialized service facility that supports the cancer research efforts of our members.

This facility is supported primarily by the Cancer Center Support Grant (CCSG) from the National Cancer Institute.  Additional support may be provided from other sources, such as chargeback systems, institutional funding and/or other grants. The support from the CCSG allows the facility to provide benefits to Cancer Center members, such as ensured access to services or subsidies to user rates.

Please remember to acknowledge the valuable services provided by the Biomedical Informatics shared resource in your research papers, publications, and grant applications. The following acknowledgement statement is recommended:

"This research was supported by the Biomedical Informatics shared resource of Rutgers Cancer Institute of New Jersey (P30CA072720)."

(Note: please also consider including the names of individuals from the shared resource if they provided any intellectual input or additional effort.)


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