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Upcoming Speaker: 

September 26, 2018

An invitation: If you are interested in presenting your work to our diverse audience of informaticists; basic, translational, and clinical researchers; software developers; and others interested in exploring the uses of informatics in cancer research, contact Eve Shalley at or 240-276-5194.


Welcome to the CBIIT Speaker Series Wiki 

The NCI Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics community. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin.

Speakers represent many different institutions, and the topics they address are wide-ranging. View a list of all past speakers, and view their presentations on our NCI CBIIT Speaker Series YouTube playlist!

For help accessing NCI CBIIT Speaker Series files, go to Help Downloading Files.

Location: 9609 Medical Center Drive, Rockville, Maryland 20850

Speaker Series Guidelines for Speakers: Download Word document

Questions or suggestions? If you have questions or would like to recommend a speaker, please email Eve Shalley at

Please refer to the Speaker Calendar below for upcoming speakers.


Upcoming Speakers:

September 26, 2018: Dr. Rob Smith, University of Montana

October 10, 2018: Helga Thorvaldsdottir, Broad Institute; Jim Robinson, UC San Diego; Mary Goldman, UC Santa Cruz; and Alex Krasnitz, Ph.D., Cold Spring Harbor National Lab (presenting via WebEx)

CBIIT Speakers

Dr. Rob Smith

This talk will discuss the role, effect, and quality of informatics in publicly funded research, from selection of proposals for funding to execution and sustainment. The case will be made that current funding mechanisms are mismatched to the scope, needs, and impact of informatics research by comparing and contrasting informatics projects with traditional experimental R&D proposals. Causes for poor quality informatics projects will be enumerated and suggestions given to address them.


Session details...




Dr. Tony Blau

Cancer patients and their doctors choose from a range of different treatment options. But often the chosen treatment is ineffective, reducing quality and length of life and increasing cost. Today treatment decisions and outcomes occur in isolation. All4Cure has built a patient-centered, web-based, knowledge sharing platform that graphically portrays treatments and responses extracted from the medical records of de-identified patients with multiple myeloma (the second most common form of blood cancer) for comment by a community of participating patients, clinicians and researchers. Having assembled more than 580 participants we will describe examples of patients have benefited from their participation.


Session details...

Dr. Daoud Meerzaman

Cancer is a complex category of diseases caused in large part by genetic or genomic, transcriptomic, proteomic, and epigenomics alterations leading to abnormal cell proliferation.  Genes and their protein products rarely act in isolation. Therefore, it is necessary to utilize a comprehensive and integrated computational approach informed by systems biology and omics-oriented approaches to investigate the disruption of biological networks caused by genomic alterations.

In this talk, Dr. Meerzaman will describe two ongoing projects. The first focuses on Sequencing Quality Control Phase 2 (SEQC II), a collaborative project led by the Food and Drug Administration (FDA) that systematically investigated somatic mutations in paired breast cancer and normal cell lines and formulated best practices for identifying, or calling, genomic variations such as single-nucleotide polymorphisms, copy-number alterations, or single-nucleotide variants. Regarding the second project, Dr. Meerzaman will discuss methods developed by the CGBG team to use mutual exclusivity and pathway network interaction algorithms to identify low-frequency “driver” (that is, causative) genomic alterations at the pathway level.

Session details...


Dr. Casey GreeneDeep learning methods have shown substantial promise across many tasks, including some relevant to biomedicine. I'll chat about some examples of how these algorithms can be used as well as the challenges that I expect us to face as we start using these on a massive scale. Also, as deep learning methods proliferate in the biomedical sciences, I expect that we will need to reconsider how we discuss reproducibility in computational research. I'll touch on a couple steps towards these objectives, but substantially more work will be needed.

Session details...



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