NIH Roadmap National Centers for biomedical computing

The National Centers for Biomedical Computing (NCBC) are cooperative agreement awards that are funded under the NIH Roadmap for Bioinformatics and Computational Biology. The Centers are intended to be the core of the networked national effort to build the computational infrastructure for biomedical computing in the nation, the National Program of Excellence in Biomedical Computing (NPEBC).

There are seven funded Centers that cover systems biology, image processing, biophysical modeling, biomedical ontologies, information integration, and tools for gene-phenotype and disease analysis. The centers will create innovative software programs and other tools that enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease.

Each Center has Cores that are focused on (1) computational science, (2) biomedical computational science and (3) driving biological projects whose intent is to drive the interaction between computational and biomedical computational science.

In addition to the Centers, the NIH has a number of active program announcements to develop collaborations with the biomedical research community—this includes announcements from the Biomedical Information Science and Technology Initiative (BISTI) and the Program for Collaborations with National Centers for Biomedical Computing. There are numerous efforts in education and training that emanate from the Centers and there is an annual all hands meeting.

NCBC’s awarded in 2004

  • Center for Computational Biology
  • Informatics for Integrating Biology and the Bedside
  • National Alliance for Medical Imaging Computing
  • Physics-based Simulation of Biological Structures

NCBC’s awarded in 2005

  • National Center for Biomedical Ontology
  • National Center for Integrative Biomedical Informatics
  • National Center for the Multi-Scale Analysis of Genomic and Cellular Networks

The NIH Roadmap National Centers for Biomedical Computing awarded in 2004 wereCenter for Computational Biology

 Centers for Biomedical Computing

PI: Arthur Toga, Ph.D.
PI Institution: University of California at Los Angeles
ID: 1-U54-RR021813
NIH Program Officer (PO): Greg Farber, Ph.D. (NCRR)
NIH Lead Science Officer (LSO): John Haller, Ph.D. (NIBIB)
NIH Science Officers (SO): Tom Aigner (NIDA), Larry Clarke (NCI), Valerie Florance (NLM), Dan Gallahan (NCI), Mike Huerta (NIMH), Yuan Liu (NINDS), Bret Peterson (NCRR), Terry Yoo (NLM), Yantian Zhang (NIBIB)

CCB Summary:
The Center for Computational Biology (CCB) studies the dynamic properties of biological shape, form and size using novel mathematical algorithms and advanced computational techniques based on statistical learning, spectral analysis and differential equations. CCB develops, validates and disseminates data and software tools for modeling, analysis and visualization of shape across the spectrum of space-and-time scales. These new methods are applied for longitudinal studies of brain development, HIV/AIDS induced dementia, schizophrenia, multiple sclerosis and animal brain models for health and disease.

Informatics for Integrating Biology and the Bedside

PI: Isaac Kohane, M.D., Ph.D.
PI Institution: Brigham and Women’s Hospital
ID: 1-U54-LM008748
NIH Program Officer (PO): Valerie Florance (NLM)
NIH Lead Science Officer (LSO): Valentina Di Francesco (NIAID)
NIH Science Officers (SO): Vivien Bonazzi (NHGRI), Rochelle Long (NIGMS), James Luo (NIBIB), Dina Paltoo (NHLBI), Joni Rutter (NIDA)

i2b2 Summary:
How can we use the informational by-products of the healthcare system for discovery research in the genomic era? Can we make every patient’s healthcare encounter maximize the progress of medicine? Informatics for Integrating Bench and the Bedside (i2b2) is designed to answer these questions affirmatively by providing a suite of tools, methods and vivid examples for use, particularly in large healthcare systems to enable population-based, genomically-augmented measurements across these systems.

These solutions include a free and open source set of tools, collectively known as the i2b2 Hive, that enable “natural language processing” of the text in medical records to provide automated characterization of thousands of patients, that automatically remove identifying data to protect patient privacy, and that allow obtaining thousands of DNA samples per week for genome-wide studies.

The methodologies range from novel predictive methods to determine how much more information, relative to conventional clinical measures, can be reliably obtained from genomic studies to organizational methods to efficiently manage the regulatory challenges of multi-institutional research. I2b2’s initial disease foci include: finding predictive genomic markers for asthma exacerbations, gene expression signatures to improve diabetic management, genomic markers to refine the classification of hypertension, and expression signatures to measure the efficacy of potential therapies for Huntington’s Disease.

National Alliance for Medical Imaging Computing

PI: Ron Kikinis, M.D.
PI Institution: Brigham and Women’s Hospital
ID: 1-U54-EB005149
NIH Program Officer (PO): Grace Peng, Ph.D. (NIBIB)
NIH Lead Science Officer (LSO): Michael Ackerman, Ph.D. (NLM)
NIH Science Officers (SO): German Cavelier (NIMH), Zohara Cohen (NIBIB), Keyvan Farahani (NCI), John Haller (NIBIB), Karen Skinner (NIDA) , Larry Stanford (NIDA), Terry Yoo (NLM)

NA-MIC Summary:
The National Alliance for Medical Imaging Computing (NA-MIC) is a multi-institutional, interdisciplinary team of computer scientists, software engineers, and medical investigators who develop computational tools for the analysis and visualization of medical image data.

The purpose of the center is to provide the infrastructure and environment for the development of computational algorithms and open source technologies, and then oversee the training and dissemination of these tools to the medical research community. This world-class software and development environment serves as a foundation for accelerating the development and deployment of computational tools that are readily accessible to the medical research community.

The team combines cutting-edge computer vision research (to create medical imaging analysis algorithms) with state of the art software engineering techniques (based on “extreme” programming techniques in a distributed, open-source environment) to enable computational examination of both basic neurosience and neurological disorders. In developing this infrastructure resource, the team is significantly expanding upon proven open systems technology and platforms.

The driving biological projects initially come from the study of schizophrenia, but the methods are applicable to many other diseases. The computational tools and open systems technologies and platforms developed by NA-MIC is initially being used to study anatomical structures and connectivity patterns in the brain, derangements of which have long been thought to play a role in the etiology of schizophrenia.

The overall analysis occurs at a range of scales, and across a range of modalities including diffusion MRI, quantitative EGG, and metabolic and receptor PET, and will potentially include microscopic, genomic, and other image data. It applies to image data from individual patients, and to studies executed across large populations. The data is taken from subjects across a wide range of time scales and will ultimately apply to a broad range of diseases in a broad range of organs.

Physics-based Simulation of Biological Structures

PI: Russ Altman, M.D., Ph.D.
PI Institution: Stanford University
ID: 1-U54-GM072970
NIH Program Officer (PO): Peter Lyster, Ph.D. (NIGMS)
NIH Lead Science Officer (LSO): Jennie Larkin, Ph.D. (NHLBI)
NIH Science Officers (SO): Jennifer Couch (NCI), Semahat Demir (NSF), Peter Highnam (NCRR), Jerry Li (NIGMS), Richard Morris (NIAID), Grace Peng (NIBIB), David Thomassen (DOE), Ron White (NASA/USRA)

Simbios Summary:
Simbios ( is devoted to helping biomedical researchers understand biological form and function. It provides infrastructure, software, and training to assist users as they create novel drugs, synthetic tissues, medical devices, and surgical interventions. Consequently, it supports structure-function studies on a wide scale of biology – from molecules to organisms.

Simbios scientists are currently focusing on challenging biological problems in RNA folding, myosin dynamics, neuromuscular biomechanics and cardiovascular dynamics. Simbios also provides the biomedical community with, a free, secure, archival, distributed software repository and development system, where researchers and computational scientists can gather to collectively pursue their interests in physics-based simulation of biological structures. presents individual projects that may include models, software, data, documentation, publications, and graphics. is also the home of the SimTK simulation toolkit, our open-source, professionally developed software that provides advanced capabilities for modeling geometry and dynamics and facilitates physics-based simulation of biological systems.

The toolkit and associated training materials result from a close collaboration with biomedical scientists. Simbios’ broad dissemination efforts include (1) the Biomedical Computation Review, a magazine devoted to the science and tools in biocomputation, (2) Simbiome, a searchable inventory of high-quality commercial and academic bio-simulation tools, and (3) both onsite and distance learning materials for biomedical scientists and students.

The NIH Roadmap National Centers for Biomedical Computing awarded in 2005 were:

National Center for Biomedical Ontology

PI: Mark A. Musen, M.D., Ph.D.
PI Institution: Stanford University
ID: 1-U54-HG004028-01
NIH Program Officer (PO): Peter Good, Ph.D. (NHGRI)
NIH Lead Science Officer (LSO): Carol Bean, Ph.D. (NCRR)
NIH Science Officers (SO): Arthur Castle (NIDDK), German Cavelier (NIMH), Jennifer Couch (NCI), Sherri De Coronado (NCI), Christopher Greer (NSF), Jennie Larkin (NHLBI), Karen Skinner (NIDA), Ram Sriram (NIST)

NCBO Summary:
The National Center for Biomedical Ontology (NCBO) is a consortium of leading biologists, clinicians, informaticians, and ontologists who develop innovative technology and methods that allow scientists to create, disseminate, and manage biomedical information and knowledge in machine-processable form. The vision for the NCBO is that all biomedical knowledge and data are disseminated on the Internet using principled ontologies, such that the knowledge and data are semantically interoperable and useful for furthering biomedical science and clinical care.

The Center’s resources include: an integrated Open Biomedical Ontologies (OBO) library; the BioPortal, a web portal for accessing, visualizing, and biomedical ontologies; a database of annotations on experimental data, the Open Biomedical Data (OBD) repositories; and tools for accessing and using this biomedical information in research.  The NCBO collaborates with Driving Biological Projects (DBPs) that involve the development and use of ontologies to annotate different types of biomedical information and to extract additional knowledge from this data.

Two DBPs based at model organism databases for zebrafish and fruit flies focus on the development and application of ontologies to describe phenotypes with the broad goal of integrating human and model organism data.  An additional DBP applies ontologies to structure data to enable the analysis of HIV clinical trial data.

A key component of the NCBO is the dissemination plan to institute frequent, formal workshops to help investigators at the grass roots to design biomedical ontologies of more utility and of more lasting value. These workshops are part of a general endeavor to establish and test best practices in ontology-building and to disseminate these practices across an ever wider community in ways designed to assure comparability of data.

National Center for Integrative Biomedical Informatics

PI: Brian D. Athey, Ph.D.
PI Institution: University of Michigan
ID: 1-U54-DA021519-01A1
NIH Program Officer (PO): Karen Skinner, Ph.D.(NIDA)
NIH Lead Science Officer (LSO): Donald P. Jenkins (NLM)
NIH Science Officers (SO): Mayada Akil (NIMH), Lisa Brooks (NHGRI), Jennifer Couch (NCI), German Cavelier (NIMH), David Harlan (NIDDK), Peter Highnam (NCRR) Di Francesco Valentina (NIAID)

NCIBI Summary:
The Mission of the National Center for Integrative Biomedical Informatics ( is to create targeted knowledge environments for molecular biomedical research that help guide experiments and enable new insights from the analysis of complex diseases. NCIBI develops efficient software tools, data integration methods, and systems modeling environments.

The resulting NICIBI “suite of tools and data” facilitates rapid construction of context-appropriate molecular biology information schemas from experimental data, biomedical databases, and the published literature. These tools, together with laboratory and community data resources, have accelerated our assembly of relevant information for research on our four Driving Biological Problems (DBPs): Prostate Cancer Progression, Complications of Type-1 Diabetes, Genetic Heterogeneity of Type-2 Diabetes, and Genetic Susceptibility of Bipolar Disorder. NCIBI is disseminating these tools, data, and their integration capabilities for applications through portal-enhanced outreach and innovative web-based interactive training and educational programs for our partners around the country and for the broader NIH community and potential new collaborators.

National Center for the Multi-Scale Analysis of Genomic and Cellular Networks

PI: Andrea Califano, Ph.D.
PI Institution: Columbia University
ID: 1-U54-CA121852-01A1
NIH Program Officer (PO): Dan Gallahan, Ph.D. (NCI)
NIH Lead Science Officer (LSO): Salvatore Sechi, Ph.D. (NIDDK)
NIH Science Officers (SO): Valerie Florance (NLM)

MAGNet Summary:
Cellular processes are determined by the concerted activity of thousands of genes, their products, and a variety of other molecules. This activity is coordinated by a complex network of biochemical interactions largely determined by molecular structures and physiochemical properties which control common intra and inter-cellular functions over a wide range of scales.

At an increasing level of granularity, these may range from the formation/activation of transcriptional complexes, to the availability of a signaling pathway, all the way to complex, macroscopic cellular processes, such as cell adhesion. Understanding this organization is crucial for the elucidation of biological function and for framing associated health related applications in a quantitative, molecular context. Additionally, the emerging complexity of these molecular interactions in the cell calls for a new level of sophistication in the design of genome-wide computational approaches.

The National Center for the Multiscale Analysis of Genomic and Cellular Networks (MAGNet) addresses this challenge through the application of both knowledge-based and physics-based methods. The Center provides an integrative computational framework to organize molecular interactions in the cell into manageable context dependent components. Furthermore, it is developing a variety of interoperable computational models and tools that can leverage such a map of cellular interactions to elucidate important biological processes and to address a variety of biomedical applications.


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