NA-MIC National Alliance for Medical Image Computing National Centers for Biomedical Computing...

NA-MICNational Alliance for Medical Image Computing http://na-mic.org

National Centers for Biomedical Computing

Software and Data Integration Working Group (SDIWG)

Peter Lyster and Zohara CohenNA-MIC All Hands MeetingTuesday January 10, 2006

National Alliance for Medical Image Computing http://na-mic.org

Brief Journey Through the Seven Centers

NIH Roadmap National Centers for Biomedical Computing (NCBC)

Informatics for IntegratingBiology and the Bedside (i2b2)Isaac Kohane, PI

Center for Computational Biology(CCB)Arthur Toga, PI

Multiscale Analysis of Genomicand Cellular Networks (MAGNet)Andrea Califano, PI

National Alliance for MedicalImaging Computing (NA-MIC)Ron Kikinis, PI

The National Center ForBiomedical Ontology (NCBO)Mark Musen, PI

Physics-Based Simulation ofBiological Structures (SIMBIOS)Russ Altman, PI

National Center for Integrative Biomedical Informatics (NCIBI) Brian D. Athey, PI

Physics-based Simulation of Biological Structures (SIMBIOS)PI: Russ Altman, M.D., Ph.D. PI Institution: Stanford University

This Center will develop, disseminate, and support a simulation tool kit (SimTK) that will enable biomedical scientists to develop and share accurate models and simulations of biological structures from atoms to organisms. SimTK will be an open-source, extensible, object-oriented framework for manipulating data, models, and simulations. The software will include advanced capabilities for modeling the geometry and physics of biological systems, generating the governing differential equations of these systems, integrating the equations to simulate the system dynamics, and interpreting the simulation results through comparison with experimental data. http://cbmc-web.stanford.edu/simbios/

http://cbmc-web.stanford.edu/simbios/

National Alliance for Medical Imaging Computing (NAMIC)PI: Ron Kikinis, M.D.PI Institution: Brigham and Women's Hospital

The National Alliance for Medical Image Computing (NAMIC), proposed here, will integrate the efforts of leading researchers with a shared vision for development and distribution of the tools required to advance the power of imaging as a methodology for quantifying and analyzing biomedical data. This shared vision is based on a thorough composition of computational methods, from image acquisition to analysis, that builds on the best available practices in algorithm development, software engineering, and application of medical image computing for understanding and mitigating the effects of disease and disability. NAMIC’s goal is to develop, integrate, and deploy computational image analysis systems that are applicable to multiple diseases, in different organs. To provide focus for these efforts, a set of key problems in schizophrenia research has been selected as the initial Driving Biological Projects (DBPs) for NAMIC. http://www.na-mic.org/index.htm

http://www.na-mic.org/index.htm

Informatics for Integrating Biology and the Bedside (I2B2)PI: Isaac Kohane, M.D., Ph.D.PI Institution: Brigham and Women's Hospital

I2B2 (Informatics for Integrating Biology and the Bedside) is an NIH-funded National Center for Biomedical Computing based at Partners HealthCare System. The I2B2 Center is developing a scalable informatics framework that will bridge clinical research data and the vast data banks arising from basic science research in order to better understand the genetic bases of complex diseases. This knowledge will facilitate the design of targeted therapies for individual patients with diseases having genetic origins. http://www.partners.org/i2b2

http://www.partners.org/i2b2

Center for Computational Biology (CCB)PI: Arthur Toga, Ph.D. PI Institution: University of California at Los Angeles

The Center for Computational Biology (CCB) was established to develop, implement and test computational biology methods that are applicable across spatial scales and biological systems. Our objective is to help elucidate characteristics and relationships that would otherwise be impossible to detect and measure. The CCB employs an integrative approach, both in terms of the biology and the participating disciplines. The Center focuses on the brain, specifically on neuroimaging, and involves research in mathematics, computational methods and informatics. It also is involved in the development of a new form of software infrastructure – the computational atlas – to manage multidimensional data spanning many scales and modalities. This will be specifically applied to the study of brain structure and function in health and disease, but will have much broader applicability to both biomedical computing and computational biology. http://www.loni.ucla.edu/CCB/

http://www.loni.ucla.edu/CCB/

Open Biomedical Ontologies

(OBO)

Open Biomedical Data (OBD)

BioPortal

Capture and index experimental results

Revise biomedicalunderstanding

Relate experimental data to results from other sources

National Center for Biomedical Ontology (NCBO)PI: Mark A. Musen M.D., Ph.D.PI Institution: Stanford University

Ontologies are essential to make sense of biomedical data

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Core 7: AdministrativeInfrastructure

National Center for Integrative Biomedical Informatics (NCIBI)

Core 4: Computing and DataInfrastructures

DiabetesGenetics

ProstateCancer

BipolarGenetics

DiabetesComplications

Core 3

Core 1:Computational

Technology

Core 2:Bioinformatics

Technology

Core 6: Outreach andDissemination

Core 5: Trainingand Education

PI: Brian D. Athey Ph.DPI Institution: University Of Michigan

SAGA: Patel Lab Feldman Lab:

Diabetes Type 1, NRF2 signalingT1DM pathways

Boehnke Lab: Diabetes Type IISNP WGA workflow Genetic Interaction linkage workflow

McInnis lab: Bipolar DisorderInteractions Between Genetic Linkage Peaks, WNT signaling

Chinnaiyan and Omenn Labs: Prostate CancerBayesian, NLP, Oncomine

Bayesian Nets: Woolf Lab

Workflows: Weymouth,

McEachin, & Programming team

MBI

MiMI

MBI: Molecular Biology Integration DB: States lab, Phillips

Natural Language Processing: States, Meng, Radev Labs

Tools for large- Scale analysis

Database Technologies for

Deep Integration of Biological

Information

MiMI: Michigan Molecular Interactions DB:

Jagadish lab, Tarcea

A B C D

MiMI

User Environment Analyses: Mirel,Ackerman labs

MiMI Onco-mine MBI

BDW

Data

BDW Client

Track useractions

workflow

Concept Mapper: Rhodes, Patel,

Woolf

BDW: Biomedical Data Workbench prototype: Weymouth

First User Environment

Driving Biological Problems

Granular Overview of NCIBI Activities Underway: Cores 1-3

Multiscale Analysis of Genomic and Cellular Networks (MAGNet)

• To study the organization of the complex networks of biochemical interactions whose concerted activity determines cellular processes at increasing levels of granularity.

• To provide an integrative computational framework to organize molecular interactions in the cell into manageable context dependent components.

• To develop interoperable computational models and tools that can leverage such cellular interaction maps to elucidate key biological processes and to dissect complex diseases.

PI: Andrea Califano Ph.D.PI Institution: Columbia University

Core 1: Computational SciencesCore 2: BioinformaticsCore 3: Cadherin binding; Cancer; Genetic determinants of common heritable disorders (Alzheimer’s, Autism)

10 U10 U

10 U

Internet

Open Science Grid

caGRID

Databases

MAGNet/C2B2

Core I, II, III

Algorithms

Data

MPI

BISON

BISON

BISON

geWorkbench


Goals of Software and Data Integration Working Group (SDIWG)

The RFA states the goal of creating “the networked national effort to build the computational infrastructure for biomedical computing for the nation”. In furthering this, the goals of the SDIWG in concert with the Project Team and Centers staff are:

1. To advance the domain sciences, and promote software interoperability and data exchange.

2. To capture the collective knowledge of software engineering and practices among the Centers and publish this knowledge widely


Mechanics…

• Google “SDIWG” (on NA-MIC!)

• Monthly last Friday Breeze/Tcon 2:30 – 3:30 PM ET

• Open (anyone and open minutes)

• Chair Peter Lyster [email protected]


NCBC Staff serving on SDIWG

• Bill Lorensen (NA-MIC)• Mike Sherman (Simbios)• Henry Chueh (I2B2)• Ivo Dinov (CCB)• Aris Floratos (MAGNet)• Daniel Rubin (NCBO)• Brian Athey (NCIBI)• Many others—Suzi Lewis, David States,

Steve Pieper, Tina Kapur, Shawn Murphy, Center PIs…


Peter Lyster (NIGMS, Chair)Michael Ackerman (NLM)Carol Bean (NCRR)Art Castle (NIDDK)German Cavelier (NIMH)Larry Clarke (NCI)Zohara Cohen (NIBIB)Elaine Collier (NCRR)Jennifer Couch (NCI)Peter Covitz (NCI)Valentina Di Francesco (NIAID)Dan Gallahan (NCI)Peter Good (NHGRI)John Haller (NIBIB)

Donald Harrington (NIBIB)Peter Highnam (NCRR)Michael Huerta (NIMH)Donald Jenkins (NLM)Jennie Larkin (NHLBI)Yuan Liu (NINDS)Michael Marron (NCRR)Richard Morris (NIAID)Bret Peterson (NCRR)Salvatore Sechi (NIDDK)Karen Skinner (NIDA)Michael Twery (NHLBI)Terry Yoo (NLM)

NIH Staff serving on SDIWG


There are a number of similar efforts to SDIWG at NIH

• Integrated Cancer Biology Program (ICBP)

• NIAID (Allergy/Infectious Diseases) Bioinformatics Resource Centers (BRC)

• Clinical Research Networks (NECTAR)• Chronic Disease Outcomes (PROMIS)• BIRN/caBIG/Sysbiol/Glue/PSI/TCNP/

P41/PGA/…


Discussions in the First Year

• Demonstration projects

• Collaborative software development environment (yellow pages, knowledge environment, full development environment or Framework)

• NIH-forge

• Emerging efforts in the community (Neuroscience Information Framework, Clearinghouse)

• Intangibles—pairwise interactions, consciousness raising

• Example—SimTK<->ITK


What would you do?


A Biomedical Software Ontology?

• ACM categorization

• Open Directory Project

• Home grown, tipping point?

Why?• To help query tools (computer-computer, human-computer)• To help describe tools (human-human)


NA-MIC Software Classification

ApplicationsSlicer2LONI Pipeline

ToolkitsInsight Toolkit itk Ontology Visualization Toolkit KWWidgets

Software Engineering ToolsTesting

Dart2CTest

Cross-Platform BuildCMake

Cross-Platform DistributionCPack

Cross-Language Wrapping CableSWIG

National Alliance for Medical Imaging ComputingRon Kikinis, M.D.Brigham and Women's Hospital


Simbios Software Classification

Deliverable software modules

Applications

Models

Computational components

Model-building toolsets

Application-building toolsets

User and developer documentation

Application areas

Driving Biological Problems

RNA folding

Myosin dynamics

Cardiovascular fluid dynamics

Neuromuscular biomechanics

Molecule modeling

Electrostatics

Physics-based Simulation of Biological StructuresRuss Altman, M.D., Ph.D. Stanford University



User categories ClinicianExperimentalistApplication developerModelerAlgorithm developerSimTK software developer

Platform support Shared memory multiprocessorsClusters

Language support Scripting languages (tcl, perl, python)JavaC++, C, Fortran



Computation components Linear Algebra (dense, sparse)Numerical Integrators (ODE, DAE, PDE, Stochastic)Monte Carlo simulationMultibody dynamicsContact modelingMeshingPDE solversControllersOptimizers/root findersMolecular force field calculationsComputational geometry

Software development tools Source control

Multiplatform build system Regression test support

Document generation



Software dissemination tools User interaction

Bug reportingFeature requestsMailing listsNews

Software and documentation delivery supportInstallationDownloadUpgrade

EducationTutorials

Course material and software Online courses


CCB Software Classification

Analysis EDA Feature Analysis

Shape Analysis Pattern Recognition

Genomic & Phenotypic Data Analysis Statistical Analysis

E.g., RIntegration

DB Efficient DB Traversal & Querying

Graphical e.g., HIVE Pipeline Grid Computing Resources Mappers e.g., BrainGraph BrainMapper Portals Resource Integration Components Web Services

Center for Computational BiologyArthur Toga, Ph.D. University of California at Los Angeles



Modeling Algorithms

Image Processing Atlas Generation Cortical Modeling Registration Segmentation

Engineering Open Source

Sequence Annotation Simulation SW Development



Pre-Processing Data Transforms

Spectral Transforms Fourier Transform Wavelet Transform

Filtering Skull Stripping

Inhomogeneity Correction Visualization

Clinical Charts e.g., Demographics Graph Viewers

Hyperbolic Graphs Hierarchical Trees

Imaging Cross-Sectional Viewers

Manifold Viewers 2D, 3D, 4D, ND Sequences


I2B2 Software Classification

Computer Code Source

Application Domain(s)LicenseTested on platforms

BinariesApplication Domain(s)LicenseTested on platforms

Informatics for Integrating Biology and the BedsideIsaac Kohane, M.D., Ph.D.Brigham and Women's Hospital



Documentation Biological Experimentation ProtocolAlgorithm DescriptionPublication

PUBMED ID or DOIHuman Cohort DescriptionNon-Human Experiment Description

OrganismSoftware/Technology protocolsTechnology white papers

Application Domains (Software)



Clinical Information Systems Natural Language Processing

Predictive modeling and classificationExtract, Transform, and LoadDatabase SchemaOntology ManagementService Oriented Architecture

Biological StructureStructure:function and structure:disease predictionProtein interaction modeling



Clinical Information Systems (cont.)Expression studies

Disease classification/advanced histopathologyOutcome predictionPathway/gene identification for diseaseIntegration of expression w/DNA studies

DNA/Genomic studiesPopulation study type (association/linkage etc)Scoring/predicting DNA variant functional and disease

significanceComparative genomicsMotif studies (TFBS/miRNA/protein domains, etc)



Experimental Data Aggregate Human Data

DNARNAProteinNon-image PhenotypeImage

Individual Human DataDNA (sequence and

mapping)RNAProtein

Non-image Phenotype

ImageUsage

Non-humanDNARNAProteinNon-image PhenotypeImage



Equipment Genomic MeasurementImaging

Imaging ClassDNA (sequence and mapping)

Gene IDNon-standard descriptor

RNA Gene IDSplice variantNon-standard descriptor

ProteinID or AA sequence?

Non-image Phenotype UMLS or other vocabulary codedNarrative text



Usage Anonymity levelConsent level

Image DICOM?MIME type?

Reagents Chemical Organismal


NCIBI Software Classification

Data ManagementTIMBER

Michigan Molecular Interactions (MiMI)

Biomolecular Interaction Network Database (BIND)

Human Proteome Organization Plasma Proteome Project (HUPO)

BioWarehouse

BioPAX

Community and User Interaction SystemsWorm Community System

MEDSPACE

VEHICLES

Answer Garden

NJFun

National Center for Integrative Biomedical InformaticsBrian D. Athey, Ph.D. University of Michigan


NCIBI Software Classification

Database and Information Retrieval AlgorithmsPeriscopemiBLAST

Workflow ManagementGenePattern

Ontologies and Natural Language ProcessingMEADNewsInEssenseProtégé

Image ProcessingEdgewarp


MAGNet Software Classification

AnalysesRegulatory/Signaling network reconstruction

ARACNE (gene expression) GeneClass (gene expression)

Network characterization NetClass/NetBoost (molecular interactions networks)InfoMod (molecular interactions networks)

Homology-based protein sequence classification Bio-Kernels (protein sequences)RankProp/MotifProp (protein sequences)

Structured-based protein classification Protein function pipeline (protein structure)

Prediction of regulatory (cis) elementsREDUCE (gene expression)MEDUSA (gene expression)

National Center for Multi-Scale Study of Cellular NetworksAndrea Califano, Ph.D. Columbia University


MAGNet Software Classification

Analyses (cont.)

Protein structure prediction

Protein structure pipeline (protein sequence)

META-server (protein sequence)

Super-NEST (protein sequence)

Protein cavity and binding site prediction (protein structure)

Databases

Molecular interactions

GeneWays

Cellular Network KB

Gene-phenotype associations

PhenotypeML DB


NCBO Software Classification

Ontology Management ProtégéOBO-EDIT

Ontology Diff and Alignment PROMPT

Ontology Visualization JambalayaOntoVizPromptVizTGViz

National Center for Biomedical OntologyMark A. Musen, M.D., Ph.D.

Stanford University


NCBO Software Classification

Biomedical Data Annotation OBO-EDIT

Progammatic Access to Ontologies Protege Script Tab

Web Access to Ontologies WebProtege


Suggestion for Next Step1. Choose one of the existing ontologies as a starting point, perhaps a

combination of the MAGNet and CCB ontologies.

2. Find one person at each NCBC who is interested in the issue of categorizing their software and who is willing to work with the SDIWG on incorporating their taxonomy into the chosen top level ontology.

3. The NCBC representatives will incorporate their software into the ontology directly or suggest changes needed in order to incorporate their software.

4. After the software are all integrated into one ontology, a set of attributes to describe the software will be developed. A format for storing the ontology will be agreed upon.

5. Each NCBC will create and host an instance of the ontology to describe their resources. OWL/Semantic Web may be used.


Contact Peter Lyster [email protected]

301.594.3928

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