Using Existing Products And Technologies For Scientific ResearchUsing Existing Products And Technologies For Scientific Research

Dan FayDirector – North AmericaTechnical ComputingMicrosoft Corporation

Dan FayDirector – North AmericaTechnical ComputingMicrosoft Corporation

Can “Here And Now” Technologies Reduce Time To Insight?Can “Here And Now” Technologies Reduce Time To Insight?

Can “Business” Tools and techniques for dealing with

Be used in scientific research to raise the bar and allow researchers to be scientists and not computer scientists.

The Problem For The e-ScientistThe Problem For The e-Scientist

Data ingest

Managing a petabyte

Common schema

How to organize it?

How to reorganize it?

How to coexist and cooperate with others?

Data ingest

Managing a petabyte

Common schema

How to organize it?

How to reorganize it?

How to coexist and cooperate with others?

Data Query and Visualization tools

Support/training

Performance

Execute queries in a minute

Batch (big) query scheduling

Data Query and Visualization tools

Support/training

Performance

Execute queries in a minute

Batch (big) query scheduling

Experiments &Instruments

Simulationsfacts

facts

answers

questions

?Literature

Other Archives facts

facts

ComputationalModeling

Real-worldData

Interpretation& Insight

PersistentDistributed

Data

Workflow,Data Mining& Algorithms

Visual Programmin

g

PersistentDistributed

Storage

Distributed Computatio

n

Interoperability & Legacy Support via

Web Services

Live Documents

Searching &

Visualization

Reputation& Influence

The Scripps Research InstitutePeter Kuhn LabThe Scripps Research InstitutePeter Kuhn Lab

Research FocusEarly detection and therapy management of cancer patients

Modulation of protein interactions for therapeutic intervention

ProjectsCancer bioengineering partnership

Structural Proteomics of SARS

Research FocusEarly detection and therapy management of cancer patients

Modulation of protein interactions for therapeutic intervention

ProjectsCancer bioengineering partnership

Structural Proteomics of SARS

TSRI GoalsTSRI Goals

Improve Collaboration Complex experimental data

Within Scripps and with outside organizations

Capture more data electronicallyImages

Discussions

Structured Data

To provide project data and decisions in context – e.g. annotations on 2D and 3D objects

Leverage existing productivity applications

Improve Collaboration Complex experimental data

Within Scripps and with outside organizations

Capture more data electronicallyImages

Discussions

Structured Data

To provide project data and decisions in context – e.g. annotations on 2D and 3D objects

Leverage existing productivity applications

The Collaborative Molecular Environment The Collaborative Molecular Environment

ApplicationAllows the user to establish context among projects, entities, and annotations

Easily collect data from multiple sources (notes, files, URLs, Screen Clipping)

Provides for Annotation on pictures, data, and molecules

Very simple reporting (not yet implemented)

Windows Presentation FoundationApplication container

Controls for annotating 2D and 3D images

Rapid application environment for images and 3D data

SharePoint 2007Supports the Application with standard Web Services

Provides the security context for project teams and external collaborators

Enables search of annotations in order to find relevant images

Provides a single repository for collaboration with internal and external (SSL) collaborators

Office 2007Captures metadata to describe application context (image, investigator, etc.)

ApplicationAllows the user to establish context among projects, entities, and annotations

Easily collect data from multiple sources (notes, files, URLs, Screen Clipping)

Provides for Annotation on pictures, data, and molecules

Very simple reporting (not yet implemented)

Windows Presentation FoundationApplication container

Controls for annotating 2D and 3D images

Rapid application environment for images and 3D data

SharePoint 2007Supports the Application with standard Web Services

Provides the security context for project teams and external collaborators

Enables search of annotations in order to find relevant images

Provides a single repository for collaboration with internal and external (SSL) collaborators

Office 2007Captures metadata to describe application context (image, investigator, etc.)

External Research & Programs

C-ME And 2D AnnotationC-ME And 2D Annotation

Annotating Protein DataAnnotating Protein Data

Data acquisition from Data acquisition from source systems and source systems and integrationintegration

Data transformation Data transformation and synthesisand synthesis

Data enrichment, Data enrichment, with business logic, with business logic, hierarchical viewshierarchical views

Data discovery via Data discovery via data miningdata mining

Data presentation Data presentation and distributionand distribution

Data access for Data access for the massesthe masses

IntegrateIntegrate AnalyzeAnalyze ReportReport

ResearchResearch

Water Content at 5 cm

y = 0.4712x

R2 = 0.70390.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.1 0.2 0.3 0.4 0.5 0.6

Tonzi

Vai

ra

Water Content at 20 cm

y = 0.5854x

R2 = 0.9163

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.1 0.2 0.3 0.4 0.5 0.6

Tonzi

Vai

ra

Comparison Of Soil MoistureComparison Of Soil Moisture

Thanks to Gretchen Miller – UC Berkeley& Catharine Van Ingen (MSR)

Temperature at North American Sites

-10

0

10

20

30

20 30 40 50 60 70 80

Latitude

Ave

rag

e T

emp

mer

atu

re in

oC

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Other ApplicationsOther Applications

Dynameomics

Goal: Perform MD simulations of representatives of all fold families (unique structures) ----maximize sampling of fold and sequence spaceProtein Folding Protein Unfolding (more tractable}

In Protein Databank~17,000 structures>35,000 domains

CATH, SCOP, Dali fold classification methods consensus → 1130 non-redundant protein folds

www.dynameomics.org

Day et al, Prot. Sci., 2003Thanks toValerie Daggett – Univ of Washington

IGG-like: 1fna Rossman: 3chy TIM barrel: 1ypi Jelly Roll: 1sac - plait: 1ris fibronectin CheY TIM SAP S6

3-helix bundle: 1enh Globin: 1a6n 4-helix bundle: 2a0b -grasp: 1pgb EF-hand: 4icb engrailed homeodomain myoglobin phosphotransfer domain protein G calbindin

Trypsin-like serine Thioredoxin-like: 1ev4 OB fold: 1mjc IGG-like: 1e65 Cytochrome C: 1hrc protease: 1qq4 -lytic protease GST A1-1 CspA azurin cytochrome C

Rossman: 1ght SH3 barrel: 1shg FAD/NAD(P) binding knottin: 1snb C-type lectin: 2afp domain: 1ebd transposon resolvase -spectrin SH3 oxidoreductase neurotoxin BMK M8 type II antifreeze prot.

lipocalin: 1ifc trefoil: 1tld Zn finger: 2adr snake toxin: 1ntn acid protease: 1g6l fatty acid binding prot. bovine trypsin Zn finger (ADR) cobra neurotoxin HIV-1 protease

Rossman: 2pth GST (C-term): 1ev4 IL-8 like (OB): 1bf4 PLP dep. transferase: 1e5f Laminin-like: 1edm peptidyl tRNA GST A1-1 Sso7d methionine -lyase coagulation hydrolase factor IX

Top 30 folds

Represent ~50% of the structures in Protein Databank

Day et al, Prot. Sci., 2003

MD is the time dependent integration of the classical equations of motion for molecular system. Our MD methods have been qualitatively and quantitatively benchmarked against experiment for more than 50 proteins in the past 15 years

Fibronectin, a representative from the top ranked fold (IGG like) is prepared for molecular dynamics (MD) simulation by adding hydrogens (not shown) to the PDB structure and solvating it with explicit waters (red and white in ball & stick).

Example simulation system (1fna)Example simulation system (1fna)

Unfolding of fibronectin, a representative from the top ranked fold (IGG like), from its biologically active state (N) to a denatured, inactive state (D). During unfolding, it loses a critical hydrophobic contact in its core between a valine and a tyrosine

Native (N)

Denatured (D)Starting structure

10 nanoseconds21 ns

Example unfolding simulation (1fna)Example unfolding simulation (1fna)

200 targets complete –6 simulations of each

1 native, 5 unfolding

DOE INCITE Award 3,300,000 CPU hours

On NERSC

250 GB every 48 hours

Projecting that we will have100 TB (compressed)

Now a database is required

200 targets complete –6 simulations of each

1 native, 5 unfolding

DOE INCITE Award 3,300,000 CPU hours

On NERSC

250 GB every 48 hours

Projecting that we will have100 TB (compressed)

Now a database is required

DynameomicsDynameomics

OLAP – On-line Analysis ProcessingOLAP – On-line Analysis ProcessingMOLAP – Multi-dimensional OLAPMOLAP – Multi-dimensional OLAP

SQL Server 2005For Their PurposesSQL Server 2005For Their Purposes

Suite of applicationsRelational database engine

OLAP engine

Performance tools

Extraction, Transformation and Loading tools

Integrated development environment

Suite of applicationsRelational database engine

OLAP engine

Performance tools

Extraction, Transformation and Loading tools

Integrated development environment

MOLAP For Scientific AnalysisMOLAP For Scientific Analysis

Why A Multidimensional Database Is DesiredWhy A Multidimensional Database Is Desired

It is efficient, most of the time, only twoor three dimensions are actively in play

The multidimensionality allows userto select properties of interest andsideline the rest

Better than SQL by eliminating the need for complicated joins

Sparsity tolerant

It is efficient, most of the time, only twoor three dimensions are actively in play

The multidimensionality allows userto select properties of interest andsideline the rest

Better than SQL by eliminating the need for complicated joins

Sparsity tolerant

Faster Time to Insight Better integration to existing Windows infrastructure Integrated and familiar development environment

Faster Time to Insight Better integration to existing Windows infrastructure Integrated and familiar development environment

Fighting HIV With Computer Science Nebojsa Jojic and David Heckerman - MSRFighting HIV With Computer Science Nebojsa Jojic and David Heckerman - MSR

A major problem: Over 40 million infectedDrug treatments are effective but are anexpensive life commitment

Vaccine needed for third world countriesEffective vaccine could eradicate disease

Methods from computer science are helping with the design of vaccine

Machine learning: Finding biological patterns that may stimulate the immune system to fight the HIV virus

Optimization methods: Compressing these patternsinto a small, effective vaccine

A major problem: Over 40 million infectedDrug treatments are effective but are anexpensive life commitment

Vaccine needed for third world countriesEffective vaccine could eradicate disease

Methods from computer science are helping with the design of vaccine

Machine learning: Finding biological patterns that may stimulate the immune system to fight the HIV virus

Optimization methods: Compressing these patternsinto a small, effective vaccine

Developed Set Of Specialist ToolsDeveloped Set Of Specialist Tools

Chromatogram deconvolution

Pathway analysis/association/causal models

Clustering/Trees (phylo, haplotypes etc.)

Protein binding and folding

Sequence diversity models (epitomes)

Image analysis/classification

Evolution modeling and inference

Epitope prediction

Chromatogram deconvolution

Pathway analysis/association/causal models

Clustering/Trees (phylo, haplotypes etc.)

Protein binding and folding

Sequence diversity models (epitomes)

Image analysis/classification

Evolution modeling and inference

Epitope prediction

HIV: The Diabolical VirusHIV: The Diabolical Virus

The train-and-kill mechanism doesn’twork for HIV – the virus adapts through rapid mutation. As soon as the killercells get the upper hand, the epitopes start changing

Strategy Find peptides or epitopes that occur commonly across a *population* of HIV viruses

Compact the known or potential immune targets into a small vaccine

The train-and-kill mechanism doesn’twork for HIV – the virus adapts through rapid mutation. As soon as the killercells get the upper hand, the epitopes start changing

Strategy Find peptides or epitopes that occur commonly across a *population* of HIV viruses

Compact the known or potential immune targets into a small vaccine

HPC and HIV Vaccine DesignCarl Kadie and David HeckermanMachine Learning and Applied StatisticsMicrosoft Research

HPC and HIV Vaccine DesignCarl Kadie and David HeckermanMachine Learning and Applied StatisticsMicrosoft Research

Developed Software: 8 or so new research programs. Most .NET(C# & C++/CLI), One in ‘R’. One in native C++.

Hardware: Cluster of 25 IBM eServer 326, 2 processors per machine

Cluster Software: Windows Compute Cluster Server 2003

Developed Software: 8 or so new research programs. Most .NET(C# & C++/CLI), One in ‘R’. One in native C++.

Hardware: Cluster of 25 IBM eServer 326, 2 processors per machine

Cluster Software: Windows Compute Cluster Server 2003

Fusion EventsFusion Events

Integrated Discovery in Gene Networks

Integrate genome-scale data for discoveryand prediction

Incorporate Disease, multiple organisms

Create applied systems network standard

Integrated Discovery in Gene Networks

Integrate genome-scale data for discoveryand prediction

Incorporate Disease, multiple organisms

Create applied systems network standardThanks to:Mehmet Dalkilic – Indiana University

James Costello (PhD Candidate), Rupali Patwardhan, Sumit Middha, Brian Eads, John Colbourne, Scott BeasonJunguk Hur

Andrews-Dalkilic Laboratory

Microarray Co-Expression

Arbeitman – “Life Cycle of Drosophila”

Parisi – “Incyte Drosophila LifeArray v1.0”

White – “Larval Tissues-Specific Transcripts”

Protein-Protein Interaction

FlyGRID (Fly General Repository for Interaction Dataset)

DIP (Drosophila Interaction Database by CuraGen)

MINT (Molecular Interaction Database)

BIND (Biomolecular Interaction Network Database)

Genetic Interaction

Flybase

Phenotypic Data

Flybase

Binding Site

DNase I Footprint Database and Patser3 using PWM

RNAi Screens

Harvard RNAi Screen – Norbert Perrimon

Microarray Co-Expression

Arbeitman – “Life Cycle of Drosophila”

Parisi – “Incyte Drosophila LifeArray v1.0”

White – “Larval Tissues-Specific Transcripts”

Protein-Protein Interaction

FlyGRID (Fly General Repository for Interaction Dataset)

DIP (Drosophila Interaction Database by CuraGen)

MINT (Molecular Interaction Database)

BIND (Biomolecular Interaction Network Database)

Genetic Interaction

Flybase

Phenotypic Data

Flybase

Binding Site

DNase I Footprint Database and Patser3 using PWM

RNAi Screens

Harvard RNAi Screen – Norbert Perrimon

xl-caBIG Smart Clientxl-caBIG Smart Client

How to give scientists a graphical interface for accessing cancer Biomedical Informatics Grid (caBIG) data-services

http://xl-cabig-client.sourceforge.net/

PI - Katarzyna Macura Johns Hopkins caBIG In Vivo Imaging Workspace Subject Matter Expert

How to give scientists a graphical interface for accessing cancer Biomedical Informatics Grid (caBIG) data-services

http://xl-cabig-client.sourceforge.net/

PI - Katarzyna Macura Johns Hopkins caBIG In Vivo Imaging Workspace Subject Matter Expert

xl-caBIG Smart Clientxl-caBIG Smart Client

Reproducible Research DocumentReproducible Research Document

Broad InstituteBroad InstituteInfusion DevelopmentInfusion DevelopmentBroad InstituteBroad InstituteInfusion DevelopmentInfusion Development

BusinessBusinessIntelligenceIntelligence

SharePoint Products And TechnologiesMicrosoft Office SharePoint Server 2007SharePoint Products And TechnologiesMicrosoft Office SharePoint Server 2007

CollaborationCollaboration

SearchSearch

PortalPortalBusinessBusiness

FormsForms

PlatformPlatformServicesServices

Workspaces, Mgmt,Workspaces, Mgmt,Security, Storage,Security, Storage,

Topology, Site ModelTopology, Site Model

ContentContentManagementManagement

Server-based Excel Server-based Excel spreadsheets and data spreadsheets and data

visualization, Report visualization, Report Center, BI Web Parts, Center, BI Web Parts,

KPIs/DashboardsKPIs/Dashboards

Integrated document Integrated document management, records management, records

management, and Web management, and Web content management with content management with

policies and workflowpolicies and workflow

Rich and Web Rich and Web forms based front-forms based front-

ends, LOB ends, LOB actions, enterprise actions, enterprise

SSOSSO

Docs/tasks/calendars, blogs, Docs/tasks/calendars, blogs, wikis, e-mail integration, wikis, e-mail integration,

project management “lite”, project management “lite”, Outlook integration, Outlook integration,

offline docs/listsoffline docs/lists

Enterprise scalability,Enterprise scalability,contextual relevance, rich contextual relevance, rich

people and business people and business data searchdata search

Enterprise Portal Enterprise Portal template, Site template, Site Directory, My Directory, My Sites, social Sites, social networking, networking,

privacy controlprivacy control

Excel 2007Excel 2007

Design and author

BrowserBrowser

High quality web rending

Zero-footprint

Interactive: Set parameters, sort, filter, explore

Limit to browser access

View and View and Interact Interact

CustomCustomapplicationsapplications

Set values, perform calculations, get updated values via web services

Retrieve full workbook file

Programmatic AccessProgrammatic Access

Open in Excel for rich exploration and analysis

Open snapshots

Excel 2007Excel 2007

Export/Snapshot into ExcelExport/Snapshot into Excel

Spreadsheets stored in document libraries

Spreadsheet calculation and rendering

External data retrieval and caching

100% calculation fidelity

SharePoint platform and Excel servicesSharePoint platform and Excel services

Publish Publish SpreadsheetsSpreadsheets

Excel ServicesOverviewExcel ServicesOverview

Development Data WorkflowCollaboration PublicationsDevelopment Data WorkflowCollaboration Publications

.NET & Visual StudioF#Iron PythonSQL SeverSQL Server analysis ServicesWindows WorkflowSharePoint Server 2007Knowledge NetworkInstant MessengerConferenceXPAcademic Live, Onfolio, etc…

.NET & Visual StudioF#Iron PythonSQL SeverSQL Server analysis ServicesWindows WorkflowSharePoint Server 2007Knowledge NetworkInstant MessengerConferenceXPAcademic Live, Onfolio, etc…

ResourcesResources

Windows Compute Cluster ServerTuesday 12-1 BakerHigh-Performance Computing with Windowshttp://windowshpc.net/

Data miningwww.sqlserverdatamining.com/

Develop without Borders Challengewww.developwithoutborders.com

Technical Computing Blogs http://blogs.msdn.com/dan_fay and http://blogs.msdn.com/eScience

Windows Compute Cluster ServerTuesday 12-1 BakerHigh-Performance Computing with Windowshttp://windowshpc.net/

Data miningwww.sqlserverdatamining.com/

Develop without Borders Challengewww.developwithoutborders.com

Technical Computing Blogs http://blogs.msdn.com/dan_fay and http://blogs.msdn.com/eScience

© 2006 Microsoft Corporation. All rights reserved.Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation.Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft,

and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation.MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.