11

Grids/CI for Scholarly Researchand application to

Chemical InformaticsHPC 2006 in Cetraro – Italy

July 4 2006

Geoffrey Fox

Computer Science, Informatics, PhysicsPervasive Technology Laboratories

Indiana University Bloomington IN 47401

gcf@indiana.eduhttp://www.infomall.org

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Motivation Build Cyberinfrastructure (Grids) that

• Support science from beginning (planning, instruments) through middle (analysis) and end (refereed publications, follow-on work)

• Integrates with the popular Web 2.0 (community) tools whose successes point to interesting ways of working together

• Integrate with Digital Library technology• Does not redo previous work but rather augments it• Assumes a heterogeneous fragmented world with multiple

platforms• Allows one to specify and manage all the services and data

that a project needs with a mix of synchronous, asynchronous, close (classic workflow) and loose (including zero) coupling

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Application Drivers Chemical Informatics as this has very precise naming

rules for compounds that allow accurate searches in documents• Suggesting how to tag scientific documents either when

writing it or after the fact “Global Information Grid” (Military Net-Centric

systems) as these inevitably need Grid of Grids to support “systems of systems”

Journal web site of the future as illustrated by Nature building social bookmarking tool Connotea

Conference support tools as can benefit from features needed by journals

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The Science Drivers From Workshop on Challenges of Scientific Workflows

http://vtcpc.isi.edu/wiki/index.php/Main_Page Workflow is underlying support for current science

model• Distributed interdisciplinary data deluged scientific

methodology as an end (instrument, conjecture) to end (paper, Nobel prize) process is a transformative approach

Reproducibility core to scientific method and requires rich provenance, interoperable persistent repositories with linkage of open data and publication as well as distributed simulations, data analysis and new algorithms.

Distributed Science Methodology publishes all steps in a new electronic logbook capturing scientific process (data analysis) as a rich cloud of resources including emails, PPT, Wikis as well as databases, compiler options, build time/runtime configuration…

Community (? VO) Tools e-mail and list-serves are oldest and best used Kazaa, Instant Messengers, Skype, Napster, BitTorrent for P2P

Collaboration – text, audio-video conferencing, files del.icio.us, Connotea, Citeulike, Bibsonomy, Biolicious manage

shared bookmarks (later) MySpace, Bebo, Hotornot, Facebook, or similar sites allow you to

create (upload) community resources and share them; Friendster, LinkedIn create networks• http://en.wikipedia.org/wiki/List_of_social_networking_websites

Writely, Wikis and Blogs are powerful specialized shared document systems

ConferenceXP and WebEx share general applications Google Scholar (Citeseer) tells you who has cited your papers

while publisher sites tell you about co-authors• Windows Live Academic Search has similar goals (later)

Note sharing resources creates (implicit) communities• Social network tools study graphs to both define communities

and extract their properties

How to use Web2.0 Community tools in CI Nearly all of them have “profiles”, “users”, “groups”, “friends”

etc.• Need to integrate these

P2P File Sharing: Maybe this is useful for sharing files in research groups (virtual organizations)• Will modify Maze http://maze.pku.edu.cn – popular Chinese social P2P

system with 2.5 million users BitTorrent: more popular than FTP – why not use for higher

performance fault tolerant cached file sharing? MySpace etc.: Could consider MyGridSpace or MyScienceSpace

that supports a similar document sharing model with users uploading pictures, papers and even data/services of interest• Could include uploaded material in workflows• Can impose different policies

Social Bookmarking and linking: discuss later• http://gf6.ucs.indiana.edu:48990/SemanticResearchGrid/

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SSG Domain-1Web service

SSG Domain-NWeb service

Tool-1Del.icio.us

Tool-2Connotea

Tool-3MySpace

Tool–N e.g.CiteSeer

NativeUI-1

NativeUI-4

NativeUI-3

NativeUI-N

IntegratedUser Interface UI

GatewayWS-1

GatewayWS-2

GatewayWS-3

GatewayWS-N

SSG MDStore

Integration Framework of Tools

SSG = Semantic Scholars’ Grid

Strategy Doesn’t seem useful to build the 251st community tool In fact a major barrier to use of existing tools is

• What happens when a better tool comes along and/or chosen tool disappears (unsupported/removed from Web)

So assume use existing tools but wrap them all as web services so can transfer information to new tools and integrate information between tools• Need some “glue” logic, a “unification” database and minimal user

interface Bookmarking tools: del.icio.us, Connotea, CiteULike (includes

plug-ins to major publisher sites) Document: Google Scholar, Windows Live, Citeseer tools,

OSCAR3 for Chemistry (later), Science.gov Journals: Manuscript Central Conferences: CMT from Microsoft or ?

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Connotea

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Connotea queried by SERVOGrid

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Delicious Semantic Web/Grid http://del.icio.us purchased by Yahoo for ~$30M http://www.CiteULike.org http://www.connotea.org (Nature) Associate metadata with Bookmarks specified by

URL’s, DOI’s (Digital Object Identifiers) Users add comments and keywords (called tags) Users are linked together into groups (communities) Information such as title and authors extracted

automatically from some sites (PubMed, ACM, IEEE, Wiley etc.)

Bibtex like additional information in CiteULike This is perhaps de facto Semantic Web – remarkable

for its simplicity

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Document-enhanced Cyberinfrastructureaka Semantic Scholar Grid I

Citeseer and Google Scholar scour the Internet and analyze documents for incidental metadata• Title, author and institution of documents• Citations with their own metadata allowing one to match

to other documents Science.gov extracts metadata from lots of US Government

databases These capabilities are sure to become more powerful and to

be extended• Give “Citation Index” in real time• Tell you all authors of all papers that cite a paper that

cites you etc. (Note it’s a small world so don’t go too far in link analysis)

• Tell you all citations of all papers in a workshop

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Document-enhanced Cyberinfrastructureaka Semantic Scholar Grid II

It is natural to develop core document Services such as those used in Citeseer/Google Scholar but applied to “your” documents of interest that may not have been processed yet • As just submitted to a conference perhaps

These tools can help form useful lists such as authors of all cited or submitted papers to a journal

OSCAR2/3 (from Peter Murray-Rust’s group at Cambridge) augment the application independent “core” metadata (Title, authors, institutions, Citations) with a list of all chemical terms • This tool is a Service that can be applied to “your” document or to a set of

documents harvested in some fashion

• Other fields have natural application specific metadata and OSCAR like tools can be developed for them

Such high value tools could appear on “publisher” sites of future (or else publishers will disappear)

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ExistingUser Interface

Document-enhanced Cyberinfrastructure

etc.

Google Scholar

ManuscriptCentral

Science.gov

Windows Live Academic Search

Citeseer

CMT Conference

Management

Existing Documentbased Research Tools

Web serviceWrappers

New Document-enhancedResearch Tools

Integration/EnhancementUser Interface

Community Tools

Generic Document Tools

MyResearchDatabase

Bibliographic Database

Export:RSS, BibtexEndnote etc.

CiteULike

Connotea

Del.icio.us

Bibsonomy

BioliciousPubChem

PubMed

TraditionalCyberinfrastructure

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Chemical Informatics as a Grid Application Chemical Informatics is the application of information technology to

problems in chemistry.• Example problems: managing data in large scale drug discovery

and molecular modeling Building Blocks: Chemical Informatics Resources:

• Chemical databases maintained by various groups NIH PubChem, NIH DTP, http://nihroadmap.nih.gov/

• Application codes (both commercial and open source) Data mining such as clustering Quantum chemistry and molecular modeling

• Screening centers (with HTS High Throughput Screening devices) measuring interaction of chemicals with biological samples

• Visualization tools• Web resources: journal articles, etc.

Chemical Informatics Grid http://www.chembiogrid.org needs to integrate these into a common, loosely coupled, distributed computing environment.

Oracle Database (HTS)

Compounds were tested against related assays and showed activity, including

selectivity within target families

Oracle Database (Genomics)

? None of these compounds have been tested in a

microarray assay

Computation

The information in the structures and known activity data is good enough to create

a QSAR model with a confidence of 75%

External Database (Patent)

Some structures with a similarity > 0.75 to these

appear to be covered by a patent held by a competitor

Computation

All the compounds pass the Lipinksi Rule of Five and

toxicity filters

Excel Spreadsheet (Toxicity)

One of the compounds was previously tested for

toxicology and was found to have no liver toxicity

Word Document (Chemistry)

Several of the compounds had been followed up in a

previous project, and solubility problems prevented further

development

Journal Article

A recent journal article reported the effectiveness of some compounds in a related series against a target in the same family

Word Document (Marketing)

A report by a team in Marketing casts doubt on

whether the market for this target is big enough to make development cost-effective

SCIENTIST

“These compounds look promising from their HTS results. Should I commit some

chemistry resources to following them up?”

?

Document, Simulation and Data rich CI for Chemical Informatics

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HTS results and COMPARE Web service

Positive results (red bar to right of vertical line) indicates greater than average toxicity of cell line to tested agent.

http://dtp.nci.nih.gov/docs/compare/compare.html

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HTS data organization & flagging

A tumor cell line is selected. The activity results for all the compounds in the DTP database in the given range are extracted from the PostgreSQL database

The compounds are clustered on chemical structure

similarity, to group similar compounds together

The compounds along with property and cluster information are converted to VOTABLES format and displayed in VOPLOT

OpenEye FILTER is used to calculate biological and chemical properties of the compounds that are related to their potential effectiveness as drugs

Use Taverna for Workflow and VOTable (from astronomy) as basic data structure; VOTable of compounds and properties with

Excel-like spreadsheet services

VOPlot

Taverna

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Varuna environment for molecular modeling (Baik, IU)

QMDatabase

Supercomputer

ResearcherResearcher

Simulation ServiceFORTRAN Code,

Scripts

Chemical Concepts

Experiments

QM/MMDatabasePubChem, PDB,

NCI, etc.

ChemBioGridChemBioGrid

ReactionDB

DB ServiceQueries, Clustering,

Curation, etc.

Papersetc.

Condor

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OSCAR3 Service from Cambridge UK Oscar3 is a tool for shallow, chemistry-specific

natural language parsing of chemical documents (i.e. journal articles).

It identifies (or attempts to identify): Chemical names: singular nouns, plurals, verbs etc., also

formulae and acronyms. Chemical data: Spectra, melting/boiling point, yield etc. in

experimental sections. Other entities: Things like N(5)-C(3) and so on.

Uses SMILES, InChI and CML There is a larger effort, SciBorg, in this area

http://www.cl.cam.ac.uk/~aac10/escience/sciborg.html

http://wwmm.ch.cam.ac.uk/wikis/wwmm/index.php/Oscar3

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OSCAR2 Chemistry Document analysis

It detects “magic” chemical strings in text and then• Stores them as

metadata associated with document

Queries ChemInformatics repositories to tell you lots of information about identified compounds

Tells you which other documents have this compound

Clustering Documents from chemicalproperties

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Provenance and Delicious CI We can use del.icio.us style interface to annotate Application

Data with (extra) provenance and user comments of any type (describing quality of data or a keyword relating different data etc.)• All data should be labeled by a URI to enable this

• One has in addition Citeseer/OSCAR metadata

Current major tagging systems support flat list of tags without name=value (RDF triple) or schema organization• RDF Triples << Full Semantic Web

• Delicious << RDF

• Tradeoff between features and pervasive deployment

Some extra features are easy to add as a custom service Features not supported by del.icio.us can be uploaded as

comments

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Current Status Google Scholar, Windows Live Academic Search, del.icio.us,

Connotea, CiteULike, OSCAR3 are Web Services Debugging on 500 presentations and papers from my CGL

research group Experiment with GGF Presentations, Broad collection of

Chemical Informatics resources (explore science document CI link) and Concurrency&Computation: Practice&Experience Web site (?business model for journals)

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Collection (Grid) Builder Tool This can perhaps be built on top of workflow systems Unlike ordinary workflow, this is a tool to manage collections of

Grids and the key metadata adorning Grids and Services It instantiates needed mediation between Grids (systems) to

convert

• JMS to MQSeries

• GT4 to WS-I+

• WS-Eventing to WS-Notification It supports conventional workflow as tightly coupled services It supports system wide “management” (configuration)

• We are using WS-Management – see CLADE paper Deploy services and mediation brokers on demand to deliver

real-time performance • DoD can’t pause the battle while WS-RM and TCP catch up if data

saturated

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Grids of Grids of Simple Services• Grids are managed collections of one or more services• A simple service is the smallest Grid• Services and Grids are linked by messages• Internally to service, functionalities are linked by methods• Link serices via methods messages streams • We are familiar with method-linked hierarchy

Lines of Code Methods Objects Programs Packages

Overlayand ComposeGrids of Grids

Methods Services Component Grids

CPUs Clusters ComputeResource Grids

MPPs

DatabasesFederatedDatabases

Sensor Sensor Nets

DataResource Grids

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Component Grids? So we build collections of Web Services which we package as

component Grids

• Visualization Grid

• Sensor Grid

• Utility Computing Grid

• Collaboration Grid

• Earthquake Simulation Grid

• Control Room Grid

• Crisis Management Grid

• Drug Discovery Grid

• Bioinformatics Sequence Analysis Grid

• Intelligence Data-mining Grid We build bigger Grids by composing component Grids

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Mediation and Transformation in a Grid of Grids and Simple Services

Po

rtP

ort

Port PortInternal

Interfaces

Grid or Service

Po

rtP

ort

Port PortInternal

Interfaces

Grid or Service

Po

rtP

ort

Port PortInternal

Interfaces

Grid or Service

Mediation andTransformation ServicesDistributed Brokersbetween distributedports

ExternalfacingInterfaces

Mediation andTransformation ServicesListen, QueueTransform, Send

Mediation andTransformation Services1-10 ms OverheadUse “OGSA” toFederate?

Axis2 Performance on Mutlicore Machines

0

10

20

30

40

50

60

70

0 500 1000 1500 2000 2500 3000 3500

Messages per Second

Round T

rip T

ime (m

s) (

ms)

Grid Farm Sun Fire - 6 Cores Sun Fire - 8 Cores HP xw9300 Dell Intel Xeon

2 Chips2 Core/chip

2 Chips1 Core/chip

1 Chip8 Core/chip1 Chip

6 Core/chip

Xeon

Opteron

4 Cores is 3000 messages per second; about one message per millisecond per core for Opteron; one message per 2 ms for Sun Niagara core

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Message Size

Naradabrokering (JMS) to IBM MQ IBM MQ to Naradabrokering (JMS)

In-orderMessages/second

No OrderingMessages/second

In-OrderMessages/second

No OrderingMessages/second

100 Bytes 350 530 320 310

1 Kbytes 330 500 290 290

4 Kbytes 200 390 220 210

Pentium 4 (3.4GHz) with 1GB of RAM while IBM- MQ Series, Naradabrokering and the Message Bridge are all running on it.

NaradaBrokering running in JMS emulation mode

3131Database

SS

SS

SS

SS

SS

SS

SS

SS

SS

SS

FS

FS

FS

FS

FS

FS

FS

FS FS

FS

FS

FS

FS

FS

FS

FS

FS FS

FS

FS

PortalFS

OS

OS

OS

OS

OS

OS

OS

OS

OS

OS

OS

OS

MD

MD

MD

MD

MD

MD

MD

MD

MD

MetaDataFilter Service

Sensor Service

OtherService

AnotherGrid

Raw Data Data Information Knowledge Wisdom

Decisions

SS

SS

AnotherService

AnotherService

SSAnother

Grid SS

AnotherGrid

SS

SS

SS

SS

SS

SS

SS

SS

FS

SOAP Messages

Portal

OS

OS

FS

OS

OS

MD MD

MD

FS