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France-Korea Particle Physics Laboratory: an International Associated Laboratory for e- science and particle physics V. Breton CNRS-IN2P3.

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Presentation on theme: "France-Korea Particle Physics Laboratory: an International Associated Laboratory for e- science and particle physics V. Breton CNRS-IN2P3."— Presentation transcript:

1 France-Korea Particle Physics Laboratory: an International Associated Laboratory for e- science and particle physics V. Breton CNRS-IN2P3

2 July 18th 2008 – V. Breton Table of content What is a LIA ? Example: the FKPPL Introduction to grids Grid-enabled virtual screening: the example of WISDOM Conclusion

3 July 18th 2008 – V. Breton International Associated Laboratory – LIA (1/3) An LIA is a "laboratory without walls" and is not a legal entity. It brings together laboratories from CNRS and from one other country. These laboratories contribute human and material resources to a common, jointly-defined project designed to "add value" to their individual pursuits. An LIA agreement is for 4 years, renewable twice.

4 July 18th 2008 – V. Breton LIA(2/3) The laboratories comprising an LIA retain their independence, their regular status, their director and their separate locations. –Co-directors of the LIA are appointed if so desired. An LIA receives earmarked funding from the CNRS and the partner institutions, for equipment, scientific missions, associate research positions, etc. It is coordinated by a scientific management committee, which determines the research program to be submitted to the steering committee. The latter is composed of representatives of the two partner institutions as well as established scientists from outside the LIA.

5 July 18th 2008 – V. Breton LIA(3/3) When to apply for LIA status? –Proposals for the creation of an LIA may be filled at any time with a laboratory's scientific department. Who makes the decision to approve an LIA proposal? –The decision to create an LIA is made by the CNRS and its foreign partner institution. When the proposal has been accepted, an agreement is established between the Director General of the CNRS and the supervisory board of the partner institution

6 July 18th 2008 – V. Breton A brief history 2005 –December: first contacts between François Le Diberder, Do-Won Kim and Marianne Noël  François Le Diberder: deputy director of CNRS Institute of Nuclear and Particle Physics  Do-Won Kim: professor of physics at Kangnung University  Marianne Noël: Attache for science and technology at French embassy in Seoul 2007 –April : signature of CNRS – KISTI MoU during the 3rd session of the Korea-France joint committee for scientific and technological cooperation –November : Visit to Korea of Blaise Pascal University president –December : François le Diberder visit to Korea - addition of new partners and of a new project on ILC microelectronics 2008 –March 20th 2008: signature of the LIA creation document at the French Embassy in Seoul

7 July 18th 2008 – V. Breton Partners Korean partners –KISTI (Daejeon) –Chonnam National University (Gwangju) –EWHA Womans University (Seoul) –Kangnung National University –Korea Institute of Radiological and Medical Sciences (Seoul) –Pohang Accelerator Laboratory (Seoul) –Sung Kyun Kwan University French partners –CNRS –Blaise Pascal University (Clermont-Ferrand) –University Paris XI (Orsay) –Ecole Polytechnique (Palaiseau)

8 July 18th 2008 – V. Breton FKPPL management Steering Committee members –Professor Dong-Pil Min (Seoul National University), co-chairman –Professor François Le Diberder (Stanford University), co- chairman –Professor YungE Earm, Seoul National University –Doctor Jysoo Lee, KISTI –Doctor Mannque Rho, CEA –Doctor Jean-Eudes Augustin, CNRS-IN2P3 –Professor Alain Baldit, University Blaise Pascal –Doctor Dominique Boutigny, CC-IN2P3 Co-directors –Doctor O. Byeon, KISTI –V.B., CNRS-IN2P3

9 July 18th 2008 – V. Breton FKPPL scientific projects FKPPL focusses on particle physics and e-science –Both require international collaboration –Particle physics is the first user community to have completely adopted the grid technology Project nameCoordinatorsPartnersStatus ILC calorimeterYongmann Yang, EWHA Jean-Claude Brient, LLR EWHA Womans Univ., Kangnung Nat. Univ.,LPC, LLR Approved ILC microelectronics Jongseo Chai, SKKU Christophe de la Taille, LAL Sung Kyun Kwan Univ., Korea Institute of Radiological and medical Sciencces, Pohang Accel. Lab. LAL, LLR Approved Grid computingS. Hwang, KISTI D. Boutigny, CC-IN2P3 KISTI, CC-IN2P3Approved WISDOMDoman Kim, CNU V. Breton, LPC Chonnam Nat. Univ., KISTI, Kangnung Nat. Univ., LPC Approved ALICEYongwook Baek, KNU Pascal Dupieux, LPC Kangnung Nat. Univ. LPCSubmitted CDFKihyeon Cho, KISTI Aurore Savoy-Navarro, LPNHE KISTI, LPNHESubmitted

10 July 18th 2008 – V. Breton What is a grid ? a fully distributed, dynamically reconfigurable, scalable and autonomous infrastructure to provide location independent, pervasive, reliable, secure and efficient access to a coordinated set of services encapsulating and virtualizing resources (computing power, storage, instruments, data, etc.) in order to support problem solving and knowledge generation across multiple administrative domains.

11 July 18th 2008 – V. Breton The different kinds of grids Computing Grid For data crunching applications Knowledge Grid Intelligent use of Data Grid for knowledge creation and tools provisions to all users Data Grid Distributed and optimized storage of large amounts of accessible data ICT for Health, ISTAG WG, March 2004 Computing grids provide resources for intensive calculations –Particularly intestesting for embarassingly parallel computations (Monte- Carlo) –Currently used for docking and molecular dynamics Data Grids allow distributed and secured storage and access to biochemical data –Databases (Zinc, PDB) Knowledge grid are about information management –Goal: allow end users to access all the computing and data resources of the grids while manipulating concepts they are familiar with –Requirements: data interoperability and ontologies

12 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 12 Enabling Grids for E-sciencE EGEE-II INFSO-RI-031688 EGEE Grid Infrastructure Flagship European grid infrastructure project Now in 3rd phase with more than 100 partners Size of the infrastructure today: > 250 sites in 48 countries One in Korea (KISTI) > 70 000 CPU cores ~ 5 PB disk + tape MSS > 150 000 jobs/day > 9000 registered users

13 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 6 scientific disciplines are routinely using the EGEE grid –>100 applications deployed 6/20062/20071/2008 Astron. & Astrophysics289 Comp. Chemistry62721 Earth Science16 18 Fusion234 High-Energy Physics9117 Life Sciences233937 Others41421 Total62118117 13 Scientific Applications on EGEE Condensed Matter Physics Comp. Fluid Dynamics Computer Science/Tools Civil Protection

14 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 Computational Chemistry Becoming the second user of the infrastructure after High Energy Physics 14

15 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 Computational chemistry on EGEE Software deployed on the grid –Free sofware: GAMESS, COLUMBUS, DL_POLY, RWAVEP or ABCtraj –Licensed software: Amber, Gaussian, Turbomole and Wien2K Contact point: Mariusz Sterzel, CYFRONET, m.sterzel@cyf- kr.edu.pl

16 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 16 Enabling Grids for E-sciencE WISDOM In silico Drug Discovery WISDOM: http://wisdom.healthgrid.org/http://wisdom.healthgrid.org/ Goal: find new drugs for neglected and emerging diseases –Neglected diseases lack R&D –Emerging diseases require very rapid response time Need for an optimized environment –To achieve production in a limited time –To optimize performances Method: grid-enabled virtual docking –Cheaper than in vitro tests –Faster than in vitro tests

17 July 18th 2008 – V. Breton 17 WISDOM partners Laboratories with expertise in grid technology –KISTI in Korea “Wet” laboratories for in vitro and in vivo studies –Chonnam national University Univ. Los Andes: Biological targets, Malaria biology LPC Clermont-Ferrand: Biomedical grid SCAI Fraunhofer: Knowledge extraction, Chemoinformatics Univ. Modena: Biological targets, Molecular Dynamics ITB CNR: Bioinformatics, Molecular modelling Univ. Pretoria / CSIR: Bioinformatics, Malaria biology Academia Sinica: Grid user interface Biological targets In vitro testing HealthGrid: Biomedical grid, Dissemination CEA, Acamba project: Biological targets, Chemogenomics Chonnam nat. univ.: In vitro testing Mahidol Univ.: Biochemistry, in vitro testing KISTI: Grid technology

18 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 18 Application to life sciences, J. Montagnat, June 18, 2008 Enabling Grids for E-sciencE EGEE-II INFSO-RI-031688 18 High Throughput Virtual Docking Chemical compounds : Chembridge – 500,000 Drug like – 500,000 Targets : Plasmepsin II (1lee, 1lf2, 1lf3)‏ Plasmepsin IV (1ls5)‏ Millions of chemical compounds available in laboratories High Throughput Screening 1-10$/compound, nearly impossible Molecular docking (FlexX, Autodock)‏ ~80 CPU years, 1 TB data Computational data challenge ~6 weeks on ~1000/1600 computers Hits screening using assays performed on living cells Chemical compounds : ZINC Molecular docking : FlexX, Autodock Targets structures : PDB Grid infrastructure : EGEE Leads Clinical testing Drug

19 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 FLEXX/ AUTODOCK Catalytic aspartic residues AMBER CHIMERA WET LABORATORY Molecular docking Molecular dynamics Complex visualization in vitro in vivo Virtual screening pipeline 19

20 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 20 Healthgrid … – March 8th, 2007 – V. Breton Enabling Grids for E-sciencE INFSO-RI-508833 20 The present WISDOM architecture Credit: J. Salzeman, V. Bloch Major new features: - improved data management - secure storage - migration to web service

21 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 21 Healthgrid … – March 8th, 2007 – V. Breton Enabling Grids for E-sciencE INFSO-RI-508833 21 WISDOM-II: A huge international effort Significant contributions from several International grid infrastructures Over 420 CPU years in 10 weeks A record throughput of 100.000 docked compounds per hour

22 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 MD refinement using Amber AntechamberLeapSander Min Sander MD Ptraj MMPBSA Mol2 prepi Target +prepi top, crd min.rst md.rst Output toppdb, top Output Final output appended into a file Preparatory PhaseSimulation Phase Re-ranking and Analysis Phase A. Ferrari, G. Degliesposti, M. Sgobba, G. Rastelli. Validation of an automated procedure for the prediction of relative free energies of binding on a set of aldose reductase inhibitors. Bioorganic & Medicinal Chemistry. 2007. In Press. Best hits from docking step based on: Docking energy Docked pose For one complete simulation, all necessary steps are embedded in one single script.

23 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 Grid Performances for MD 25, 000 compounds: Plasmepsin: 5000 compounds Pf-DHFR: 15,000 compounds Pf-GST: 5000 compounds Number of Jobs500 Total Number of compounds simulated 25000 Estimated duration on 1 CPU347 days Duration on the grid25 days Maximum number of concurrent running jobs 90 Number of computing elements used1 Average duration of a job16.6 hours

24 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 Virtual screening on the grid: deployment status DatesTarget (s) CPU consumed EGEE AuverGrid Data produced Specific featuresStatus Summer 2005 Malaria: plasmepines 80 years1TB First data challenge In vitro tests In vivo tests Spring 2006 Avian flu: Neuraminidase N1 100 years*800 GB <45 days needed for preparation In vitro tests Winter 2006 Malaria: GST, DHFR, Tubulin 400 years1,6TB > 100.000 dockings / hr Analyzed,ready for in vitro tests Fall 2007 Avian flu: Neuraminidase N1 Estimated 100 CPU years* Estimated 800 GB* Joint deployment on CNGrid Under analysis Spring 2008 Diabetes: amylase Estimated 120 CPU years Estimated 800 GB New production environment Under way Summer 2008 Malaria: DHPS To be estimated Joint deployment on desktop grid In preparation

25 V. Breton, July 18th 2008 Enabling Grids for E-sciencE INFSO-RI-508833 KISTI contribution to WISDOM E-science division –Partner of EGEE-III (European project) –Contact point: S. Hwang, hwang@kisti.re.kr Improve data management services on EGEE Improvement to the WISDOM production environment –Allow the use of several biochemical data servers Deploy large scale docking computations on amylase –Collaboration with CNU and LPC Clermont-Ferrand DrugScreener-G –Goal: provide a user-friendly integrated environment for Grid-based large-scale virtual screening for users without much knowledge of Grid computing –Target users: Bioinformaticians, Biologists, Drug Chemists –Contact point: Jincheol Kim, e-science division, KISTI, jin.cheol.kim@kisti.re.kr

26 DrugScreener-G : Architecture

27 July 18th 2008 – V. Breton CNU contribution to WISDOM Lab. of Functional Carbohydrate Enzyme and Microbial Genomics, led by Prof. D. Kim (dmkim@jnu.ac.kr) –Partner of EGEE-III (European project) –Partner of STAR project (Korea-France funding program) In vitro test of the best compounds selected in silico on the grid –Malaria: 6/30 compounds similar or better than PepstatinA on plasmepsin target –Avian flu: 20% of compounds better than Tamiflu on neuraminidase N1 target –Best compounds patented in Korea Search for new drugs against diabetes –First target studied: amylase

28 July 18th 2008 – V. Breton Summary of the existing collaborations on grids Bilateral agreements –Memorandum of Understanding between Chonnam Nat. Univ. and Univ. B. Pascal, Kangnung Nat. Univ. and Univ. B. Pascal –STAR project( CNU, KNU, CNRS) –International Associated Laboratory FKPPL (CNU, KISTI, CNRS, Univ. Blaise Pascal) EU project –KISTI, CNU involved in the EGEE-III project (FP7) with CNRS and Univ. B. Pascal  Participation to the Life Sciences cluster of EGEE-III

29 July 18th 2008 – V. Breton Conclusion The FKPPL LIA offers a framework for collaboration on particle physics and e-science between Korea and France –July 14 – 25: Grid school at Seoul National University  Installation of grid services  User tutorial  Advanced tools for data analysis –July 21 : first FKPPL Steering Committee meeting Grids are under adoption by the Computational Chemistry community –Popular software like Amber, Gaussian deployed on EGEE grid –Well fitted for embarrassingly parallel applications (Monte-Carlo) –Potential limitations:  Licensing issues  Memory < 2GB / node

30 July 18th 2008 – V. Breton Perspectives In France –French Ministry of Research has organized a wide consultation for the deployment of a multidisciplinary grid for scientific production –Contribution of the Computational Chemistry community is important –Contact point: Guy Wormser, director of Institut des Grilles, wormser@lal.in2P3.fr In Korea –First grid school in Seoul currently going on –Deployment of grid nodes foreseen in Korean universities –Contact point: Dr Soonwook Hwang, KISTI, hwang@kisti.re.kr

31 July 18th 2008 – V. Breton PCSV group at LPC Clermont-Ferrand (together with HealthGrid association)


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