CryoEM: From Biomedical impact to Cloud deployment. Laura del Caño Jesús Cuenca CNB CSIC, Madrid
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1 CryoEM: From Biomedical impact to Cloud deployment Laura del Caño Jesús Cuenca CNB CSIC, Madrid
2 How can one see a virus?
3 250 nm Confocal optical microscope
4 0.1 nm (1 Å) X-ray crystallography
5 0.5 nm (5 Å) From small amounts of diluted samples, it is possible to solve......the structure of large and flexible macromolecular complexes... without 3D crystals.
6 Structural and molecular basis for Ebola virus neutralization by protective human antibodies Misasi et al. Science 351(6279), (2016)
7 MICROGRAPHS BIM correction MOVIES CTF estimation CTF Particle Picking Single Particle Analysis (SPA) COORDINATES Preprocessing Postprocessing 2D Classification 3D Refinement 2D CLASSES Validation Estimate resolution 3D CLASSES Initial Model VOLUME REFINED VOLUME 3D classification
8
9
10 Cluster Edition Cloud Edition Desktop Edition Web Tools
11 Desktop Edition
12
13 Web Tools
14
15 box
16
17 Scipion cluster edition Cluster Edition Universität Basel (Switzerland) NCPS (Shanghai) EPFL (Switzerland) Utah University (USA) IMM (France) Columbia University (USA) Politecnico de Torino (Italy) CIC-Biogune (Spain)
18
19 Towards Scipion on the Cloud
20 Application User data Libraries Low-level middleware Operating system Brick Brick Virtual servers farm VM VM VM VM VM Virtualization layer SAN Real servers farm SaaS (Software) Central installation Web access: easy & on demand Billing PaaS (Platform) Standard software framework Built-in scalability and failover Predefined deployment cycle Billing IaaS (Infrastructure) Distributed resources: lots of servers and storage across datacenters (across the world) Elastic computing: dynamic scaling to handle peaks Resource pooling: real infrastructure is share by all the IaaS users Billing: variable cost (as function of resource use) CLOUD SCENARIOS
21 Objective Lower barriers for scientists to access modern e-science solutions from micro to macro scales. Grid & cloud based infrastructures. Task 2 Cryo-EM in the cloud: bringing clouds to the data. A Competence Center to Serve Translational Research from Molecule to Brain.
22 ENMR.eu VO Deployment for CryoEM processing
23 Sara HPC Cloud Deployment for CryoEM processing
24 Sara HPC Cloud Deployment for Instruct training
25 Objective Bring the world of complex data analysis in Structural Biology to a simple Web browser-based Virtual Research Environment. Task 2 Integration of existing Cryo-EM web services, Scipion Web Tools, on the VRE. World-wide E-infrastructure for structural biology
26 ENMR.eu VO Scipion Web Tools Deployment
27 Install and test Scipion on AWS EC2 platform. Create Scipion AMI (not public yet). Test StarCluster (Elastic Cloud images)
28 Our experience The cloud paradigm is quite different from legacy HPC, but we were able to deploy successfully Remote visualization Cloud architecture for legacy HPC (1.0) Images for cloud (beta)
29 Challenges Elastic cloud Image publishing to independent repositories Image contextualization Big data transfers Fault-Tolerant High Performance filesystems Security
30 Our vision: Scipion Ubiquity 1-click instances in research and commercial clouds: simple provisioning for Scipion showcase & training SaaS: Scipion Web Tools Ready for every client profile / infrastructure: traditional HPC facilities ( owners ) research clouds (paper per use) commercial clouds (pay per use)
31 Further info Structural and molecular basis for Ebola virus neutralization by protective human antibodies Misasi et al. Science 351(6279), (2016) Structures of protective antibodies reveal sites of vulnerability on Ebola virus. Murin et al. PNAS 111(48), (2014) Camouflage and Misdirection: The Full-On Assault of Ebola Virus Disease. Misasi et al. Cell 159(3), (2014) Electron counting and beam-induced motion correction enable near-atomicresolution single-particle cryo-em. Li et al. Nature Methods 10, (2013)
32 Further info Scipion - INSTRUCT - MoBrain project - Westlife project - StarCluster - Infrastructure Manager - Elastic Cloud Computing (EC3):
33 Acknowledgements Miguel Caballer (UPV) Enol Fernandez (EGI.eu) Boris Parak (CESNET) Nuno Ferreira (SURFsara)
34 Laura del Caño Jesús Cuenca-Alba i2pc.cnb.csic.es Follow us on
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