West-Life: A VRE for Structural Biology Alexandre Bonvin, Utrecht University Chris Morris STFC EGI Community Forum Bari, November

Background West-Life: Life Sciences in the Cloud

Structural Biologists are mature computer users First use of digital computers in 1940s Protein Data Bank Log new entries by year

New scientific goals Larger macromolecular machines Membrane association 4D (structure + dynamics) Transient interactions

INSTRUCT user survey 73% working on eukaryotic rather than prokaryotic systems 84% working on complexes rather than single gene products Each research team routinely uses three-four different techniques 83% would use combined SB techniques more often if it was easier to get access to experimental facilities 73% of the cases found it hard to combine software tools for different techniques in integrated workflows

New experimental methods Combined techniques Users are not always experts Small samples Data noisy and incomplete Deliver results to other life scientists  Calls for integrative, user-friendly solutions

Crowdsourcing from the middle tier Community includes: – Life scientists who use computers – End user programmers – Algorithm developers We aim at easing the process of creating web- based services

The Project West-Life: Life Sciences in the Cloud

10 Partners: o STFC (UK) (lead partner, Martyn Winn Coordinator) o Dutch Cancer Institute (NKI) (NL) o EMBL (DE) o Masaryk University (MU) (CZ) o Consejo Superior De Investigaciones Cientificas (CSIC) (ES) o Consorzio Interuniversitario Risonanze Magnetiche Di Metallo Proteine (CIRMPP) (IT) o INSTRUCT (UK) o Utrecht University (NL) o Luna (FR) – (SME) o INFN (IT) The project Budget: € Duration: 36 months Started: 1 Nov 2015 Proposal ID

Support for combined techniques: – Multiple facilities visited for one project – Data management challenges inc. provenance – New algorithms needed for integrative approaches – Extends weNMR, uses iCAT, EGI and EUDAT resources – Will integrate and connect the already available services Main Concepts

Main objectives 1.Provide analysis solutions for the different Structural Biology approaches 2.Provide automated pipelines to handle multi-technique datasets in an integrative manner 3.Provide integrated data management for single and multi-technique projects, based on existing e- infrastructure 4.Foster best practices, collaboration and training of end users

Main Concepts

Ideas Challenges Requirements West-Life: Life Sciences in the Cloud

Structural Biology Work Bench Seamless data transfer between stages Accumulate metadata without user intervention No installation effort Extensible Data management should be combined with data processing

Reinvent nothing Existing best practise includes: – weNMR – PaNData – Diamond: pipelines and archives – Scipion – Data Life Cycle Lab Integration, not competition

Processing requirements Datasets may be scattered NMR, MX: Parameter sweeps and embarrassingly parallel models EM class assignment: IO intensive One can estimate the total demand, but it is hard to predict peak demand E-Infra requirements submitted to EGI, together with the MoBrain CC, WeNMR and N4U

New data challenges Data volume: – Combined output of European SB facilities > LHC – XFEL will double it Improve archiving of data and metadata Support for data moving / replication Improve automated pipelines for MX … create pipelines for other techniques

New data challenges Reproducibility – Keywords, version numbers – Archive software to ensure reproducibility, e.g. in Cloud VMs? Combined algorithms Quality indications

Data requirements Raw experimental data -> reduced data -> structure Large experimental facilities have own resource … small ones need help Automatically record provenance metadata when data used

AAI requirements Saved sessions, data access – “I am the person you gave these credentials to…” Collaborations – “I am the person you think I am” Remote experiments – “I am definitely the person you think I am” Personal certificates – Implausible that our community would use them at broad (but examples within WeNMR)

? Cryo-EM ISGC 2016 in Taipei

Supplementary material

Current AAI status WeNMR uses SSO – – Accepts eduGAIN and social media id Experimental facilities issue userids – Moving to Moonshot / Umbrella integration with eduGAIN – Check passports at gate – … but moving to remote access Instruct issues userids – Moving to Moonshot / Umbrella integration with eduGAIN – Verifies identity by phone call to PI (small community) West-Life not started yet

AAI solutions Solution for homeless users – create a local id without associating it with a homeid – We have colleagues not in eduGAIN Solutions to handle user attributes – Stored locally – updates are checked by administrator Preferred technology – Shibboleth has become standard – SAML probably sufficient for authorization Web access, with delegation

References Biasini et al. (2013). Acta Cryst. D69, Gutmanas et al. (2013). Acta Cryst. D69, Karaca, E. & Bonvin, A. M. J. J. (2013). Acta Cryst. D69, Marabini, et al. (2013). Acta Cryst. D69, Morris, C. & Segal, J. (2012). IEEE Software, 29, Perrakis et al. J. Struct. Biol. 175, DiMaio et al., Nature Methods, Improved protein crystal structures at low resolution by integrated refinement with Phenix and Rosetta, in press