Elastic Cloud Computing Cluster (EC3) is a tool to create elastic virtual clusters on top of Infrastructure as a Service (IaaS) providers, either public (such as Amazon Web Services, Google Cloud or Microsoft Azure) or on-premises (such as OpenNebula and OpenStack). We offer recipes to deploy TORQUE (optionally with MAUI), SLURM, SGE, HTCondor, Mesos, Nomad and Kubernetes clusters that can be self-managed with CLUES: it starts with a single-node cluster and working nodes will be dynamically deployed and provisioned to fit increasing load (number of jobs at the LRMS). Working nodes will be undeployed when they are idle. This introduces a cost-efficient approach for Cluster-based computing.
The target group of the training is developers and administrators of services that want to integrate to ELIXIR AAI for user authentication and authorisation. The training has hands-on sessions for the participants to integrate their own service (or, a test service provided by the trainers) to ELIXIR AAI.
Keywords: AAI, OpenID Connect, Authentication
Target audience: service administrators in organizations that want to make use of ELIXIR AAI
Difficulty level: Intermediate
Authors: Michal Prochazka, Dominik Frantisek Bucik
The main objective of this webinar is to show how the CompBioMed community can use the EOSC services for managing active research data (i.e. data transfer, storage, and sharing) and for preserving final research data (i.e. data archiving and publishing). In this webinar, we give a brief overview of the EUDAT Services and the data life cycle. We further demonstrate how these services operate and integrate with each other to meet the data management requirements of research communities and comply with the FAIR principles – which require the data to be properly documented, annotated, archived, published and accessible to the wider community.
Target audience: community researchers, data managers and the IT support people.
The first tutorial demonstrates the use of cross-linking data from mass spectrometry to guide protein-protein docking in HADDOCK.
The second tutorial illustrates how metadynamics can be used to sample conformations of a binding pocket; those are subsequently used for docking a ligand using HADDOCK. The conformational sampling approach is following the EDES approach described in the following publication:
This webinar will introduce the Service Management System based on the FitSM standard for IT Service Management developed and deployed by EOSC-hub for EOSC, with a particular focus on the Service Portfolio Management as a key and highly strategic process. The structure of the EOSC Service Portfolios will be also presented.
This webinar will describe the Reference Technical Architecture for EOSC proposed by EOSC-hub during the recent EOSC-hub Technical Workshop.
The proposed architecture is based on the concepts of service composability and interoperability. Service categories and relationships between them will be presented. The process to define interoperability guidelines for different technical areas will be also depicted.
Who should attend:
Service providers, Users, members of other EOSC implementation projects including EOSC cluster projects, members of EOSC working groups, European and national e-infrastructures, European and national research infrastructures
Key Takeaways for attendees
EOSC Technical Reference architecture proposed by EOSC-hub
Classification of services within EOSC
Status of the EOSC-hub work to define interoperability guidelines for EOSC macro-features (Federating core, AAI, Cloud and Container computing, FAIR data management, etc.)
DisVis is a software developed in our lab to visualise and quantify the information content of distance restraints between macromolecular complexes. It is open-source and available for download from our Github repository. To facilitate its use, we have developed a web portal for it.
This tutorial demonstrates the use of the DisVis web server. The server makes use of either local resources on our cluster, using the multi-core version of the software, or GPGPU-accelerated grid resources of the EGI to speed up the calculations. It only requires a web browser to work and benefits from the latest developments in the software based on a stable and tested workflow. Next to providing an automated workflow around DisVis, the web server also summarises the DisVis output highlighting relevant information and providing a first overview of the interaction space between the two molecules with images autogenerated in UCSF Chimera.
The case we will be investigating is the interaction between two proteins of the 26S proteasome of S. pombe, PRE5 (UniProtKB: O14250) and PUP2 (UniProtKB: Q9UT97). For this complex seven experimentally determined cross-links (4 ADH & 3 ZL) are available (Leitner et al., 2014). We added two false positive restraints - it is your task to try to identify these! For this, we use DisVis to try to filter out these false positive restraints while assessing the true interaction space between the two chains. We will then use the interaction analysis feature of DisVis that allows for a more complete analysis of the residues putatively involved in the interaction between the two molecules. To do so, we will extract all accessible residues of the two partners, and give the list of residues to DisVis using its interaction analysis feature. Finally, we will show how the restraints can be provided to HADDOCK in order to model the 3D interaction between the 2 partners.
This tutorial will demonstrate the use of HADDOCK for predicting the structure of a protein-protein complex from NMR chemical shift perturbation (CSP) data. Namely, we will dock two E. coli proteins involved in glucose transport: the glucose-specific enzyme IIA (E2A) and the histidine-containing phosphocarrier protein (HPr).
The structures in the free form have been determined using X-ray crystallography (E2A) (PDB ID 1F3G) and NMR spectroscopy (HPr) (PDB ID 1HDN). The structure of the native complex has also been determined with NMR (PDB ID 1GGR).
These NMR experiments have also provided us with an array of data on the interaction itself (chemical shift perturbations, intermolecular NOEs, residual dipolar couplings, and simulated diffusion anisotropy data), which will be useful for the docking. For this tutorial, we will only make use of inteface residues identified from NMR chemical shift perturbation data as described in Wang et al, EMBO J (2000).