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  • BioSimSpace – filling the gaps between molecular simulation codes

    27 June 2018

    BioSimSpace – filling the gaps between molecular simulation codes https://tess.elixir-europe.org/events/biosimspace-filling-the-gaps-between-molecular-simulation-codes [BioSimSpace](https://biosimspace.org) is a flagship software project from the [CCP-BioSim](https://ccpbiosim.ac.uk) and [HEC-BioSim](https://hecbiosim.ac.uk) biomolecular modelling communities. The project aims to make it easier for researchers to develop, share and re-use biomolecular simulation workflow nodes. The software problem in our community is that we have lots of different pieces of software that are all incompatible and are not interoperable. This forces the community to hand-write small scripts for converting between different file formats, or to generate different software input files. The resulting scripts are specific for the software and task performed, leading to the community generating lots of bespoke and brittle workflows. BioSimSpace solves this problem by providing an **interoperability layer** between the major molecular simulation packages. In effect, BioSimSpace provides the shims that fill in the gaps between codes. BioSimSpace Python scripts can be run from the command line, used as workflow nodes in packages such as Knime, or run on the cloud as Jupyter notebooks. In this talk, we will show how BioSimSpace has been implemented, will talk about its capabilities and our future plans, and will demonstrate some BioSimSpace workflow nodes running on the cloud. 2018-06-27 15:00:00 UTC 2018-06-27 16:00:00 UTC BioExcel Molecular modelling Molecular dynamics Workflows University of Manchester [] IntermediateBeginners [] [] GROMACSPythonKNIMEJupyter notebook
  • H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 1

    20 August 2018

    H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 1 https://tess.elixir-europe.org/events/h3abionet-2018-genotyping-chip-data-analysis-and-gwas-lecture-series #### Computational requirements for running the H3ABioNet GWAS workflows The first of a series of seven online lectures for Genome Wide Association Studies (GWAS) will cover the technical requirements for setting up a your computational environment for running the H3ABioNet GWAS workflows. In this inaugural lecture of the series, Prof. Hazelhurst will cover the the following topics: Installing and using Nextflow Installing and using Github Use of containers for packaging and running tools Pulling the GWAS pipeline from Github and running it As this lecture aims to provide attendees with an environment to the run the H3ABioNet GWAS workflow at their own pace, there are some preliminary software requirements: Either a Linux machine or an Apple running macOS Ideally you should have machine with at least 2-4 cores and 8GB of RAM. Java 8 Nextflow installed (see installation instructions at https://www.nextflow.io/) Python 3 Please also install either Docker OR the following dependencies using pip3: Pandas, Matplotlib, Openpyxl, SciPy, NumPy PLINK 1.9 [Please also refer to the following documentation to obtain the H3ABioNet GWAS workflow]: https://github.com/h3abionet/h3agwas/blob/master/README.md 2018-08-20 15:00:00 UTC 2018-08-20 16:30:00 UTC H3ABioNet Population genomics Genotyping experiment Computational biology Workflows GWAS study Bioinformatics H3ABioNet info@h3abionet.org H3ABioNet Anyone intersted in GWAS and using the H3Africa genotyping chipAnyone who wants to learn more about GWAS workshops_and_courses [] NextflowDockerH3ABioNetGWASWorkflowsGenotyping array analysis bioinformaticsAfricaPopulation GenomicsReproducible ScienceH3Africa genotyping arrayHigh performance computingCloud computingGWAS workflowH3ABioNet GWAS 2018 Lecture Series
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