Register event
  • International Summer School on Rare Disease Registries and FAIRification of Data

    23 - 27 September 2019

    Roma, Italy

    International Summer School on Rare Disease Registries and FAIRification of Data Registries are key resources in order to increase timely and accurate diagnosis, improve patients management, tailor treatments, facilitate clinical trials, support healthcare planning and speed up research. This course is composed of two training modules: The first module “Rare Disease Registries” starts on September 23 till September 25, 2019, during these three days participants will learn (a) what resources are needed for the establishment / maintenance of a high quality registry (b) the features of successful strategies to ensure (i) long-time sustainability of the registry, (ii) quality, (iii) legal and ethical issues in compliance with the EU General Data Protection Regulation and (iv) FAIR principles The second module “FAIRification of data”, starts on September 26 till September 27, 2019 during these two days participants, working with IT-trainers, will make use case data FAIR. The potential of a FAIR registry, as the basis for cross resource questions, will be demonstrated by executing a query across the use cases that become FAIR. In this part a time slot will be allocated to discuss FAIR data management and FAIR project planning. 2019-09-23 09:00:00 UTC 2019-09-27 18:00:00 UTC European Joint Programme on Rare Diseases (EJP-RD), Istituto Superiore di Sanità of Italy Via Giano della Bella, 34, Roma, Italy Via Giano della Bella, 34 Roma Città Metropolitana di Roma Italy Rare diseases Istituto Superiore di Sanità [] Cliniciansmedical specialistsregistry curatorsdatabase managershealthcare professionals rare disease patients representatives workshops_and_courses first_come_first_servedregistration_of_interest Rare DiseasesRegistryethical issues
  • Practical Data and Software Skills for Reproducible Research Workshops

    2 - 4 October 2019

    Roma, Italy

    Practical Data and Software Skills for Reproducible Research Workshops Two one-day introductory workshops on the skills and technologies you need for publishable and reproducible data-driven science. People can register for one or both workshops. Practical Data Skills Workshop: 2-3 October, 2019 Practical Software Skills Workshop: 3-4 October, 2019 Working with “Big data” is challenging for most researchers and the barriers to publication can be difficult. These workshops introduce free open-source approaches that reduce these challenges and help you deliver research that is more impactful, open, and reproducible. Training will focus on solutions developed by publicly funded cyberinfrastructure developed in the US (CyVerse) and Europe (CyVerse UK, ELIXIR, EOSC, and others). Lessons learned will prepare you with skills you can apply no matter which computing platforms you use. 2019-10-02 14:30:00 UTC 2019-10-04 14:30:00 UTC University of Arkansas in collaboration with Cold Spring Harbor Laboratory, the National Research Council of Italy, Earlham Institute, Center for Research and Technology Hellas (CERTH), the Netherlands eScience Center and the University of Arizona University of Arkansas Rome Center: Palazzo Taverna, Via di Monte Giordano, 36 - 00186 Rome Italy., Roma, Italy University of Arkansas Rome Center: Palazzo Taverna, Via di Monte Giordano, 36 - 00186 Rome Italy. Roma Città Metropolitana di Roma Italy 00186 University of Arkansas Jason Williams (Cold Spring Harbor Laboratory, NY) Email: University of Arkansas Investigators and researchers working in all areas of the life sciences. workshops_and_courses first_come_first_served Open scienceReproducible ResearchData skillsSoftware skills
  • Software Carpentry Workshop

    16 - 18 October 2019

    Heidelberg, Germany

    Software Carpentry Workshop Educators: Malvika Sharan, Georg Zeller, Mike Smith, Thomas Schwarzl, Frank Thommen (HD-HuB), Holger Dinkel Date: 16-10-2019 - 18-10-2019 09:00-18:00 Location: ATC Computer Training Lab, EMBL Heidelberg Contents: Computation is an integral part of today's research as data has grown too large or too complex to be analysed by hand. An ever-growing fraction of science is performed computationally and many wet-lab biologists spend part of their time on the computer. Many scientists struggle with this aspect of research as they have not been properly trained in the necessary set of skills. The result is that too much time is spent using inefficient tools when progress could be faster. This course provides training in several key tools, with a focus on good development practices that encourage efficient and reproducible research computing. Topics covered include: Introduction to Python scripting Introduction to the Unix shell and usage of cluster resources Version control with Git and Github Analysis pipeline management Scientific Python & working with biological data Literate programming with Jupyter notebooks Learning goals: This course aims to teach software writing skills and best practices to researchers in biology who wish to analyse data, and to introduce a toolset that can help them in their work. The goal is to enable them to be more productive and to make their science better and more reproducible. Prerequisites: This is a course for researchers in the life sciences who are using computers for their analyses, even if not full time. The target student will be familiar with some command line/programmatic computer usage, will want to become more confident using these tools efficiently and reproducibly. A target student will have written a for loop in some language before, but will not know what git is (or at least not be very comfortable using git). Keywords: Programming; Command Line; Version Control; Bioinformatics; Data Analysis; Cluster Computing Tools: Python; Bash; Unix/Linux; Git; GitHub; SnakeMake; Biopython; Pandas; Numpy; SciPy; Matplotlib 2019-10-16 09:00:00 UTC 2019-10-18 17:00:00 UTC de.NBI / ELIXIR Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany [] [] [] workshops_and_courses [] []
  • Machine Learning in R

    6 - 7 November 2019

    Heidelberg, Germany

    Machine Learning in R Date Nov 6 - Nov 7 2019 Location EMBL Heidelberg Tutors and helpers - Dr. Malvika Sharan - Prof Bernd Bischl - Martin Binder - Giuseppe Casalicchio Affiliation: Ludwig-Maximilians-University Munich Course Information This two-day course, on the implementation of Machine Learning in R, using mlr package will be delivered as practical sessions on programming and data analysis. The main goal of mlr is to provide a unified interface for machine learning tasks as classification, regression, cluster analysis and survival analysis in R. Sessions will be driven by many practical exercises and case studies. Before this workshop, participants are expected to review the official material introducing the principle of Machine Learning (see the prerequisite). Course Content This 2-day course will cover hands-on sessions using `mlr` and other relevant packages. Daily schedule - 09:30-12:30 3h morning, 90 min Theory + 90 min Practical - 12:30-13:30 1h Lunchbreak - 13:30-16:30 3h afternoon, 90 min Theory + 90 min Practical - 16:30-17:00 Time for general questions Day 1 Introduction to the concepts and Practical with mlr - Performance Evaluation and Resampling (Metrics, CV, ROC) - Introduction to Boosting Day 2 Introduction to the concepts and Practical with mlr - Tuning and Nested Cross-Validation - Regularization and Feature Selection Prerequisite The course is aimed at advanced R programmers, preferably with some knowledge of statistics and data modeling (See prerequisite materials from Day-1, 2, & 4). In this course, our learners will learn more about machine learning and its application and implementation through the hands-on sessions and use cases. Optional: Discussion-Based Session On The Principle of Machine Learning Anna Kreshuk (EMBL Group Leader) will lead a one-day discussion-based session on 14 October 2019 to address your questions on the prerequisite materials on the principle of Machine Learning. This will also allow you to connect with other participants of this workshop informally, and discuss the materials in smaller groups. Please register for this workshop separately: Registration Please register on this page: Please note that the maximum capacity of this course is 40 participants and registration is required to secure a place. If you have any questions, please contact Malvika Sharan. In your registration, please mention your EMBL group name, or institute's name (e.g. DKFZ, Uni-HD) if you are registering as an external participant. Costs 60,00 EUR Keywords: Machine Learning, R 2019-11-06 09:00:00 UTC 2019-11-07 17:00:00 UTC de.NBI Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany [] [] [] workshops_and_courses [] []
  • Translational Medicine Explained course

    11 - 15 November 2019

    Barcelona, Spain

    Elixir node event
    Translational Medicine Explained course Interested in discovering the landscape of Translational Medicine? Want to learn about the job profiles of scientists in Industry? Then join the 2019 Winter school “Translational Medicine Explained (TMex)” which will be held in the beautiful Palau Macaya in Barcelona from… The post Translational Medicine Explained course appeared first on Dutch Techcentre for Life Sciences. 2019-11-11 09:00:00 UTC 2019-11-15 00:00:00 UTC Barcelona, Spain, Barcelona, Spain Barcelona, Spain Barcelona Spain [] [] [] workshops_and_courses [] []
  • Constraint-based modelling: introduction and advanced topics

    25 - 29 November 2019

    Leiden University, Netherlands

    Elixir node event
    Constraint-based modelling: introduction and advanced topics Constraint-based modeling is a powerful modeling methodology that is being used to model a diverse range of biological phenomena. These include both fundamental and applied questions relevant to biotechnology, microbiology and medicine. Central to constraint-based modeling is the use of… The post Constraint-based modelling: introduction and advanced topics appeared first on Dutch Techcentre for Life Sciences. 2019-11-25 09:00:00 UTC 2019-11-29 00:00:00 UTC Leiden University, Leiden, the Netherlands, Leiden University, Netherlands Leiden University, Leiden, the Netherlands Leiden University Netherlands [] [] [] workshops_and_courses [] []
  • Advances in Computational Biology Conference 2019

    28 - 29 November 2019

    Barcelona, Spain

    Elixir node event
    Advances in Computational Biology Conference 2019 The first **Advances in Computational Biology conference – _Fostering collaboration among women scientists_** will bring together researchers working on systems biology, omics technologies, artificial intelligence and high-performance computing with applications to biology from both the public and private sectors. One of the main purposes of the conference is to **visualize and promote the research done by women scientists** and for this reason, all presenters will be women, although the conference is open to everyone. We want to create a space to foster collaborations between scientists, providing an excellent opportunity to share ideas and build research networks. Topics included: - **Learning from Biological Sequences**: population genomics, evolutionary genomics, systems biology, transcriptomics, sequence analysis - **When Computational Biology meets Medicine**: biomedical applications, mutational landscapes, clinical genomics - **Machines Speeding up Research**: high performance computing, machine learning in the life sciences, imaging data analysis, dynamic simulations and algorithm development Key dates: - Open registration: May 6th, 2019 - Abstract submission opens: May 6th, 2019 - **Abstract submission deadline: July 1st, 2019** - Early bird registration deadline: September 15th, 2019 - Registration deadline: November 1st, 2019 - AdvCompBio Conference: November 28th - 29th, 2019 The programme will include poster and oral presentations, as well as keynotes from leading scientists in the computational biology and high-performance computing fields. The keynote speakers of the conference are: **Christine Orengo**, group leader of Orengo Group at University College London, **Natasa Przulj**, group leader of the Life Sciences – Integrative Computational Network Biology at the Barcelona Supercomputing Center and **Marie-Christine Sawley**, director of the Exascale Lab at Intel. The confirmed chairs of the conference are: **Alison Kennedy**, director of the STFC Hartree Centre, **Janet Kelso**, group leader of the Minerva Research Group for Bioinformatics at the Max Planck Institute for Evolutionary Anthropology, and **Nuria Lopez-Bigas**, leader of the Biomedical Genomics Research Group at the Institute for Research in Biomedicine Barcelona. Furthermore, the participants will have the opportunity to interact personally with female leaders in the fields of IT, academic research and politics that support the conference. The conference is organised by the Bioinfo4Women programme from the Barcelona Supercomputing Center (BSC-CNS) with the collaboration of IMIM-UPF Research Programme on Biomedical Informatics (GRIB), the Spanish National Bioinformatics Institute (INB/ELIXIR-ES) and the Universitat Politècnica de Catalunya (UPC). It is an affiliate conference of the International Society for Computational Biology (ISCB). 2019-11-28 09:00:00 UTC 2019-11-29 17:00:00 UTC La Pedrera, 92, Passeig de Gràcia, Barcelona, Spain La Pedrera, 92, Passeig de Gràcia Barcelona Barcelona Spain Imaging Machine learning Computational biology Computer science Biomedical science Sequence analysis Transcriptomics Evolutionary biology Population genomics Omics Systems biology Bioinformatics [] [] ResearchersPhD studentsPostdoctoral studentsComputer scienceComputational biologistsbioinformaticians meetings_and_conferences [] HPCBioinformaticsComputational BiologyArtificial IntelligenceGenomicsTranscriptomicsSystems biologyPopulation GenomicsEvolutinary genomicsSequence Analysisbiomedical applicationsmutational landscapesclinical genomicsImagingdynamic simulationsalgorithmsmachine learning
Note, this map only displays events that have geolocation information in TeSS.
For the complete list of events in TeSS, click the grid tab.