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  • FLAMES Summer School

    9 - 20 September 2019

    Gent, Belgium

    FLAMES Summer School FLAMES (Flanders Training Network for Methodology and Statistics) organizes a two-week Summer School aiming at providing practical methodological and statistical training to young researchers (particularly PhD students) from all disciplines. After the success of the FLAMES Summer School in 2013 (at KULeuven), 2014 (at UGent), 2015 (at VUB), 2016 (at UHasselt) , 2017 (at UAntwerp) and 2018 (at KULeuven) we are going to offer and even broader variety of courses from top lecturers around the world. Whether you are a complete dummy, a starter with a limited knowledge, or a more experienced researcher with a broad basic knowledge in the world of methodology and statistics, the FLAMES summer school offers courses at your level, which emphasizes everyday research practice. The program consists of 23 courses (called modules) from which participants can choose. Each module seamlessly connects theory with hands-on exercises or lab sessions, focusing on various disciplines and software packages whenever possible. The basic courses are combined in 2 recommended tracks, that directly connect to the prior knowledge of the participant. This year the FLAMES Summer School will take place at Gent University, De Sterre. 2019-09-09 09:00:00 UTC 2019-09-20 17:00:00 UTC Krijgslaan 281, Gent, Belgium Krijgslaan 281 Gent Oost-Vlaanderen Belgium Ghent University [] [] workshops_and_courses registration_of_interest []
  • Microscopy Image Analysis Course

    19 - 20 September 2019

    Heidelberg, Germany

    Microscopy Image Analysis Course Educators: Karl Rohr, Thomas Wollmann, Manuel Gunkel (HD-HuB), Qi Gao, Leonid Kostrykin Date: 19.-20.9.2019 Location: Heidelberg University IPMB (Institute of Pharmacy and Molecular Biotechnology) Im Neuenheimer Feld 364 Contents: The course gives an introduction into the field of microscopy image analysis for cell biology and the use of software tools for automated processing of image data. Basic methods for computer-based analysis of microscopy images are introduced such as image preprocessing, segmentation, feature extraction, classification, colocalization, and tracking. Concepts of software platforms with focus on ImageJ and their use for analyzing cell microscopy image data are also taught. Workflow systems for automating image analysis pipelines are also considered (e.g., KNIME, Galaxy). The course consists of lectures and practical sessions. Participants should bring their laptops for the practical sessions. The target group are researchers with a background in biology or medicine that need to analyze their data and have little or no experience in automated image analysis. Learning goals: - Introduction into cell microscopy image analysis - Application of software tools for automated analysis of image data Prerequisites: Basic knowledge in using software tools for image analysis is helpful but not mandatory Keywords: Computer-based image analysis, image preprocessing, segmentation, feature extraction, classification, colocalization, tracking Tools: Image J Course fee: Participants will be charged with a course fee of 40 Euros (to cover the lunch and infrastructure related cost). The invoice details will be shared via email. Registration: Please register directly on the HD-HuB website: In the "Comments" section of the registration form, please provide some information about yourself and your motivation to attend the training (e.g. Position, Field of study/Background, Topic of work, Knowledge of image analysis methods/tools). Registration closes on August 11, 2019. The capacity is limited to 20 participants and applicants will be selected after registration closed. You will be notified of the outcome by e-mail on August 23, 2019. 2019-09-19 09:00:00 UTC 2019-09-20 17:00:00 UTC de.NBI Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany [] [] [] [] [] []
  • Metabolomics: Understanding Metabolism in the 21st Century

    23 September - 18 October 2019

    Edgbaston, United Kingdom

    Elixir node event
    Metabolomics: Understanding Metabolism in the 21st Century This online course explores metabolomics, an emerging field that aims to measure the complement of metabolites (the metabolome) in living organisms. The metabolome represents the downstream effect of an organism's... 2019-09-23 09:00:00 UTC 2019-10-18 23:59:00 UTC Online, Edgbaston, United Kingdom Online Edgbaston United Kingdom B15 2TT [] [] [] [] [] []
  • 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 [] []
  • CABANA Workshop: Analysis of Crop Genomics Data

    2 - 6 December 2019

    Bogota, Colombia

    Elixir node event
    CABANA Workshop: Analysis of Crop Genomics Data This course will introduce crop biologists to methods and approaches for analysing crop genomics data. 2019-12-02 08:30:00 UTC 2019-12-06 12:45:00 UTC Universidad de los Andes - UniAndes, Bogota, Colombia Universidad de los Andes - UniAndes Bogota Colombia 111711 [] Marco Cristancho [] [] [] [] HDRUK
  • A tour of machine learning: classification

    13 - 14 January 2020

    Gent, Belgium

    Elixir node event
    A tour of machine learning: classification Machine learning has become ubiquitous in biotechnology (as in many other fields), fueled largely by the increasing availability and amount of data. Learning algorithms can figure out how to perform important tasks by generalizing examples. Typical applications are diagnoses/prognoses, gene/protein annotation, drug design, image recognition, text mining and many others. However, building successful machine learning models requires a substantial amount of “black art” that is hard to find in textbooks. This course is an interactive Jupyter Notebook (Python) that will teach you how to build successful machine learning models. No background in machine learning is assumed, just a keen interest. 2020-01-13 09:00:00 UTC 2020-01-14 00:00:00 UTC VIB Bioinformatics Core iGent, Gent, Belgium iGent Gent Belgium 9052 [] [] [] [] [] []
  • Best practices in data management and data stewardship

    27 - 28 January 2020

    Esch-sur-Alzette, Luxembourg

    Best practices in data management and data stewardship 2020-01-27 09:00:00 UTC 2020-01-28 17:00:00 UTC Roland Krause, Pinar Alper Luxembourg Learning Centre, Esch-sur-Alzette, Luxembourg Luxembourg Learning Centre Esch-sur-Alzette Esch-sur-Alzette Luxembourg Workflows Bioinformatics Data management University of Luxembourg ELIXIR-Luxembourg PhD studentspostdoctoral researchersdata stewards 25 [] [] []
  • Mass spectrometry data processing

    2 - 3 June 2020

    Gent, Belgium

    Elixir node event
    Mass spectrometry data processing Obtain a good understanding of the origins and properties of mass spec data Obtain an understanding of the processing of mass spec data, aimed at identifying and quantifying peptides and proteins Gain sufficient understanding of the software tools and database used, and of the issues and caveats involved, to critically analyse and assess results from mass spectrometry based proteomics experiments 2020-06-02 09:00:00 UTC 2020-06-03 00:00:00 UTC VIB Bioinformatics Core iGent, Gent, Belgium iGent Gent Belgium 9052 [] [] [] [] [] []
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