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13 events found

Organizer: SIB Swiss Institute of Bioi...  or NanoCommons  or de.NBI 

  • Tools for Systems biology modeling and data exchange: COPASI, CellNetAnalyzer, SABIO-RK, FAIRDOMHub/SEEK 2020

    21 - 23 September 2020

    Tools for Systems biology modeling and data exchange: COPASI, CellNetAnalyzer, SABIO-RK, FAIRDOMHub/SEEK 2020 https://tess.elixir-europe.org/events/hdhd Educators: Axel von Kamp, Steffen Klamt, Sven Thiele (MPI Magdeburg), Frank T. Bergmann, Ursula Kummer (University of Heidelberg), Wolfgang Müller, Maja Rey, Andreas Weidemann, Ulrike Wittig (HITS) (de.NBI-SysBio) Date: 21. - 23 September 2020 Location: MPI Magdeburg Sandtorstrasse 1 39106 Magdeburg or online Contents: Key concepts of stoichiometric and kinetic modeling of biochemical networks: - stoichiometric matrix and stoichiometric networks - steady state flux distributions - principles of constraint-based modeling - metabolic flux analysis and flux optimization (flux balance analysis) - metabolic pathway analysis with elementary flux modes - metabolic network design via minimal cut sets - simulation of dynamic (kinetic) models - sensitivity analysis - carrying out parameter estimation tasks - model exchange using SBML Data and model management: - manual/programmatic access to reaction kinetics data from SABIO-RK - storage and exchange of data and models using FAIRDOMHub/SEEK - modeling specific functionalities in FAIRDOMHub/SEEK Learning goals: During this 3-day course, attendees will learn basic techniques for modeling of biochemical networks including data access and storage due to the FAIR principles. The first day SABIO-RK is used as a resource for kinetic data and FAIRDOMHub/SEEK is introduced as a data and model management platform fitted to the needs of systems biologists. The second day introduces principles of stoichiometric and constraint-based modeling coupled with hands on exercises using CellNetAnalyzer. The third day continues with kinetic modeling techniques which will be illustrated and exercised with COPASI The hands on exercises throughout the three days will ensure that attendees become familiar with the software tools and with analyzing, creating, editing, importing, simulating and storing biochemical networks. Prerequisites: Some knowledge of mathematical modeling will be advantageous. The participants should bring their own laptop with MATLAB installed (if you do not have MATLAB please let us know during registration). Download and preinstallation of COPASI and CellNetAnalyzer is recommended but not mandatory. Keywords: CellNetAnalyzer (CNA), COPASI, SBML, FAIR, modeling, kinetic data access, database, data and model management Tools: CellNetAnalyzer, COPASI, Matlab, SABIO-RK, FAIRDOMHub/SEEK 2020-09-21 09:00:00 UTC 2020-09-23 17:00:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • Computational genomics course for hands-on data analysis 2020

    23 - 25 September 2020

    Computational genomics course for hands-on data analysis 2020 https://tess.elixir-europe.org/events/computational-genomics-course-for-hands-on-data-analysis-2020 Educators: Altuna Alkalin, Verdan Franke, Bora Uyar (RBC/deNBI-epi Scientists from Berlin) Date: 23-25 September 2020 Location: Online Contents: The general aim of the course is to equip participants with practical and technical knowledge to analyze single cell RNA-seq data. With this aim in mind, we will go through unsupervised machine learning methods to analyze high-dimensional data sets, and move on to statistical methods developed to analyze bulk RNA-seq. Lastly, we will introduce analysis techniques used for single cell RNA-seq. There will be theoretical lectures followed by practical sessions where students directly apply what they have learned. The programming will be mainly done in R. Day 1: Intro to machine learning & data visualization for genomics Day 2: Bulk RNA-seq analysis Day 3: Single cell RNA-seq analysis Learning goals: The course will be beneficial for first year computational biology PhD students, and experimental biologists and medical scientists who want to begin data analysis or are seeking a better understanding of computational genomics and analysis of popular sequencing methods.r Prerequisites: Some statistics and R programming experience will be good to keep up with the course. Practicals will be done in R. Keywords: Computational genomics, RNA-seq, Machine learing, Tools: R/Bioconductor 2020-09-23 09:00:00 UTC 2020-09-25 17:00:00 UTC de.NBI Berlin, Berlin, Germany Berlin Berlin Germany [] [] [] workshops_and_courses [] []
  • Bioinformatics for Lipidomics – Online Workshop

    1 October 2020

    Bioinformatics for Lipidomics – Online Workshop https://tess.elixir-europe.org/events/bioinformatics-for-lipidomics-online-workshop Educators: Jacobo Miranda Ackerman, Fadi Al Machot, Nils Hoffmann (BioInfra.Prot / LIFS) Date: October 1st, 2020 Deadline for Workshop Registration: September 25th, 2020 Location: Online, virtual workshop as part of the joint European Lipidomics Meeting & Lipidomics Forum 2020. Contents: In the first part of the course, we will work through an example for targeted LC-MS lipidomics with LipidCreator and Skyline. In the second part of the course, we will apply PeakStrainer and LipidXplorer for filtering, identification and quantification of lipid signals from shotgun lipidomics. The course will consist of a short theory and background overview of the employed programs complemented by the application of the tools to provided data sets. The third part of this course will work through a typical use-case of downstream data processing of shotgun lipidomics data following MS acquisition with LipidXplorer. We will inspect, check and normalize the data as well as calculate absolute quantities using internal class-specific standards with lxPostman. We will then perform a qualitative comparison of the lipidomes using the LUX Score lipidome homology. 09:00 – 09:30 Welcome and Introduction 09:30 – 12:00 Targeted Lipidomics with LipidCreator and Skyline 12:00 – 13:00 Break 13:00 – 15:00 Shotgun Lipidomics with PeakStrainer and LipidXplorer 15:00 – 17:00 Downstream processing with lxPostman and lipidome comparison with LUX Score Learning goals: Participants will be able to understand and explain the shotgun MS and targeted LC-MS workflows for lipidomics. They will learn the fundamentals of the software tools used and how to choose parameters for them. They will learn to understand and interpret the results of each step of the pipeline. Prerequisites: Basic knowledge of lipidomics, analytical workflows in lipidomics and basic familiarity with web-based and desktop applications. Please note that you may need to install software on your computer to fully participate in all exercises which may require the proper rights. The workshop will be a mix of small lecture segments and hands-on exercises. The trainers will be available for questions and assistance during the workshop. We will use Zoom to host the workshop. To participate, please ensure that the Zoom client software is installed on your computer. Keywords: Lipidomics, Shotgun, Targeted, LC-MS Tools: PeakStrainer and LipidXplorer, LipidCreator, Skyline, lxPostman, LUX Score 2020-10-01 09:00:00 UTC 2020-10-01 17:00:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • 3rd de.NBI Cloud Usermeeting

    8 - 14 October 2020

    3rd de.NBI Cloud Usermeeting https://tess.elixir-europe.org/events/3rd-de-nbi-cloud-usermeeting 3rd de.NBI Cloud Usermeeting Online Educators: de.NBI cloud group including Peter Belmann, Daniel Hübschmann, Peter Ebert, Martin Zurowietz, Kay Schallert, Sven Olaf Twardziok, Jan Krüger, Maximillian Hanussek, Martin Braun, Marius Dieckmann, Björn Grüning etc. Date: 8.10.2020 – 14.10.2020 Location: Online Contents: We are pleased to announce the third de.NBI Cloud User Meeting. In comparison to preceding meetings, this year`s meeting will be organized as an online conference. Over five days users can watch talks of already experienced users and long running projects and thereby learn about best practices in cloud computing. Same as the last years we will try to cover topics for beginners such as virtualization but also topics for software engineers and administrators such as orchestration with Kubernetes. Participants will learn how to scale up their analysis to handle growing input data and how to use workflow managers such as Snakemake in a cloud environment. As every year we are also going to demonstrate the usage of bioinformatics software in the de.NBI Cloud using Docker images or Bioconda packages. Planned Courses: - Running Snakemake Workflows in the de.NBI Cloud - OpenStack Introduction - BioConda and BioContainers - Kubernetes Introduction - Deploying Web Services in the de.NBI Cloud - Extensible Cluster Setup in the Cloud with BibiGrid and Ansible - Using Terraform to define infrastructure as code Learning goals: Working with the de.NBI cloud Prerequisites: We welcome people from all background, no matter if you are new to the de.NBI Cloud or considering to submit a project application, to learn and network in our growing community. Keywords: de.NBI cloud Tools: de.NBI cloud Webpage: https://cloud.denbi.de/3rd-de-nbi-cloud-user-meeting/ 2020-10-08 09:00:00 UTC 2020-10-14 17:00:00 UTC de.NBI [] [] [] meetings_and_conferences [] []
  • Computing Skills for Reproducible Research: Software Carpentry Course 2020

    19 - 23 October 2020

    Computing Skills for Reproducible Research: Software Carpentry Course 2020 https://tess.elixir-europe.org/events/computing-skills-for-reproducible-research-software-carpentry-course-2020 Educators: Renato Alves (HD-HuB) Date: 19-10-2020 - 23-10-2020 09:00-18:00 Location: Online 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 2020-10-19 09:00:00 UTC 2020-10-23 17:00:00 UTC de.NBI Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany [] [] [] workshops_and_courses [] []
  • 5th Differential analysis of quantitative proteomics data using R

    2 November 2020

    5th Differential analysis of quantitative proteomics data using R https://tess.elixir-europe.org/events/5th-differential-analysis-of-quantitative-proteomics-data-using-r Educators: Michael Turewicz (bioinformatician) and Karin Schork (biostatistician) (BioInfra.Prot) Date: Monday, 2nd Nov 2020 Location: Online Contents: This course will impart knowledge about how to conduct a differential analysis of high-throughput quantitative proteomics data using R. As we start with a basic introduction to the popular statistical programming language, no prior knowledge on R is required. The statistical background on utilized methods is explained in order to enable the participants to assess their own as well as published workflows critically. In this regard the course will touch upon • statistical inference: hypotheses, type I and II error • location tests (t-test) • multiple testing Learning goals: • Independent usage of basic R functions including - data import and export - basic plots - statistical tests • Deeper understanding of statistical methods applied in differential analyses Prerequisites: • Basic understanding of high-dimensional data sets from quantitative proteomics or other life sciences; • No prior knowledge on R required • Computer with stable internet connection, headset and camera Keywords: R; high-throughput data; omics; proteomics; differential analysis Tools: download and more information on R here: https://cran.r-project.org/ We recommend using an editor such as RStudio, see www.rstudio.com 2020-11-02 09:00:00 UTC 2020-11-02 17:00:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • 2nd Advanced analysis of quantitative proteomics data using R

    9 November 2020

    2nd Advanced analysis of quantitative proteomics data using R https://tess.elixir-europe.org/events/2nd-advanced-analysis-of-quantitative-proteomics-data-using-r Educators: Michael Turewicz (bioinformatician) and Karin Schork (biostatistician) (BioInfra.Prot) Date: Monday, 9th Nov 2020 Location: Online Contents: In this course you will learn about using R for the analysis of proteomics data. We will focus on data preprocessing methods and advanced methods for data analysis. In this regard the cpurse will touch upon: • data normalization • quality control, handling of missing values • clustering, heatmaps • ROC-curves Please be aware that basic knowledge of R and methods for differential analysis of proteomics data are taught in our course “Differential analysis of quantitative proteomics data” the previous day (Monday, 2nd Nov 2020, http://goo.gl/forms/mpKHnbT1Um) Learning goals: • Independent usage of R functions for - Data preprocessing - Plots and graphs - Statistical methods for data analysis - Use of additional R packages • Deeper understanding of statistical methods applied in differential analyses Prerequisites: • Basic understanding of high-dimensional data sets from quantitative proteomics or other life sciences; • Basic knowledge of R (e.g. data import, basic plots, t-test, for loop) and basic knowledge of differential analysis of proteomics data. Both can for example be gained from our course “Differential analysis of quantitative proteomics data” the previous day (Monday, 2nd Nov 2020, http://goo.gl/forms/mpKHnbT1Um). • Computer with stable internet connection, headset and camera Keywords: R; high-throughput data; omics; proteomics; data analysis, graphics, data preprocessing Tools: download and more information on R here: https://cran.r-project.org/ We recommend using an editor such as RStudio, see www.rstudio.com 2020-11-09 09:00:00 UTC 2020-11-09 17:00:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • de.NBI Crop Analysis Tool Suite (Part I) training course – Explore the barley genome

    16 November 2020

    de.NBI Crop Analysis Tool Suite (Part I) training course – Explore the barley genome https://tess.elixir-europe.org/events/de-nbi-crop-analysis-tool-suite-part-i-training-course-explore-the-barley-genome Educators: Uwe Scholz (GCBN), Sebastian Beier (GCBN) Date: 16th November 2020, 10:00 a.m. – 11:30 a.m. Location: Online Contents: Complex plant genomes impose high demands on analytical software and the knowledge of biologists to interpret these results. The service centre GCBN offers CATS (Crop Analysis Tool Suite), which provides various tools for sequence analysis. In this first of three courses the main focus is on the operation of the BLAST Server and the integration with BARLEX (Barley Genome Explorer). There will be two short presentations on the two topics and two online live demonstrations with examples. Together the whole training course will last about 90 minutes. Learning goals: The primary objective of this training course is to introduce tools for sequence analysis for crops (in particular barley). The theoretical basics as well as some examples will be shown by using online demonstrations, which will enable the participants to design and perform their own analyses. Prerequisites: The training course is designed for early career scientists such as PhD students and postdocs, but also for experienced scientists who want to learn more about the analysis and handling of sequence data for complex plant genomes like barley. Keywords: Sequence analysis, genomics, transcriptomics, annotation, Morex v2 assembly Tools: IPK WebBlast - https://webblast.ipk-gatersleben.de/barley_ibsc/ BARLEX - http://barlex.barleysequence.org/ 2020-11-16 10:00:00 UTC 2020-11-16 11:30:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • de.NBI – e!DAL-PGP training course – Sharing and Publishing Comprehensive Plant Research Data

    19 November 2020

    de.NBI – e!DAL-PGP training course – Sharing and Publishing Comprehensive Plant Research Data https://tess.elixir-europe.org/events/de-nbi-e-dal-pgp-training-course-sharing-and-publishing-comprehensive-plant-research-data Educator: Daniel Arend (GCBN) Date: 19th November 2020, 10:00 a.m. – 11:30 a.m. Location: Online Contents: In the context of a growing global demand for food and feed the need for improved crop yield and the identification of more efficient and better adapted crops to answer the world's growing population is an important driving force for high-throughput plant genotyping and phenotyping studies which comprise comprehensive and data-intense experiments. As formulated in current funding policies, research data should be published under consideration of the FAIR (findable, accessible, interoperable, and reusable) data principles. Contrarily, they remain frequently unpublished due to organizational reasons or missing infrastructures. Therefore, the reproducibility and the preservation of research data depend on the scientists or the journal to which they want to publish their results. The eDAL-PGP repository provide a powerful infrastructure to easily share and publish comprehensive and cross-domain plant research data. Learning goals: The major goal of this trainings course is to get a general understanding how to publish plant research data that do not fit into the scope of existing databases in a FAIR way by using the eDAL-PGP repository. Prerequisites: The training course is designed for early career scientists such as PhD students and postdocs, but also for experienced scientists who want to learn more about the analysis and handling of sequence data for complex plant genomes like barley. Keywords: FAIR research data, Digital Object Identifier, Research Data Publication, Genomics, Phenomics Tools: e!DAL-PGP - http://edal-pgp.ipk-gatersleben.de/ 2020-11-19 10:00:00 UTC 2020-11-19 11:30:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • de.NBI Crop Analysis Tool Suite (Part II) training course – Working with repetitive sequences

    20 November 2020

    de.NBI Crop Analysis Tool Suite (Part II) training course – Working with repetitive sequences https://tess.elixir-europe.org/events/de-nbi-crop-analysis-tool-suite-part-ii-training-course-working-with-repetitive-sequences Educator: Sebastian Beier (GCBN) Date: 20th November 2020, 10:00 a.m. – 11:30 a.m. Location: Online Contents: Complex plant genomes impose high demands on analytical software and the knowledge of biologists to interpret these results. The service centre GCBN offers CATS (Crop Analysis Tool Suite), which provides various tools for sequence analysis. In this second of three courses the main focus is on the operation of repeat analysis and masking with the tools Kmasker plants (mathematically defined repeats) and MISA-Web (microsatellites). There will be two short presentations on the two topics and two online live demonstrations with examples. Together the whole training course will last about 90 minutes. Learning goals: The primary objective of this training course is to introduce tools for sequence analysis for crops. The theoretical basics as well as some examples will be shown by using online demonstrations, which will enable the participants to design and perform their own analyses. Prerequisites: The training course is designed for early career scientists such as PhD students and postdocs, but also for experienced scientists who want to learn more about the repeat analysis and masking of sequence data for complex plant genomes. Keywords: Microsatellite, Mathematically Defined Repeat, K-mer, SSR Tools: Kmasker Plants - https://kmasker.ipk-gatersleben.de/ MISA-Web - https://webblast.ipk-gatersleben.de/misa/ 2020-11-20 10:00:00 UTC 2020-11-20 11:30:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • Introduction to the Cloud for Proteomics Analyses

    23 November 2020

    Introduction to the Cloud for Proteomics Analyses https://tess.elixir-europe.org/events/introduction-to-the-cloud-for-proteomics-analyses Educators: Dominik Kopczynski, Markus Stepath, Michael Turewicz and Julian Uszkoreit (BioInfra.Prot) Date: Monday, 2020-11-23 Location: online Contents: In this one day course we will show some of BioInfra.Prot's tools provided by de.NBI, namely “PIA - Protein Inference Algorithms”, “BIONDA – A Free Biomarker Database” and “CalibraCurve”. Besides the tool based sessions we offer a "Proteomics in the Cloud" session where we show advantages of cloud based bioinformatics and give a tutorial how to access the de.NBI cloud. PIA allows to inspect and combine the results of proteomics search engines. The main focus lays on the integrated inference algorithms for identification and quantification purposes. BIONDA is a free, up-to-date and user-friendly biomarker and biomarker candidate database that facilitates any kind of research on protein biomarkers and the corresponding diseases. CalibraCurve is a tool intended for the generation of calibration curves in the context of MRM (targeted proteomics) experiments. Such calibration curves are necessary for the selection of suitable transitions. In addition the web service STAMPS will be part of this course. It is a pathway-centric service for the development of targeted proteomics assays. In combination with Skyline, it offers a streamlined pipeline for identification and quantification in targeted proteomics analyses and development of targeted proteomics assays. Learning goals: Attendees of the course will learn how to use the tools PIA, BIONDA, CalibraCurve and STAMPS effectively for their daily proteomics tasks. Additionally they will learn how to use the de.NBI cloud. Prerequisites: This course is for all researches in the field of proteomics. The attendees should have basic knowledge of LC-MS proteomics, but no prior bioinformatics skills are required. Basic knowledge of how to analyse LC-MS data are sufficient. Attendees are required to bring their own laptops. If this is not possible or laptops have very low computing capacities, please contact the organizers. Keywords: Proteomics; Data Analysis; Assay Development; Biomarkers; de.NBI Cloud 2020-11-23 09:00:00 UTC 2020-11-23 17:00:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • de.NBI Crop Analysis Tool Suite (Part III) training course – Explore barley diversity

    24 November 2020

    de.NBI Crop Analysis Tool Suite (Part III) training course – Explore barley diversity https://tess.elixir-europe.org/events/de-nbi-crop-analysis-tool-suite-part-iii-training-course-explore-barley-diversity Educator: Patrick König (GCBN) Date: 24th November 2020, 10:00 a.m. – 11:30 a.m. Location: Online Contents: The service centre GCBN offers CATS (Crop Analysis Tool Suite), which includes a web application for exploratory data analysis of the genomic diversity data derived from studies based on the concept of gene bank genomics. The concept of gene bank genomics is about to gain insight into the diversity of genetic resources stored in gene banks and to allow the utilisation of this mainly untapped diversity for breeding and further research and exploitation. BRIDGE is an interactive web tool for exploratory data analysis of a gene bank genomics study of more than 20,000 barley accessions. The tool helps researchers and breeders to keep the overview about the massive amount of data and to derive a benefit from diversity data through context-based data visualisation and data export. Learning goals: The goal of this training course is to provide an introduction into the BRIDGE web application, its available data domains and its use for data visualisation, exploratory data analysis and data export for different use cases of specific research interests. Prerequisites: The training course is aimed at young scientists such as PhD students and postdocs, but also at experienced scientists who want to learn more about exploratory data analysis, visualization and exploitation of plant diversity data for use in breeding and research. Keywords: Barley, Gene bank genomics, Exploratory data analysis, Visual analytics, Data visualisation, Data warehouse, Tools: BRIDGE (https://doi.org/10.3389/fpls.2020.00701 2020-11-24 10:00:00 UTC 2020-11-24 11:30:00 UTC de.NBI [] [] [] workshops_and_courses [] []
  • Data visualization using R

    7 December 2020

    Data visualization using R https://tess.elixir-europe.org/events/data-visualization-using-r Educators: Markus Stepath, Karin Schork, Nils Hoffmann (BioInfra.Prot / LIFS) Date: Monday, 7th Dec 2020 Location: Online training Contents: In this course you will learn how to use the ggplot2 package in R to create informative and beautiful figures to communicate your omics data and analysis results. We will cover the following topics: - Usage of the tidyverse for data preprocessing - Usage of the ggplot2 R package - Presentation of different types of graphics and when to use them - Customization of graphics Please be aware that basic knowledge of R is taught in our course “Differential analysis of quantitative proteomics data” on Monday, 2nd Nov 2020 (http://goo.gl/forms/mpKHnbT1Um). Learning goals: - Using the ggplot2 R package to create graphics for omics data - Decide which type of graph is appropriate for the given data - Ability to costumize the graphics using ggplot2 Prerequisites: - Basic understanding of high-dimensional data sets from quantitative proteomics or other life sciences; - Basic knowledge of R (e.g. data import, basic plots. This can for example be gained from our course “Differential analysis of quantitative proteomics data” (Monday, 2nd Nov 2020, http://goo.gl/forms/mpKHnbT1Um). - Computer with stable internet connection, headset and camera Keywords: R; tidyverse; ggplot2; high-throughput data; omics; proteomics; data analysis, graphics, data preprocessing Tools: Download and more information on R here: https://cran.r-project.org/ We recommend using an editor such as RStudio, see www.rstudio.com 2020-12-07 09:00:00 UTC 2020-12-07 17:00:00 UTC de.NBI [] [] [] workshops_and_courses [] []

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