Software Carpentry 1.2020
31 August - 1 September 2020Software Carpentry 1.2020 https://www.denbi.de/training/821-software-carpentry-1-2020 https://tess.elixir-europe.org/events/software-carpentry-1-2020 Educators: Rabea Müller, Konrad Förstner, Till Sauerwein (ZB MED/Associated Partner) Date August 31 - September 01 2020 Location: Online Contents: Data, Shell, Git and GitHub, Python: Day 1 Before Pre-workshop survey 09:00 Data Intro 10:30 Morning break 12:00 Lunch break 13:00 Shell Lessons 14:15 Afternoon break 15:30 Wrap-up 16:00 END Day 2 09:00 Python Intro 10:30 Morning break 12:00 Lunch break 13:00 Git Intro 14:15 Afternoon break 15:30 Wrap-up 15:45 Post-workshop Survey 16:00 END Learning goals: Get basic knowledge of the programming language python, the unix-shell, automating tasks, the version control software git and the cloud service GitHub, Prerequisites: Attendees must use their own laptop with the following software already installed: Gitbash (Windows) / Shell (Linux) / Terminal (MAC OS) , Anaconda3 and Git. Every attendee also needs a GitHub account. Keywords: programming, automation, version control, reproducible science Tools: Shell, Git and GitHub, 2020-08-31 09:00:00 UTC 2020-09-01 17:00:00 UTC de.NBI Köln, Köln, Germany Köln Köln Köln Germany    workshops_and_courses  
BioC++ - solving daily bioinformatic tasks with C++ efficiently - GCB2020
14 September 2020BioC++ - solving daily bioinformatic tasks with C++ efficiently - GCB2020 https://www.denbi.de/training/752-seqan-at-the-german-conference-for-bioinformatics-gcb https://tess.elixir-europe.org/events/seqan-at-the-german-conference-for-bioinformatics-gcb Educators: René Rahn, Marcel Ehrhardt, Svenja Mehringer (CIBI) Date: 14.09.2020 9:00 - 17:00 (CEST) Location: Online - GCB Conference https://gcb2020.de/WS4.html Contents: In this half-day tutorial we are going to teach how to use modern C++ and utilise modern C++ libraries to rapidly develop tools and scripts for operating on and manipulating large-scale sequencing data. The high variability and heterogeneity often observed within various genomic data is challenging for many standard tools, for example for read alignment and variant calling. Often, these tools are wrapped in complicated pre- and postprocessing data curation steps in order to obtain results with higher quality. However, these additional steps incur a high maintenance and performance burden to the established work process and often do not scale with larger data sets. Seldomly, C++ is considered as the language of choice for these small processes, although it is the main language used in high-performance computing. We are going to show that implementing modern C++ can be as easy as using other modern high-level languages. Learning goals: Students will develop - skills in developing an application using the C++ programming language - skills in using modern C++ libraries to query large sequence databases (e.g. SeqAn, SDSL, etc.) - knowledge and understanding of modern C++ features, such as ranges and concepts - knowledge and understanding about modern and efficient data structures as well as algorithms crucial for large-scale genomic sequence analysis - knowledge and understanding about how to develop and sustain high-quality software Prerequisites: This tutorial is mostly suited for computational biologist and bioinformaticians with research focus on sequence analysis (e.g., genomics, metagenomics, proteomics, read alignment, variant detection, etc.). A fundamental knowledge about sequencing experiments and the involved data is required. We expect that attendees have an intermediate knowledge in programming with any high-level programming language, e.g. Python, Java or C++. Some basic C++-knowledge is helpful but not mandatory to successfully complete the course. This tutorial is targeting beginners and intermediate C++ developers that want to learn more about modern C++ features like ranges and concepts. Keywords: BioC++, modern C++, bioinformatics, SeqAn, FileIO Tools: - A simple text editor - g++ >= 7 - cmake >= 3.12 - git 2020-09-14 09:00:00 UTC 2020-09-14 17:00:00 UTC de.NBI Frankfurt am Main, Frankfurt am Main, Germany Frankfurt am Main Frankfurt am Main Darmstadt Germany    meetings_and_conferences  
ProteinsPlus at the German Conference for Bioinformatics (GCB)
14 September 2020ProteinsPlus at the German Conference for Bioinformatics (GCB) https://www.denbi.de/training/807-proteinsplus-at-the-german-conference-for-bioinformatics-gcb https://tess.elixir-europe.org/events/proteinsplus-at-the-german-conference-for-bioinformatics-gcb Educators: Matthias Rarey & Katrin Schöning-Stierand (BioData) Date: 14.09.2020 13:00-18:00 Location: Online - GCB 2020 https://gcb2020.de/WS6.html Contents: Three-dimensional protein structures are a fundamental basis for understanding, modulating, and manipulating protein functionality. With over 155,000 structures, the Protein Data Bank (PDB) is one of the most important bioinformatics resources for life science. In this workshop, we present the ProteinsPlus server enriching structural knowledge from the PDB by additional computed information required for common biological research questions. ProteinsPlus enables easy access to this information for all researchers in the fields of molecular life sciences. The provided computational services comprise various tools for the assessment, representation, preprocessing, and interconnection of structural data. Many of the provided tools focus on protein binding pockets and molecular interactions to small molecules due to their relevance for various research questions. Participants will get to know a combination of tools and web services for searching and analyzing protein structure data. The focus will be on protein function and related interactions to small molecules. We will work with the ProteinsPlus web service that contains a diverse range of software solutions for the analysis of protein structures and its application in molecular modeling approaches. Learning goals: This course is designed for life and computer scientists with interest in protein structures, but only very basic experience in 3D modeling. Topics include: Finding and selecting protein structure data, evaluating the quality of experimental data, preprocessing structure data for modeling, first modeling steps like the analysis of binding site properties and conformational flexibility. Usage of ProteinsPlus is free and open to all users. Prerequisites: General knowledge of proteins and their role in life sciences Keywords: Protein structures, protein-ligand interactions, molecular modeling, structure-to-function relationships, cheminformatics, ProteinsPlus, BRENDA, EnzymeStructures, KNIME Tools: ProteinsPlus, 2020-09-14 13:00:00 UTC 2020-09-14 18:00:00 UTC de.NBI Frankfurt am Main, Frankfurt am Main, Germany Frankfurt am Main Frankfurt am Main Darmstadt Germany    meetings_and_conferences  
Computational genomics course for hands-on data analysis 2020
23 - 25 September 2020Computational genomics course for hands-on data analysis 2020 https://www.denbi.de/training/806-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  
Computing Skills for Reproducible Research: Software Carpentry Course 2020
19 - 23 October 2020Computing Skills for Reproducible Research: Software Carpentry Course 2020 https://www.denbi.de/training/789-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  
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