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In May 2013, the announcement of funding guidelines for a German Network for Bioinformatics Infrastructure (de.NBI) was published by the German Federal Ministry of Education and Research (BMBF). The aim of this announcement was to establish an infrastructure in Germany that will provide solutions to the ‘Big Data Problem’ in life science by means of bioinformatics services and training. A second announcement of funding guidelines for de.NBI partner projects was published in November 2015. The de.NBI program was launched by the BMBF in March 2015, and the partner projects started their work in November 2016.<ref name="autogenerated2" /> In August 2016, Germany joined [[ELIXIR]], the European life-sciences Infrastructure for biological Information, with the German [[ELIXIR]] Node (ELIXIR Germany) being run by de.NBI partners.<ref>[https://www.elixir-europe.org/news/elixir-board-meeting-2016-spring-session ELIXIR Board Meeting Spring 2016]</ref><ref>[https://www.elixir-europe.org/news/germany-joins-elixir Germany joins ELIXIR]</ref><ref>[https://www.elixir-europe.org/about-us/who-we-are/nodes/germany. ELIXIR Germany]</ref>
The first coordinator of the de.NBI project was [[Alfred Pühler]] until 2021. The head of the German ELIXIR Node is Andreas Tauch.<ref>{{Cite web|last=|first=|date=|title=de.NBI Quarterly Newsletter 2/20|url=https://www.denbi.de/images/Downloads/Newsletter/quarterly_newsletter_20.pdf
== Organisation ==
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=== Tools ===
de.NBI develops and supplies about 100 bioinformatics tools for the German and global life sciences community, e.g. [[Galaxy (computational biology)]]/useGalaxy.eu (Workflow engine for all Freiburg RNA Tools),<ref>{{cite journal| pmid=28554830 | doi=10.1016/j.jbiotec.2017.05.019 | volume=261 | title=RNA-bioinformatics: Tools, services and databases for the analysis of RNA-based regulation | year=2017 | journal=J Biotechnol | pages=76–84 | last1 = Backofen | first1 = R | last2 = Engelhardt | first2 = J | last3 = Erxleben | first3 = A | last4 = Fallmann | first4 = J | last5 = Grüning | first5 = B | last6 = Ohler | first6 = U | last7 = Rajewsky | first7 = N | last8 = Stadler | first8 = PF| doi-access = free }}</ref> EDGAR (Comparative Genome Analyses Plattform),<ref>{{cite journal| pmid=28705636 | doi=10.1016/j.jbiotec.2017.07.010 | volume=261 | title=A review of bioinformatics platforms for comparative genomics. Recent developments of the EDGAR 2.0 platform and its utility for taxonomic and phylogenetic studies | year=2017 | journal=J Biotechnol | pages=2–9 | last1 = Yu | first1 = J | last2 = Blom | first2 = J | last3 = Glaeser | first3 = SP | last4 = Jaenicke | first4 = S | last5 = Juhre | first5 = T | last6 = Rupp | first6 = O | last7 = Schwengers | first7 = O | last8 = Spänig | first8 = S | last9 = Goesmann | first9 = A| doi-access = free }}</ref> [[KNIME]] (Workflow engine),<ref>{{cite journal| pmid=28757290 | doi=10.1016/j.jbiotec.2017.07.028 | volume=261 | title=KNIME for reproducible cross-___domain analysis of life science data | year=2017 | journal=J Biotechnol | pages=149–156 | last1 = Fillbrunn | first1 = A | last2 = Dietz | first2 = C | last3 = Pfeuffer | first3 = J | last4 = Rahn | first4 = R | last5 = Landrum | first5 = GA | last6 = Berthold | first6 = MR| doi-access = free }}</ref> [[OpenMS]] (Open-source software C++ library for LC/MS data management and analyses),<ref>{{cite journal| pmid=28559010 | doi=10.1016/j.jbiotec.2017.05.016 | volume=261 | title=OpenMS - A platform for reproducible analysis of mass spectrometry data | year=2017 | journal=J Biotechnol | pages=142–148 | last1 = Pfeuffer | first1 = J | last2 = Sachsenberg | first2 = T | last3 = Alka | first3 = O | last4 = Walzer | first4 = M | last5 = Fillbrunn | first5 = A | last6 = Nilse | first6 = L | last7 = Schilling | first7 = O | last8 = Reinert | first8 = K | last9 = Kohlbacher | first9 = O| doi-access = free }}</ref> [[SeqAN]] (Open source [[C++]] library of efficient algorithms and data structures),<ref>{{cite journal| pmid=28888961 | doi=10.1016/j.jbiotec.2017.07.017 | volume=261 | title=The SeqAn C++ template library for efficient sequence analysis: A resource for programmers | year=2017 | journal=J Biotechnol | pages=157–168 | last1 = Reinert | first1 = K | last2 = Dadi | first2 = TH | last3 = Ehrhardt | first3 = M | last4 = Hauswedell | first4 = H | last5 = Mehringer | first5 = S | last6 = Rahn | first6 = R | last7 = Kim | first7 = J | last8 = Pockrandt | first8 = C | last9 = Winkler | first9 = J | last10 = Siragusa | first10 = E | last11 = Urgese | first11 = G | last12 = Weese | first12 = D| doi-access = free }}</ref> PIA (toolbox for MS based protein inference and identification analysis),<ref name="autogenerated1" /> [[Fiji (software)]] (Image processing package), [[MetFrag]] (in silico fragmenter combines compound database searching and fragmentation prediction for small molecule identification from tandem [[mass spectrometry]] data),<ref>{{cite journal| pmid=28554829 | doi=10.1016/j.jbiotec.2017.05.018 | volume=261 | title=Bioinformatics can boost metabolomics research | year=2017 | journal=J Biotechnol | pages=137–141 | last1 = Meier | first1 = R | last2 = Ruttkies | first2 = C | last3 = Treutler | first3 = H | last4 = Neumann | first4 = S| doi-access = free }}</ref> [[COPASI]] ([[Open-source software|open source]] software application for creating and solving [[mathematical models]] of [[biological processes]]),<ref>{{cite journal| pmid=28655634 | doi=10.1016/j.jbiotec.2017.06.1200 | pmc=5623632 | volume=261 | title=COPASI and its applications in biotechnology | year=2017 | journal=J Biotechnol | pages=215–220 | last1 = Bergmann | first1 = FT | last2 = Hoops | first2 = S | last3 = Klahn | first3 = B | last4 = Kummer | first4 = U | last5 = Mendes | first5 = P | last6 = Pahle | first6 = J | last7 = Sahle | first7 = S}}</ref> [[SIAMCAT]] (Framework for the statistical inference of associations between [[microbial communities]] and host [[phenotypes]]), [[The e!DAL Plant Phenomics and Genomics Research Data Repository|e!DAL - PGP]] (Open source software framework to publish and share research data), MGX ([[Metagenome]] analysis),<ref>{{cite journal| pmid=29690922 | doi=10.1186/s40168-018-0460-1 | pmc=5937802 | volume=6 | title=Flexible metagenome analysis using the MGX framework | year=2018 | journal=Microbiome | page=76 | last1 = Jaenicke | first1 = S | last2 = Albaum | first2 = SP | last3 = Blumenkamp | first3 = P | last4 = Linke | first4 = B | last5 = Stoye | first5 = J | last6 = Goesmann | first6 = A| issue=1 | doi-access=free }}</ref> ASA³P (automated WGS analysis of bacterial cohorts),<ref>{{cite journal |title=ASA3P: An automatic and scalable pipeline for the assembly, annotation and higher-level analysis of closely related bacterial isolates |date=2020-03-05 |journal=PLOS Computational Biology |volume=16 |issue=3 |at=pp. e1007134 |language=German |bibcode=2020PLSCB..16E7134S |doi=10.1371/journal.pcbi.1007134 |issn=1553-7358 |pmc=7077848 |pmid=32134915 |last1=Schwengers |first1=Oliver |last2=Hoek |first2=Andreas |last3=Fritzenwanker |first3=Moritz |last4=Falgenhauer |first4=Linda |last5=Hain |first5=Torsten |last6=Chakraborty |first6=Trinad |last7=Goesmann |first7=Alexander |doi-access=free }}</ref> Bakta<ref>{{Cite journal |last1=Schwengers |first1=Oliver |last2=Jelonek |first2=Lukas |last3=Dieckmann |first3=Marius Alfred |last4=Beyvers |first4=Sebastian |last5=Blom |first5=Jochen |last6=Goesmann |first6=Alexander |date=2021-11-05 |title=Bakta: rapid and standardized annotation of bacterial genomes via alignment-free sequence identification |journal=Microbial Genomics |volume=7 |issue=11 |page=000685 |doi=10.1099/mgen.0.000685 |issn=2057-5858 |pmc=8743544 |pmid=34739369}}</ref> (annotation of bacterial genomes and plasmids) and many more.
de.NBI tools are also registered and searchable in the ELIXIR Tools and Data Services Registry that provides more information in a standardized format.
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Different types of training activities are supported and organized by de.NBI. First of all, the summer schools provide training courses for undergraduate and [[graduate students]] in specific topics related to one or several de.NBI centers. The respective centers organize tool-specific training. These trainings are attached to existing conferences or organized independently. In addition, online training was introduced on the de.NBI website in 2016. Since 2017, online training formats like [[hackathon]]s or [[webinars]] are offered by all service centers.
The de.NBI training program started in 2015 with 17 f2f training courses with 329 participants, steadily increasing to 79 courses with 1586 Participants in 2019. In 2020 and 2021, the practical delivery of training was significantly affected by the COVID-19 pandemic, but the development of online training and materials (40 courses with 1,149 participants in 2020) enabled 2,128 training participants to be upskilled in 49 courses in 2021. A total of 9,076 scientists have been trained in 371 courses through our bioinformatics network to date (as of January 2022).<ref>{{Cite web |date=2022-02-24 |title=de.NBI Quarterly Newsletter 01/22 |url=https://www.denbi.de/downloads/21-about/1362-newsletter-27
=== de.NBI Summer Schools===
Next to the training courses de.NBI offers annual [[Summer school|summer schools]] to cover a distinct topic in more detail. The first Summer School was held in 2015 by the Service Centers Bielefeld-Gießen (BiGi) Center for Microbial Bioinformatics, RBC and de.NBI-SysBio and was focused in the workflow from genome assembly to genome and transcriptome analysis.<ref>[https://www.denbi.de/training-archive-sorted-according-by-date/2015/142-de-nbi-late-summer-school-2015 de.NBI Summer School 2015]</ref> In the following years the Summer Schools were organized by the Service Centers BioInfraProt, CIBI and BiGi as well as BioData, GCBN and de.NBI-SysBio and held at different locations throughout Germany. The Summer Schools covered the topics proteomics and mass spectrometry data (2016),<ref>[https://www.denbi.de/training-archive-sorted-according-by-date/2016/180-de-nbi-summer-school-2016-from-big-data-to-big-insights de.NBI Summer School 2016]</ref> Cloud Computing for Bioinformatics (2017),<ref>{{Cite web |date=2017-04-01 |title=de.NBI Summer School 2017 -2 |url=https://www.denbi.de/training-archive-sorted-according-by-date/2017/219-de-nbi-summer-school-on-cloud-computing-for-bioinformatics
===Additional de.NBI Schools ===
In addition, as an outreach activity de.NBI supported the Summer School BioByte 2019 at [[Martin Luther University of Halle-Wittenberg|University of Halle]] addressed at high school students which offers an ideal opportunity to get to know the diversity of bioinformatics.<ref>{{Cite web|url=https://biobyte.uni-halle.de/|title=Sommerschule für neugierige Schülerinnen und Schüler, die die Naturwissenschaft der Zukunft entdecken möchten.|last=|first=|date=|website=|language=de
==References==
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