@article{ChristopherAshwoodBittremieuxDeutschetal.2020,
  author    = {Christopher Ashwood, Wout Bittremieux and Bittremieux, Wout and Deutsch, Eric W. and Doncheva, Nadezhda T. and Dorfer, Viktoria and Gabriels, Ralf and Gorshkov, Vladimir and Gupta, Surya and Jones, Andrew R. and K{\"a}ll, Lukas and Kopczynski, Dominik and Lane, Lydie and Lautenbacher, Ludwig and Legeay, Marc and Locard-Paulet, Marie and Mesuere, Bart and Sachsenberg, Timo and Salz, Renee and Samaras, Patroklos and Schiebenhoefer, Henning and Schmidt, Tobias and Schw{\"a}mmle, Veit and Soggiu, Alessio and Uszkoreit, Julian and Van Den Bossche, Tim and Van Puyvelde, Bart and Van Strien, Joeri and Verschaffelt, Pieter and Webel, Henry and Willems, Sander and Perez-Riverolab, Yasset and Netz, Eugen and Pfeuffer, Julianus},
  title     = {Proceedings of the EuBIC-MS 2020 Developers' Meeting},
  series = {EuPA Open Proteomics},
  volume    = {24},
  journal   = {EuPA Open Proteomics},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2212-9685},
  doi       = {10.1016/j.euprot.2020.11.001},
  pages     = {1 -- 6},
  year      = {2020},
  abstract  = {The 2020 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers' meeting was held from January 13th to January 17th 2020 in Nyborg, Denmark. Among the participants were scientists as well as developers working in the field of computational mass spectrometry (MS) and proteomics. The 4-day program was split between introductory keynote lectures and parallel hackathon sessions. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts, and to actively contribute to highly relevant research projects. We successfully produced several new tools that will be useful to the proteomics community by improving data analysis as well as facilitating future research. All keynote recordings are available on https://doi.org/10.5281/zenodo.3890181.},
  language  = {en}
}
@article{WittigMirandaHoelzeretal.2022,
  author    = {Wittig, Alice and Miranda, Fabio Malcher and H{\"o}lzer, Martin and Altenburg, Tom and Bartoszewicz, Jakub Maciej and Beyvers, Sebastian and Dieckmann, Marius Alfred and Genske, Ulrich and Giese, Sven Hans-Joachim and Nowicka, Melania and Richard, Hugues and Schiebenhoefer, Henning and Schmachtenberg, Anna-Juliane and Sieben, Paul and Tang, Ming and Tembrockhaus, Julius and Renard, Bernhard Y. and Fuchs, Stephan},
  title     = {CovRadar},
  series = {Bioinformatics},
  volume    = {38},
  journal   = {Bioinformatics},
  number    = {17},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {1367-4803},
  doi       = {10.1093/bioinformatics/btac411},
  pages     = {4223 -- 4225},
  year      = {2022},
  abstract  = {The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast.},
  language  = {en}
}