TY  - JOUR
A1  - Christopher Ashwood, Wout Bittremieux
A1  - Bittremieux, Wout
A1  - Deutsch, Eric W.
A1  - Doncheva, Nadezhda T.
A1  - Dorfer, Viktoria
A1  - Gabriels, Ralf
A1  - Gorshkov, Vladimir
A1  - Gupta, Surya
A1  - Jones, Andrew R.
A1  - Käll, Lukas
A1  - Kopczynski, Dominik
A1  - Lane, Lydie
A1  - Lautenbacher, Ludwig
A1  - Legeay, Marc
A1  - Locard-Paulet, Marie
A1  - Mesuere, Bart
A1  - Sachsenberg, Timo
A1  - Salz, Renee
A1  - Samaras, Patroklos
A1  - Schiebenhoefer, Henning
A1  - Schmidt, Tobias
A1  - Schwämmle, Veit
A1  - Soggiu, Alessio
A1  - Uszkoreit, Julian
A1  - Van Den Bossche, Tim
A1  - Van Puyvelde, Bart
A1  - Van Strien, Joeri
A1  - Verschaffelt, Pieter
A1  - Webel, Henry
A1  - Willems, Sander
A1  - Perez-Riverolab, Yasset
A1  - Netz, Eugen
A1  - Pfeuffer, Julianus
T1  - Proceedings of the EuBIC-MS 2020 Developers’ Meeting
JF  - EuPA Open Proteomics
N2  - 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.
KW  - computational mass spectrometry
KW  - proteomics
KW  - bioinformatics
KW  - spectrum clustering
KW  - phosphoproteomics
KW  - XIC extraction
KW  - proteomics graph networks
KW  - predicted spectra
Y1  - 2020
U6  - https://doi.org/10.1016/j.euprot.2020.11.001
SN  - 2212-9685
VL  - 24
SP  - 1
EP  - 6
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Wittig, Alice
A1  - Miranda, Fabio Malcher
A1  - Hölzer, Martin
A1  - Altenburg, Tom
A1  - Bartoszewicz, Jakub Maciej
A1  - Beyvers, Sebastian
A1  - Dieckmann, Marius Alfred
A1  - Genske, Ulrich
A1  - Giese, Sven Hans-Joachim
A1  - Nowicka, Melania
A1  - Richard, Hugues
A1  - Schiebenhoefer, Henning
A1  - Schmachtenberg, Anna-Juliane
A1  - Sieben, Paul
A1  - Tang, Ming
A1  - Tembrockhaus, Julius
A1  - Renard, Bernhard Y.
A1  - Fuchs, Stephan
T1  - CovRadar
BT  - continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance
JF  - Bioinformatics
N2  - 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.
Y1  - 2022
U6  - https://doi.org/10.1093/bioinformatics/btac411
SN  - 1367-4803
SN  - 1367-4811
VL  - 38
IS  - 17
SP  - 4223
EP  - 4225
PB  - Oxford Univ. Press
CY  - Oxford
ER  -