Johannes Rainer

Dr. Johannes Rainer

Institute for Biomedicine, Eurac Research, Bolzano, Trentino-Alto Adige, Italy
orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 August 2020 in Nature Methods
Verified
Journal Article
Open access
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LNLouis-Félix Nothias
Louis-Félix Nothias
DPDaniel Petras
Daniel Petras
RSRobin Schmid
Robin Schmid
KDKai Dührkop
Kai Dührkop
Johannes RainerJohannes Rainer
Johannes Rainer
PDPieter C. Dorrestein
Pieter C. Dorrestein
Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.

22 June 2021 in Nature Communications
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Journal Article
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RSRobin Schmid
Robin Schmid
DPDaniel Petras
Daniel Petras
LNLouis-Félix Nothias
Louis-Félix Nothias
MWMingxun Wang
Mingxun Wang
AAAllegra T. Aron
Allegra T. Aron
PDPieter C. Dorrestein
Pieter C. Dorrestein
Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

9 July 2004 in Cell Death & Differentiation
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Journal Article
Closed access
SSS Schmidt
S Schmidt
Johannes RainerJohannes Rainer
Johannes Rainer
CPChristian Ploner
Christian Ploner
EPE Presul
E Presul
SRS Riml
S Riml
RKR Kofler
R Kofler

10 March 2013 in Nature
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Journal Article
Closed access
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THToshikatsu Hanada
Toshikatsu Hanada
SWStefan Weitzer
Stefan Weitzer
BMBarbara Mair
Barbara Mair
CBChristian Bernreuther
Christian Bernreuther
BWBrian J. Wainger
Brian J. Wainger
JPJosef M Penninger
Josef M Penninger

1 July 2006 in Nucleic Acids Research
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Journal Article
Open access
Johannes RainerJohannes Rainer
Johannes Rainer
FSFatima Sanchez-Cabo
Fatima Sanchez-Cabo
GSG. Stocker
G. Stocker
ASA. Sturn
A. Sturn
ZTZ. Trajanoski
Z. Trajanoski
CARMAweb (Comprehensive R-based Microarray Analysis web service) is a web application designed for the analysis of microarray data. CARMAweb performs data preprocessing (background correction, quality control and normalization), detection of differentially expressed genes, cluster analysis, dimension reduction and visualization, classification, and Gene Ontology-term analysis. This web application accepts raw data from a variety of imaging software tools for the most widely used microarray platforms: Affymetrix GeneChips, spotted two-color microarrays and Applied Biosystems (ABI) microarrays. R and packages from the Bioconductor project are used as an analytical engine in combination with the R function Sweave, which allows automatic generation of analysis reports. These report files contain all R commands used to perform the analysis and guarantee therefore a maximum transparency and reproducibility for each analysis. The web application is implemented in Java based on the latest J2EE (Java 2 Enterprise Edition) software technology. CARMAweb is freely available at https://carmaweb.genome.tugraz.at.

25 January 2019 in Bioinformatics
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Journal Article
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Johannes RainerJohannes Rainer
Johannes Rainer
LGLaurent Gatto
Laurent Gatto
CWChristian X Weichenberger
Christian X Weichenberger
Bioinformatics research frequently involves handling gene-centric data such as exons, transcripts, proteins and their positions relative to a reference coordinate system. The ensembldb Bioconductor package retrieves and stores Ensembl-based genetic annotations and positional information, and furthermore offers identifier conversion and coordinates mappings for gene-associated data. In support of reproducible research, data are tied to Ensembl releases and are kept separately from the software. Premade data packages are available for a variety of genomes and Ensembl releases. Three examples demonstrate typical use cases of this software. ensembldb is part of Bioconductor (https://bioconductor.org/packages/ensembldb). Supplementary data are available at Bioinformatics online.