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Astrid Wachter

dblp:168/1195 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
multi-omics data integration
0.212015
pwOmics: an R package for pathway-based integration of time-series omics data using public database knowledge · Bioinform. 2015
Bioinformatics and computational biology › biological network › network biology
network inference
0.212015
pwOmics: an R package for pathway-based integration of time-series omics data using public database knowledge · Bioinform. 2015
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
pathway-based data integration
0.212015
pwOmics: an R package for pathway-based integration of time-series omics data using public database knowledge · Bioinform. 2015

Methods — techniques the papers use, named apart from their topics

steiner tree · 0.2dynamic bayesian network inference · 0.2
YearPublicationVenuePosition
2015 pwOmics: an R package for pathway-based integration of time-series omics data using public database knowledge
abstract
UNLABELLED: Characterization of biological processes is progressively enabled with the increased generation of omics data on different signaling levels. Here we present a straightforward approach for the integrative analysis of data from different high-throughput technologies based on pathway and interaction models from public databases. pwOmics performs pathway-based level-specific data comparison of coupled human proteomic and genomic/transcriptomic datasets based on their log fold changes. Separate downstream and upstream analyses results on the functional levels of pathways, transcription factors and genes/transcripts are performed in the cross-platform consensus analysis. These provide a basis for the combined interpretation of regulatory effects over time. Via network reconstruction and inference methods (Steiner tree, dynamic Bayesian network inference) consensus graphical networks can be generated for further analyses and visualization. AVAILABILITY AND IMPLEMENTATION: The R package pwOmics is freely available on Bioconductor (http://www.bioconductor.org/). CONTACT: [email protected].
Astrid Wachter, Tim Beißbarth
Bioinform.1