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Heiko Giese

dblp:157/9538 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0002-5786-901XORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2 · 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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
signaling pathway analysis
0.412019
isiKnock: in silico knockouts in signaling pathways · Bioinform. 2019
Bioinformatics and computational biology
proteomics
0.212015
NOVA: a software to analyze complexome profiling data · Bioinform. 2015

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

transition invariants · 0.4manatee invariants · 0.4cluster analysis · 0.2
YearPublicationVenuePosition
2019 isiKnock: in silico knockouts in signaling pathways
abstract
SUMMARY: isiKnock is a new software that automatically conducts in silico knockouts for mathematical models of signaling pathways. The software allows for the prediction of the behavior of biological systems after single or multiple knockout. The implemented algorithm applies transition invariants and the novel concept of Manatee invariants. A knockout matrix visualizes the results. The tool enables the analysis of dependencies, for example, in signal flows from the receptor activation to the cell response at steady state. AVAILABILITY AND IMPLEMENTATION: isiKnock is an open-source tool, freely available at http://www.bioinformatik.uni-frankfurt.de/tools/isiKnock/. It requires at least Java 8 and runs under Microsoft Windows, Linux, and Mac OS.
Jennifer Hannig, Heiko Giese, Börje Schweizer, Leonie Amstein, Jörg Ackermann 0001, Ina Koch
Bioinform.2
2015 NOVA: a software to analyze complexome profiling data
abstract
SUMMARY: We introduce nova, a software for the analysis of complexome profiling data. nova supports the investigation of the composition of complexes, cluster analysis of the experimental data, visual inspection and comparison of experiments and many other features. AVAILABILITY AND IMPLEMENTATION: nova is licensed under the Artistic License 2.0. It is freely available at http://www.bioinformatik.uni-frankfurt.de. nova requires at least Java 7 and runs under Linux, Microsoft Windows and Mac OS. CONTACT: [email protected].
Heiko Giese, Jörg Ackermann 0001, Heinrich Heide, Lea Bleier, Stefan Dröse, Ilka Wittig, Ulrich Brandt, Ina Koch
Bioinform.1