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Niklas Niehus

dblp:247/1814 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › sequence assembly
assembly visualization
0.412019
GfaViz: flexible and interactive visualization of GFA sequence graphs · Bioinform. 2019
Visualization and visual analytics
biological data visualization
0.112019
GfaViz: flexible and interactive visualization of GFA sequence graphs · Bioinform. 2019
Visualization and visual analytics › graph visualization
interactive graph visualization
0.112019
GfaViz: flexible and interactive visualization of GFA sequence graphs · Bioinform. 2019

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

stylesheet-based configuration · 0.8interactive layout · 0.8
YearPublicationVenuePosition
2019 GfaViz: flexible and interactive visualization of GFA sequence graphs
abstract
SUMMARY: The graphical fragment assembly (GFA) formats are emerging standard formats for the representation of sequence graphs. Although GFA 1 was primarily targeting assembly graphs, the newer GFA 2 format introduces several features, which makes it suitable for representing other kinds of information, such as scaffolding graphs, variation graphs, alignment graphs and colored metagenomic graphs. Here, we present GfaViz, an interactive graphical tool for the visualization of sequence graphs in GFA format. The software supports all new features of GFA 2 and introduces conventions for their visualization. The user can choose between two different layouts and multiple styles for representing single elements or groups. All customizations can be stored in custom tags of the GFA format itself, without requiring external configuration files. Stylesheets are supported for storing standard configuration options for groups of files. The visualizations can be exported to raster and vector graphics formats. A command line interface allows for batch generation of images. AVAILABILITY AND IMPLEMENTATION: GfaViz is available at https://github.com/ggonnella/gfaviz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Giorgio Gonnella, Niklas Niehus, Stefan Kurtz
Bioinform.2