Demo Data from EDBT 2026 / reviewers in the wild / expert
William Kaufmann
dblp:97/7065
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2009
—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% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › phylogenetics › phyloinformatics
tree visualization |
0.1 | 1 | 2009 | A novel method for large tree visualization · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
tree layout · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | A novel method for large tree visualizationabstractSUMMARY: Many genomic and proteomic analyses generate as a result a tree of genes or proteins. These trees are often large (containing tens of thousands of nodes and edges), and need a visualization tool to fully display all the information contained in the tree. Clustering analysis can be performed on these trees to obtain clusters of proteins, and we need an efficient way to visualize the clustering results. We present a novel tree visualization tool to help with such analyses. AVAILABILITY: http://www2.renci.org/~jeff/software/bin/win32/ProteinVis-2.1.6-win32.zip. Jeff Heard, William Kaufmann, Xiaojun Guan |
Bioinform. | 2 |