Demo Data from SIGIR 2026 / reviewers in the wild / expert
Steven W. Singer
dblp:176/9805
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · unresolved
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 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › metagenomics › metagenome-assembled genome
metagenome-assembled genome reconstruction |
0.2 | 1 | 2016 | MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets · Bioinform. 2016 |
Bioinformatics and computational biology
metagenomics |
0.2 | 1 | 2016 | MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets · Bioinform. 2016 |
Bioinformatics and computational biology › metagenomics
metagenomic binning |
0.2 | 1 | 2016 | MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets · Bioinform. 2016 |
Methods — techniques the papers use, named apart from their topics
co-assembly · 0.2automated binning · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasetsabstractUNLABELLED: The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments. AVAILABILITY AND IMPLEMENTATION: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Blake A. Simmons, Steven W. Singer |
Bioinform. | 3 |