Demo Data from VLDB 2026 / reviewers in the wild / expert
Florent E. Angly
dblp:30/3908
· DBLP profile ↗
3ranked-venue papers
3as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 3 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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › microbiology
microbial ecology |
0.2 | 1 | 2014 | The Bio-Community Perl toolkit for microbial ecology · Bioinform. 2014 |
Bioinformatics and computational biology
bioinformatics infrastructure |
0.1 | 1 | 2014 | The Bio-Community Perl toolkit for microbial ecology · Bioinform. 2014 |
Methods — techniques the papers use, named apart from their topics
perl · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | The Bio-Community Perl toolkit for microbial ecologyabstractThe development of bioinformatic solutions for microbial ecology in Perl is limited by the lack of modules to represent and manipulate microbial community profiles from amplicon and meta-omics studies. Here we introduce Bio-Community, an open-source, collaborative toolkit that extends BioPerl. Bio-Community interfaces with commonly used programs using various file formats, including BIOM, and provides operations such as rarefaction and taxonomic summaries. Bio-Community will help bioinformaticians to quickly piece together custom analysis pipelines and develop novel software. Availability an implementation: Bio-Community is cross-platform Perl code available from http://search.cpan.org/dist/Bio-Community under the Perl license. A readme file describes software installation and how to contribute. Florent E. Angly, Christopher J. Fields, Gene W. Tyson |
Bioinform. | 1 |
| 2009 | The GAAS Metagenomic Tool and Its Estimations of Viral and Microbial Average Genome Size in Four Major BiomesabstractMetagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS), a complete software package that provides improved estimates of community composition and average genome length for metagenomes in both textual and graphical formats. GAAS implements a novel methodology to control for sampling bias via length normalization, to adjust for multiple BLAST similarities by similarity weighting, and to select significant similarities using relative alignment lengths. In benchmark tests, the GAAS method was robust to both high percentages of unknown sequences and to variations in metagenomic sequence read lengths. Re-analysis of the Sargasso Sea virome using GAAS indicated that standard methodologies for metagenomic analysis may dramatically underestimate the abundance and importance of organisms with small genomes in environmental systems. Using GAAS, we conducted a meta-analysis of microbial and viral average genome lengths in over 150 metagenomes from four biomes to determine whether genome lengths vary consistently between and within biomes, and between microbial and viral communities from the same environment. Significant differences between biomes and within aquatic sub-biomes (oceans, hypersaline systems, freshwater, and microbialites) suggested that average genome length is a fundamental property of environments driven by factors at the sub-biome level. The behavior of paired viral and microbial metagenomes from the same environment indicated that microbial and viral average genome sizes are independent of each other, but indicative of community responses to stressors and environmental conditions. Florent E. Angly, Dana Willner, Alejandra Prieto-Davó, Robert A. Edwards, Robert Schmieder, Rebecca Vega-Thurber, Dionysios A. Antonopoulos, Katie Barott, Matthew T. Cottrell, Christelle Desnues, Elizabeth A. Dinsdale, Mike Furlan, Matthew Haynes, Matthew R. Henn, Yongfei Hu, David L. Kirchman, Tracey McDole, John D. McPherson, Folker Meyer, R. Michael Miller, Egbert Mundt, Robert K. Naviaux, Beltran Rodriguez-Mueller, Rick L. Stevens, Linda Wegley, Lixin Zhang 0006, Baoli Zhu, Forest Rohwer |
PLoS Comput. Biol. | 1 |
| 2005 | PHACCS, an online tool for estimating the structure and diversity of uncultured viral communities using metagenomic informationabstractBACKGROUND: Phages, viruses that infect prokaryotes, are the most abundant microbes in the world. A major limitation to studying these viruses is the difficulty of cultivating the appropriate prokaryotic hosts. One way around this limitation is to directly clone and sequence shotgun libraries of uncultured viral communities (i.e., metagenomic analyses). PHACCS http://phage.sdsu.edu/phaccs, Phage Communities from Contig Spectrum, is an online bioinformatic tool to assess the biodiversity of uncultured viral communities. PHACCS uses the contig spectrum from shotgun DNA sequence assemblies to mathematically model the structure of viral communities and make predictions about diversity. RESULTS: PHACCS builds models of possible community structure using a modified Lander-Waterman algorithm to predict the underlying contig spectrum. PHACCS finds the most appropriate structure model by optimizing the model parameters until the predicted contig spectrum is as close as possible to the experimental one. This model is the basis for making estimates of uncultured viral community richness, evenness, diversity index and abundance of the most abundant genotype. CONCLUSION: PHACCS analysis of four different environmental phage communities suggests that the power law is an important rank-abundance form to describe uncultured viral community structure. The estimates support the fact that the four phage communities were extremely diverse and that phage community biodiversity and structure may be correlated with that of their hosts. Florent E. Angly, Beltran Rodriguez-Brito, David Bangor, Pat McNairnie, Mya Breitbart, Peter Salamon, Ben Felts, James Nulton, Joseph M. Mahaffy, Forest Rohwer |
BMC Bioinform. | 1 |