Demo Data from VLDB 2026 / reviewers in the wild / expert
David Dineen
dblp:128/7482
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
—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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › multiple sequence alignment
alignment quality assessment |
0.2 | 1 | 2013 | Making automated multiple alignments of very large numbers of protein sequences · Bioinform. 2013 |
Bioinformatics and computational biology
multiple sequence alignment |
0.2 | 1 | 2013 | Making automated multiple alignments of very large numbers of protein sequences · Bioinform. 2013 |
Bioinformatics and computational biology
sequence analysis |
0.2 | 1 | 2013 | Making automated multiple alignments of very large numbers of protein sequences · Bioinform. 2013 |
Bioinformatics and computational biology › structural bioinformatics
protein structure |
0.0 | 1 | 2013 | Making automated multiple alignments of very large numbers of protein sequences · Bioinform. 2013 |
Methods — techniques the papers use, named apart from their topics
iterative refinement · 0.2guide tree construction · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Making automated multiple alignments of very large numbers of protein sequencesabstractMOTIVATION: Recent developments in sequence alignment software have made possible multiple sequence alignments (MSAs) of >100 000 sequences in reasonable times. At present, there are no systematic analyses concerning the scalability of the alignment quality as the number of aligned sequences is increased. RESULTS: We benchmarked a wide range of widely used MSA packages using a selection of protein families with some known structures and found that the accuracy of such alignments decreases markedly as the number of sequences grows. This is more or less true of all packages and protein families. The phenomenon is mostly due to the accumulation of alignment errors, rather than problems in guide-tree construction. This is partly alleviated by using iterative refinement or selectively adding sequences. The average accuracy of progressive methods by comparison with structure-based benchmarks can be improved by incorporating information derived from high-quality structural alignments of sequences with solved structures. This suggests that the availability of high quality curated alignments will have to complement algorithmic and/or software developments in the long-term. AVAILABILITY AND IMPLEMENTATION: Benchmark data used in this study are available at http://www.clustal.org/omega/homfam-20110613-25.tar.gz and http://www.clustal.org/omega/bali3fam-26.tar.gz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Fabian Sievers, David Dineen, Andreas Wilm, Desmond G. Higgins |
Bioinform. | 2 |