Demo Data from VLDB 2026 / reviewers in the wild / expert
Yoichiro Nakatani
dblp:78/3147
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2017
0000-0001-7604-0242ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 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 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › comparative genomics
ancestral genome reconstruction |
0.3 | 1 | 2017 | Genomes as documents of evolutionary history: a probabilistic macrosynteny model for the reconstruction of ancestral genomes · Bioinform. 2017 |
Bioinformatics and computational biology
comparative genomics |
0.3 | 1 | 2017 | Genomes as documents of evolutionary history: a probabilistic macrosynteny model for the reconstruction of ancestral genomes · Bioinform. 2017 |
Bioinformatics and computational biology › molecular evolution › evolutionary bioinformatics
evolutionary genomics |
0.3 | 1 | 2017 | Genomes as documents of evolutionary history: a probabilistic macrosynteny model for the reconstruction of ancestral genomes · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
variational bayes · 0.3topic model · 0.3probabilistic model · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Genomes as documents of evolutionary history: a probabilistic macrosynteny model for the reconstruction of ancestral genomesabstractMOTIVATION: It has been argued that whole-genome duplication (WGD) exerted a profound influence on the course of evolution. For the purpose of fully understanding the impact of WGD, several formal algorithms have been developed for reconstructing pre-WGD gene order in yeast and plant. However, to the best of our knowledge, those algorithms have never been successfully applied to WGD events in teleost and vertebrate, impeded by extensive gene shuffling and gene losses. RESULTS: Here, we present a probabilistic model of macrosynteny (i.e. conserved linkage or chromosome-scale distribution of orthologs), develop a variational Bayes algorithm for inferring the structure of pre-WGD genomes, and study estimation accuracy by simulation. Then, by applying the method to the teleost WGD, we demonstrate effectiveness of the algorithm in a situation where gene-order reconstruction algorithms perform relatively poorly due to a high rate of rearrangement and extensive gene losses. Our high-resolution reconstruction reveals previously overlooked small-scale rearrangements, necessitating a revision to previous views on genome structure evolution in teleost and vertebrate. CONCLUSIONS: We have reconstructed the structure of a pre-WGD genome by employing a variational Bayes approach that was originally developed for inferring topics from millions of text documents. Interestingly, comparison of the macrosynteny and topic model algorithms suggests that macrosynteny can be regarded as documents on ancestral genome structure. From this perspective, the present study would seem to provide a textbook example of the prevalent metaphor that genomes are documents of evolutionary history. AVAILABILITY AND IMPLEMENTATION: The analysis data are available for download at http://www.gen.tcd.ie/molevol/supp_data/MacrosyntenyTGD.zip , and the software written in Java is available upon request. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Yoichiro Nakatani, Aoife McLysaght |
Bioinform. | 1 |