Demo Data from EDBT 2026 / reviewers in the wild / expert
Rafael F. Guerrero
dblp:277/1048
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0002-8451-3609ORCID · reported
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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › functional genomics
gene function prediction |
0.4 | 1 | 2020 | The ortholog conjecture revisited: the value of orthologs and paralogs in function prediction · Bioinform. 2020 |
Bioinformatics and computational biology › protein function prediction › sequence-based protein function prediction
homology-based function transfer |
0.4 | 1 | 2020 | The ortholog conjecture revisited: the value of orthologs and paralogs in function prediction · Bioinform. 2020 |
Methods — techniques the papers use, named apart from their topics
statistical analysis · 0.4annotation transfer · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | The ortholog conjecture revisited: the value of orthologs and paralogs in function predictionabstractMOTIVATION: The computational prediction of gene function is a key step in making full use of newly sequenced genomes. Function is generally predicted by transferring annotations from homologous genes or proteins for which experimental evidence exists. The 'ortholog conjecture' proposes that orthologous genes should be preferred when making such predictions, as they evolve functions more slowly than paralogous genes. Previous research has provided little support for the ortholog conjecture, though the incomplete nature of the data cast doubt on the conclusions. RESULTS: We use experimental annotations from over 40 000 proteins, drawn from over 80 000 publications, to revisit the ortholog conjecture in two pairs of species: (i) Homo sapiens and Mus musculus and (ii) Saccharomyces cerevisiae and Schizosaccharomyces pombe. By making a distinction between questions about the evolution of function versus questions about the prediction of function, we find strong evidence against the ortholog conjecture in the context of function prediction, though questions about the evolution of function remain difficult to address. In both pairs of species, we quantify the amount of information that would be ignored if paralogs are discarded, as well as the resulting loss in prediction accuracy. Taken as a whole, our results support the view that the types of homologs used for function transfer are largely irrelevant to the task of function prediction. Maximizing the amount of data used for this task, regardless of whether it comes from orthologs or paralogs, is most likely to lead to higher prediction accuracy. AVAILABILITY AND IMPLEMENTATION: https://github.com/predragradivojac/oc. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Moses Stamboulian, Rafael F. Guerrero, Matthew W. Hahn, Predrag Radivojac |
Bioinform. | 2 |