Demo Data from EDBT 2026 / reviewers in the wild / expert
L. L. Kisselev
dblp:08/2327
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1999
—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 · 50% Computational science and engineering · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational science and engineering › data infrastructure
database |
0.0 | 1 | 1999 | Prediction of eukaryotic mRNA translational properties · Bioinform. 1999 |
Bioinformatics and computational biology
gene expression |
0.0 | 1 | 1999 | Prediction of eukaryotic mRNA translational properties · Bioinform. 1999 |
Methods — techniques the papers use, named apart from their topics
sequence feature analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Prediction of eukaryotic mRNA translational propertiesabstractMOTIVATION: It is well known that eukaryotic mRNAs are translated at different levels depending on their sequence characteristics. Evaluation of mRNA translatability is of importance in prediction of the gene expression pattern by computer methods and to improve the recognition of mRNAs within cloned nucleotide sequences. It may also be used in biotechnological experiments to optimize the expression of foreign genes in transgenic organisms. RESULTS: The sets of 5' untranslated region characteristics, significantly different between mRNAs encoding abundant and scarce polypeptides, were determined for mammals, dicot plants and monocot plants, and collected in the LEADER_RNA database. Computer tools for the prediction of mRNA translatability are presented. AVAILABILITY: Programs for mRNA translatability prediction are available at http://wwwmgs.bionet.nsc. ru/programs/acts2/mo_mRNA.htm (for monocots), http://wwwmgs.bionet. nsc.ru/programs/acts2/di_mRNA.htm (for dicots) and http://wwwmgs. bionet.nsc.ru/programs/acts2/ma_mRNA.htm (for mammals). The LEADER_RNA database may be accessed at: http://wwwmgs.bionet.nsc. ru/systems/LeaderRNA/. Alexey V. Kochetov, Mikhail P. Ponomarenko, Anatoly S. Frolov, L. L. Kisselev, Nikolay A. Kolchanov |
Bioinform. | 4 |