Demo Data from EDBT 2026 / reviewers in the wild / expert
S. Laiter
dblp:35/1911
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1995
—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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
protein structure analysis |
0.0 | 1 | 1995 | Rapid protein structure classification using one-dimensional structure profiles on the bioSCAN parallel computer · Comput. Appl. Biosci. 1995 |
Bioinformatics and computational biology › structural bioinformatics
protein structure classification |
0.0 | 1 | 1995 | Rapid protein structure classification using one-dimensional structure profiles on the bioSCAN parallel computer · Comput. Appl. Biosci. 1995 |
Methods — techniques the papers use, named apart from their topics
weighted scoring matrix · 0.0pseudodihedral angle encoding · 0.0parallel sequence alignment · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Rapid protein structure classification using one-dimensional structure profiles on the bioSCAN parallel computerabstractRapid growth of protein structures database in recent years requires an effective approach for objective comparison and classification of deposited protein structures. We describe a novel method for structure comparison and classification based on the alignment of one-dimensional structure profiles. These profiles are obtained by calculating the OCCO pseudodihedral angles (formed by O-C-C-O atoms of carbonyl groups of consecutive amino acid residues) from protein three-dimensional coordinates. These angle measurements are then converted into a 24 letter alphabet, and the protein structures are represented by sequences of letter from this alphabet. The BioSCAN parallel computer, designed for primary sequence alignment, is used to rapidly align and classify these one-dimensional structure profiles. We have developed and implemented weighted scoring matrix to identify structural classes based on commonly found structural motifs. The results of our experiments are in good agreement with the traditional protein structure classification schemes. One-dimensional structure profiles significantly improve efficiency of structure comparison and classification. D. L. Hoffman, S. Laiter, Raj K. Singh, Iosif I. Vaisman, Alexander Tropsha |
Comput. Appl. Biosci. | 2 |