Demo Data from VLDB 2026 / reviewers in the wild / expert
Cezar Bendic
dblp:61/4100
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1996
—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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › structural bioinformatics
macromolecular structure analysis |
0.0 | 1 | 1996 | HBexplore - a new tool for identifying and analysing hydrogen bonding patterns in biological macromolecules · Comput. Appl. Biosci. 1996 |
Bioinformatics and computational biology › structural bioinformatics
nucleic acid structure analysis |
0.0 | 1 | 1996 | HBexplore - a new tool for identifying and analysing hydrogen bonding patterns in biological macromolecules · Comput. Appl. Biosci. 1996 |
Bioinformatics and computational biology
structural biology |
0.0 | 1 | 1996 | HBexplore - a new tool for identifying and analysing hydrogen bonding patterns in biological macromolecules · Comput. Appl. Biosci. 1996 |
Methods — techniques the papers use, named apart from their topics
geometric criteria analysis · 0.0binary tree search · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | HBexplore - a new tool for identifying and analysing hydrogen bonding patterns in biological macromoleculesabstractThe program HBexplore is a new tool for identifying and analysing H-bonding patterns in biological macromolecules. It selects all potential H-bonds according to geometrical criteria. The H-bond table can then be subjected to further automatic or interactive analysis tools. These tools include the calculation of mean values and distributions of geometrical H-bond parameters for parts of a single structure, for complete single structures and for structure sets, the classification of each H-bond according to the participation of backbone, side chain or base, ligand and water parts of nucleic acids or proteins, identification of Watson-Crick nucleotide pairs and of H-bonded pairs of equal nucleotides, the calculation of the mean number of H-bonds per residue, and of the fraction of potential donor and acceptor atoms involved in H-bonds. HBexplore further generates automatically a H-bond residue interaction table. This table lists for all residues of the structure the other residues, ligands or water molecules directly connected via a H-bond. By means of a binary tree search algorithm, this table is then converted into a H-bond cluster table. Clusters are understood here as an uninterrupted network of H-bonded residues. For nucleic acids, secondary structures and tertiary interactions are automatically derived from the H-bonding pattern. HBexplore is applied to two example RNA structures: a pseudoknot and a hairpin. It provides a comprehensive listing of individual H-bonds and statistical information for larger structure sets. In addition, it can identify interesting new H-bond motifs. One example is a pentanucleotide base-base H-bond interaction motif in the RNA pseudoknot. HBexplore is intended to contribute both to the elucidation of general principles of the architecture of biological macromolecules, and to the prediction and refinement of single structures. Klaus Lindauer, Cezar Bendic, Jürgen Sühnel |
Comput. Appl. Biosci. | 2 |