Demo Data from VLDB 2026 / reviewers in the wild / expert
Carl R. Woese
dblp:16/3728
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 1994
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
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
2 papers |
Bioinformatics and computational biology · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
User interface design and tools · 100% | |
| Theoretical computer science
1 paper |
Algorithms and data structures · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
multiple sequence alignment |
0.0 | 1 | 1994 | The genetic data environment an expandable GUI for multiple sequence analysis · Comput. Appl. Biosci. 1994 |
Bioinformatics and computational biology
sequence analysis |
0.0 | 1 | 1994 | The genetic data environment an expandable GUI for multiple sequence analysis · Comput. Appl. Biosci. 1994 |
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure prediction |
0.0 | 1 | 1990 | Structure detection through automated covariance search · Comput. Appl. Biosci. 1990 |
User interface design and tools
graphical user interface |
0.0 | 1 | 1994 | The genetic data environment an expandable GUI for multiple sequence analysis · Comput. Appl. Biosci. 1994 |
Algorithms and data structures › computational biology
sequence analysis |
0.0 | 1 | 1990 | Structure detection through automated covariance search · Comput. Appl. Biosci. 1990 |
Methods — techniques the papers use, named apart from their topics
x-windows · 0.0external program integration · 0.0covariation analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | The genetic data environment an expandable GUI for multiple sequence analysisabstractAn X-Windows-based graphic user interface is presented which allows the seamless integration of numerous existing biomolecular programs into a single analysis environment. This environment is based on a core multiple sequence editor that is linked to external programs by a user-expandable menu system and is supported on Sun and DEC workstations. There is no limitation to the number of external functions that can be linked to the interface. The length and number of sequences that can be handled are limited only by the size of virtual memory present on the workstation. The sequence data itself is used as the reference point from which analysis is done, and scalable graphic views are supported. It is suggested that future software development utilizing this expandable, user-defined menu system and the I/O linkage of external programs will allow biologists to easily integrate expertise from disparate fields into a single environment. Steven W. Smith, Ross A. Overbeek, Carl R. Woese, W. Gilbert, P. M. Gillevet |
Comput. Appl. Biosci. | 3 |
| 1990 | Structure detection through automated covariance searchabstractThis paper summarizes our investigations into the computational detection of secondary and tertiary structure of ribosomal RNA. We have developed a new automated procedure that not only identifies potential secondary and tertiary structural interactions, but also provides the covariation evidence that supports the proposed bondings, and any counterevidence that can be detected in the known sequences. A small number of previously unknown higher-order structural features have been detected in individual RNA molecules (16S rRNA and 7S RNA) through the use of our automated procedure. We are systematically studying mitochondrial rRNA, seeking tertiary structure within 16S rRNA and quaternary structure between 16S and 23S rRNA. To test hypotheses suggested by an examination of our program's output, our colleagues in biology are sequencing key portions of the 23S ribosomal RNA for species in which the known 16S ribosomal RNA exhibits variation (from the dominant pattern) at the site of a proposed bonding. Our ultimate hope is that automated covariation analysis will contribute significantly to a refined picture of ribosomal structure. Steven K. Winker, Ross A. Overbeek, Carl R. Woese, Gary J. Olsen, N. Pfluger |
Comput. Appl. Biosci. | 3 |