Demo Data from EDBT 2026 / reviewers in the wild / expert
Zhu-Jin Zhang
dblp:51/7065
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021
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 › sequence analysis › sequence visualization
DNA sequence visualization |
0.1 | 1 | 2009 | DV-Curve: a novel intuitive tool for visualizing and analyzing DNA sequences · Bioinform. 2009 |
Bioinformatics and computational biology
sequence analysis |
0.1 | 1 | 2009 | DV-Curve: a novel intuitive tool for visualizing and analyzing DNA sequences · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
dual-vector curve · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Imputing DNA Methylation by Transferred Learning Based Neural Network
Xinfeng Wang, Jiahua Rao, Zhu-Jin Zhang, Yuedong Yang |
J. Comput. Sci. Technol. | 4 |
| 2009 | DV-Curve: a novel intuitive tool for visualizing and analyzing DNA sequencesabstractMOTIVATION: The rapid growth of DNA sequence data creates a need to find graphic tools to study DNA sequence in a perceivable form. A large number of scholars work hard in this field. However, it is difficult to handle the following problems in one graph: (i) degeneracy, (ii) loss of information, (iii) difficulty of observing in multi-dimensional graph, (iv) difficulty of visualization when representing long DNA sequences and (v) need to reflect useful information. RESULTS: DV-Curve (Dual-Vector Curve) using two vectors to represent one alphabet of DNA sequences not only avoids degeneracy and loss of information, but also has good visualization no matter whether sequences are long, and can reflect the length of DNA sequence. The applications of the DV-Curve on mutation analysis and two types of similarity analysis are presented in detail. DV-Curve is a significative tool by which biologists could find useful biological knowledge. AVAILABILITY: The corresponding software of DV-Curve is available at http://bmchust.3322.org/Data/Soft/332-DV-Curve2.0.zip. Zhu-Jin Zhang |
Bioinform. | 1 |