EDBT 2026 Demo / reviewers in the wild / expert
Wei-Cheng Gu
dblp:159/2223
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 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 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › genomics
genome organization |
0.7 | 1 | 2023 | EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficient · Bioinform. 2023 |
Methods — techniques the papers use, named apart from their topics
error-vector resultant · 0.7clustering coefficient · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficientabstractMOTIVATION: Reconstruction of 3D structure models is of great importance for the study of chromosome function. Software tools for this task are highly needed. RESULTS: We present a novel reconstruction algorithm, called EVRC, which utilizes co-clustering coefficients and error-vector resultant for chromosome 3D structure reconstruction. As an update of our previous EVR algorithm, EVRC now can deal with both single and multiple chromosomes in structure modeling. To evaluate the effectiveness and accuracy of the EVRC algorithm, we applied it to simulation datasets and real Hi-C datasets. The results show that the reconstructed structures have high similarity to the original/real structures, indicating the effectiveness and robustness of the EVRC algorithm. Furthermore, we applied the algorithm to the 3D conformation reconstruction of the wild-type and mutant Arabidopsis thaliana chromosomes and demonstrated the differences in structural characteristics between different chromosomes. We also accurately showed the conformational change in the centromere region of the mutant compared with the wild-type of Arabidopsis chromosome 1. Our EVRC algorithm is a valuable software tool for the field of chromatin structure reconstruction, and holds great promise for advancing our understanding on the chromosome functions. AVAILABILITY AND IMPLEMENTATION: The software is available at https://github.com/mbglab/EVRC. Wei-Cheng Gu, Bin-Guang Ma |
Bioinform. | 2 |