Demo Data from EDBT 2026 / reviewers in the wild / expert
Kevin A Li
dblp:440/7288
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0009-0446-6135ORCID · reported
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 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › population genetics
kinship estimation |
1.0 | 1 | 2026 | Fault-tolerant pedigree reconstruction from pairwise kinship relations · Bioinform. 2026 |
Bioinformatics and computational biology › population genetics
pedigree reconstruction |
1.0 | 1 | 2026 | Fault-tolerant pedigree reconstruction from pairwise kinship relations · Bioinform. 2026 |
Methods — techniques the papers use, named apart from their topics
sampling · 1.0pruning · 1.0iterative search · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Fault-tolerant pedigree reconstruction from pairwise kinship relationsabstractMOTIVATION: Pedigrees reconstructed from biologically related ancient genomes have revealed many insights into (pre)history. To our knowledge, all reported ancient pedigrees have been primarily manually reconstructed, as existing pedigree reconstruction methods are ill-suited for the quality and nature of ancient DNA data. RESULTS: We introduce repare, an open-source software method to automatically reconstruct pedigrees from inferred pairwise kinship relations, which are readily obtainable from ancient genomes. This method reconstructs pedigrees by iteratively incorporating pairwise kinship relations into a set of candidate pedigrees, with pruning and sampling to reduce its search space. It optionally considers supporting information such as haplogroups and skeletal age-at-death estimates. We evaluate this method on a variety of simulated pedigrees with varying error rates and missingness. We also use this method to reconstruct several published pedigrees that were originally manually reconstructed; for one, we present a potential alternative topology. repare optionally incorporates user-inferred pedigree constraints, enabling "human-in-the-loop" reconstruction workflows. Especially when used with these user-inferred constraints, we find that repare represents a powerful and flexible tool for ancient pedigree reconstruction. AVAILABILITY AND IMPLEMENTATION: repare is freely available at https://github.com/Narasimhan-Lab/repare. In addition, source code, benchmark scripts, and benchmark results used in this work are archived at https://doi.org/10.5281/zenodo.19716772. Edward C. Huang, Kevin A Li, Vagheesh M. Narasimhan |
Bioinform. | 2 |