Author

X.-X. Pang

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Evolutionary Biology· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:chromatin & epigenetic regulation· 2 Research Focus:phylogenetics / evolution· 2 Approach:Bayesian inference· 1 Organism:C. elegans· 1 Research Focus:gene regulatory network inference· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

D.-Y. Zhang· 3 shared P. Li· 1 shared W.-N. Bai· 1 shared W.-P. Zhang· 1 shared Y. Cao· 1 shared Y. Yang· 1 shared Y.-M. Ding· 1 shared

Activity by Year

2023-2024 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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3 shared papersEvolutionary Biology

D.-Y. Zhang

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3 papers

Recent·Most cited

A Cautionary Note on Using STRUCTURE to Detect Hybridization in a Phylogenetic Context

X.-X. Pang, D.-Y. Zhang

This study evaluates STRUCTURE's performance in detecting hybridization across phylogenetic scales, finding it ineffective for ancient or ghost admixtures.

bioRxiv · Feb 6, 2024Evolutionary Biology

Uncovering Ghost Introgression Through Genomic Analysis of a Distinct East Asian Hickory Species

W.-P. Zhang, Y.-M. Ding, Y. Cao, P. Li, Y. Yang, X.-X. Pang, W.-N. Bai, D.-Y. Zhang

The paper detects ghost introgression in Carya sinensis using genomic analysis and phylogenetic methods, revealing introgression from an extinct lineage.

bioRxiv · Jun 26, 2023 · PreprintEvolutionary Biology

Detection of Ghost Introgression from Phylogenomic Data Requires a Full-Likelihood Approach

X.-X. Pang, D.-Y. Zhang

The paper evaluates methods for detecting ghost introgression and finds that full-likelihood approaches like BPP outperform heuristic methods in accurate identification.

bioRxiv · Apr 29, 2023Evolutionary Biology