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Xiaohan Yang
Researcher at Oak Ridge National Laboratory
Publications - 151
Citations - 8806
Xiaohan Yang is an academic researcher from Oak Ridge National Laboratory. The author has contributed to research in topics: Biology & Gene. The author has an hindex of 36, co-authored 122 publications receiving 7296 citations. Previous affiliations of Xiaohan Yang include Battelle Memorial Institute & University of Tennessee.
Papers
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Journal ArticleDOI
Third-codon transversion rate-based _Nymphaea_ basal angiosperm phylogeny -- concordance with developmental evidence
TL;DR: It is shown that the 3rd codon transversion (P3Tv), with high neutrality and low saturation, is a robust high-resolution phylogenetic signal for such divergences and that the P3TV-based land plant phylogeny cautiously identifies _Nymphaea_, followed by _Amborella_, as the most basal among the angiosperm species examined in this study.
Posted ContentDOI
Plant-based biosensors for detecting CRISPR-mediated genome engineering
Guoliang Yuan,Md. Mahmudul Hassan,Md. Mahmudul Hassan,Tao Yao,Haiwei Lu,Michael Melesse Vergara,Jesse L. Labbé,Wellington Muchero,Changtian Pan,Jin-Gui Chen,Gerald A. Tuskan,Yiping Qi,Paul E. Abraham,Xiaohan Yang +13 more
TL;DR: In this paper, the authors developed a real-time detection system that can spontaneously indicate CRISPR-Cas tools for genome editing and gene regulation in biological systems, such as Nuclease, base editing, prime editing, and CRISpra in plants.
Journal ArticleDOI
Biodesign Research to Advance the Principles and Applications of Biosystems Design
Xiaohan Yang,Lei S. Qi,Alfonso Jaramillo,Alfonso Jaramillo,Alfonso Jaramillo,Zong-Ming Cheng,Zong-Ming Cheng +6 more
TL;DR: In this article, the authors presented the results of a study at the Oak Ridge National Laboratory (ORNL) and the Center for Bioenergy Innovation (CBIE) in the US.
Journal ArticleDOI
PPCM: Combing Multiple Classifiers to Improve Protein-Protein Interaction Prediction
TL;DR: A robust pipeline for PPI prediction is established by integrating multiple classifiers using Random Forests algorithm, which will be useful for predicting PPI in nonmodel species.
Patent
Tnt cloning system
TL;DR: In this paper, the authors present vectors and components for a nucleic acid cloning system, and methods of use of the vectors and component in cloning nucleic acids fragments of interest.