RiboBA: a bias-aware probabilistic framework for robust ORF identification across diverse ribosome profiling protocols
RiboBA improves ncORF identification by accounting for protocol-induced biases in ribosome profiling data.
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Northwest A&F UniversityORCID 0000-0001-6241-6317Unclaimed ORCID profile · follow to get notified of new preprints
4 papers
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RiboBA improves ncORF identification by accounting for protocol-induced biases in ribosome profiling data.
Juan Bai, Yanfen Fan, Ruolin Yang, Jingquan Yu
This study shows FERONIA affects translational buffering of ribosome-associated genes in tomato roots under salt stress, altering translational efficiency and gene expression patterns.
Shipeng Yang, Cheng Si, Xiaoting Jiang…·Ruolin Yang
This study constructs a single-cell transcriptomic atlas of tomato adventitious root development, identifying vascular tissues as key regulators of cell fate transitions and revealing conserved molecular mechanisms across species.
Zhenhao Zhang, Yuxi Liu, Meichen Xiao…·Fuyi Li
This paper introduces scSimGCL, a graph contrastive learning framework for scRNA-seq data that improves cell clustering through self-supervised pretraining and high-quality representation learning.