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Yingbo Cui

As seen in: Wiley Online Library, Genome Biology
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Articles

[2511.10180] Selection of Supervised Learning-based Sparse Matrix Reordering Algorithms

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By Yingbo Cui, Jianbin Fang, Peng Zhang, Youfu Jiang
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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SpaBalance: Balanced Learning for Efficient Spatial Multi‐Omics Decoding

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By Yingbo Cui, Yong Zhao, Canqun Yang, Tao Tang
| Wiley Online Library Verified
1 Introduction In recent years, spatial multi-omics technologies have advanced rapidly, enabling the simultaneous acquisition of multi-layered omics data along with their spatial localization. This breakthrough overcomes the limitations of conventional sequencing methods,[1-4] which rely on aligning sequencing reads to reconstruct transcript structures and measure gene expression levels, but typically lack spatial information.
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A survey of sequence-to-graph mapping algorithms in the pangenome era - Genome Biology

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By Chenchen Peng, Zeyu Xia, Canqun Yang, Yifei Guo, Yingbo Cui
| Genome Biology Verified
We consider “mapping” to be a more general concept than “alignment.” “Mapping” refers to the process of locating the approximate position of a sequence within a reference without precise “alignment” [6, 40]. It can also encompass the entire process, including exact “alignment,” such as GenomeMapper [21] or VG map [41]. In contrast, “alignment” specifically denotes the process of achieving base-level precision in matching, as seen in algorithms like Smith-Waterman (SW) [42] and WFA [43, 44].
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