Xiaochen Bo

6.9k total citations · 2 hit papers
166 papers, 4.2k citations indexed

About

Xiaochen Bo is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research. According to data from OpenAlex, Xiaochen Bo has authored 166 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 130 papers in Molecular Biology, 39 papers in Computational Theory and Mathematics and 21 papers in Cancer Research. Recurrent topics in Xiaochen Bo's work include Bioinformatics and Genomic Networks (43 papers), Computational Drug Discovery Methods (37 papers) and Genomics and Chromatin Dynamics (22 papers). Xiaochen Bo is often cited by papers focused on Bioinformatics and Genomic Networks (43 papers), Computational Drug Discovery Methods (37 papers) and Genomics and Chromatin Dynamics (22 papers). Xiaochen Bo collaborates with scholars based in China, United States and United Kingdom. Xiaochen Bo's co-authors include Shengqi Wang, Fei Li, Wenjie Shu, Guangchuang Yu, Yide Qin, Yibo Wu, Feng Liu, Hebing Chen, Song He and Shengjun Wang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Xiaochen Bo

155 papers receiving 4.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

GOSemSim: an R package for measuring semantic similarity among GO terms and gene products

2010 852 citations Xiaochen Bo, Shengqi Wang et al. profile →
Deep Learning and Its Applications in Biomedicine

2018 404 citations Feng Liu, Wenjie Shu et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xiaochen Bo China	31	2.7k	567	553	360	306	166	4.2k
Mickaël Guedj France	23	2.2k 0.8×	362 0.6×	413 0.7×	435 1.2×	231 0.8×	54	4.0k
Farrokh Mehryary Finland	8	2.1k 0.8×	235 0.4×	460 0.8×	347 1.0×	241 0.8×	15	3.8k
James C. Costello United States	29	2.9k 1.1×	231 0.4×	528 1.0×	365 1.0×	212 0.7×	82	4.6k
Bo Li China	33	2.3k 0.9×	333 0.6×	414 0.7×	266 0.7×	128 0.4×	198	4.3k
Sune Pletscher-Frankild Denmark	15	4.4k 1.6×	563 1.0×	800 1.4×	481 1.3×	340 1.1×	17	6.1k
Shanrong Zhao United States	19	2.1k 0.8×	866 1.5×	480 0.9×	251 0.7×	170 0.6×	35	3.7k
Pingzhao Hu Canada	38	2.2k 0.8×	352 0.6×	668 1.2×	687 1.9×	294 1.0×	167	4.3k
Yuhang Zhang China	36	2.4k 0.9×	237 0.4×	830 1.5×	205 0.6×	265 0.9×	280	4.4k
Guanming Wu United States	23	3.1k 1.2×	404 0.7×	682 1.2×	320 0.9×	294 1.0×	46	3.9k
Weiwei Xue China	41	3.3k 1.3×	1.0k 1.8×	377 0.7×	151 0.4×	243 0.8×	177	5.7k

Countries citing papers authored by Xiaochen Bo

Since Specialization

Citations

This map shows the geographic impact of Xiaochen Bo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaochen Bo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaochen Bo more than expected).

Fields of papers citing papers by Xiaochen Bo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaochen Bo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaochen Bo. The network helps show where Xiaochen Bo may publish in the future.

Co-authorship network of co-authors of Xiaochen Bo

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaochen Bo. A scholar is included among the top collaborators of Xiaochen Bo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaochen Bo. Xiaochen Bo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Li, Jingyang, Yanpeng Zhao, Zhenting Wang, et al.. (2025). Identify drug-drug interactions via deep learning: A real world study. Journal of Pharmaceutical Analysis. 15(6). 101194–101194.

Wen, Yuqi, et al.. (2024). Multi-view uncertainty deep forest: An innovative deep forest equipped with uncertainty estimation for drug-induced liver injury prediction. Information Sciences. 667. 120342–120342. 2 indexed citations

Ren, Zilin, et al.. (2024). DeepPFP: a multi-task-aware architecture for protein function prediction. Briefings in Bioinformatics. 26(1). 1 indexed citations

Zhao, Yanpeng, et al.. (2024). A Point Cloud Graph Neural Network for Protein–Ligand Binding Site Prediction. International Journal of Molecular Sciences. 25(17). 9280–9280. 4 indexed citations

Xu, Xiang, Dandan Huang, Lin Lin, et al.. (2024). A comprehensive benchmarking with interpretation and operational guidance for the hierarchy of topologically associating domains. Nature Communications. 15(1). 4376–4376. 7 indexed citations

Ouyang, Zhangyi, Feng Liu, Wanying Li, et al.. (2024). The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model. Nucleic Acids Research. 52(13). 7610–7626. 2 indexed citations

Wang, Junting, Chengyue Zhang, Li Zhang, et al.. (2023). Comparative study on genomic and epigenomic profiles of retinoblastoma or tuberous sclerosis complex via nanopore sequencing and a joint screening framework. Cancer Gene Therapy. 31(3). 439–453.

Song, Bin, Peilin Zhang, Zhi Zhong, et al.. (2023). PC3T: a signature-driven predictor of chemical compounds for cellular transition. Communications Biology. 6(1). 989–989. 1 indexed citations

Zhang, Yinan, Xiaoyao Yin, Kun He, et al.. (2023). Prime factorization via localized tile assembly in a DNA origami framework. Science Advances. 9(13). eadf8263–eadf8263. 7 indexed citations

10.

Chen, Jing, Lianlian Wu, Kunhong Liu, et al.. (2023). EDST: a decision stump based ensemble algorithm for synergistic drug combination prediction. BMC Bioinformatics. 24(1). 325–325. 6 indexed citations

11.

Su, Jiayu, et al.. (2023). A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures. Genome Research. 33(8). 1381–1394. 12 indexed citations

12.

Wang, Bolun, Shuo Liu, Xinyu He, et al.. (2022). ACE2 decoy receptor generated by high-throughput saturation mutagenesis efficiently neutralizes SARS-CoV-2 and its prevalent variants. Emerging Microbes & Infections. 11(1). 1488–1499. 7 indexed citations

13.

Guo, Dan, Qiu Xie, Shuai Jiang, et al.. (2021). Synergistic alterations in the multilevel chromatin structure anchor dysregulated genes in small cell lung cancer. Computational and Structural Biotechnology Journal. 19. 5946–5959. 6 indexed citations

14.

Hong, Hao, Shuai Jiang, Hao Li, et al.. (2020). DeepHiC: A generative adversarial network for enhancing Hi-C data resolution. PLoS Computational Biology. 16(2). e1007287–e1007287. 50 indexed citations

15.

Wen, Yuqi, et al.. (2020). Exploring the classification of cancer cell lines from multiple omic views. PeerJ. 8. e9440–e9440. 7 indexed citations

16.

Li, Ruijiang, Shuai Jiang, Wanying Li, et al.. (2019). Exploration of prognosis-related microRNA and transcription factor co-regulatory networks across cancer types. RNA Biology. 16(8). 1010–1021. 6 indexed citations

17.

Li, Ruijiang, Hebing Chen, Shuai Jiang, et al.. (2018). CMTCN: a web tool for investigating cancer-specific microRNA and transcription factor co-regulatory networks. PeerJ. 6. e5951–e5951. 8 indexed citations

18.

Zhang, Zhongnan, et al.. (2017). Drug—target interaction prediction with a deep-learning-based model. 469–476. 9 indexed citations

19.

Ni, Ming, Wenjie Shu, Xiaochen Bo, Shengqi Wang, & Songgang Li. (2010). Correlation between sequence conservation and structural thermodynamics of microRNA precursors from human, mouse, and chicken genomes. BMC Evolutionary Biology. 10(1). 329–329. 11 indexed citations

20.

Bo, Xiaochen, et al.. (2001). Tumour necrosis factor α impairs function of liver derived T lymphocytes and natural killer cells in patients with primary sclerosing cholangitis. Gut. 49(1). 131–141. 92 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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