Jiu-Xin Tan

593 total citations
8 papers, 502 citations indexed

About

Jiu-Xin Tan is a scholar working on Molecular Biology, Epidemiology and Spectroscopy. According to data from OpenAlex, Jiu-Xin Tan has authored 8 papers receiving a total of 502 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 1 paper in Epidemiology and 1 paper in Spectroscopy. Recurrent topics in Jiu-Xin Tan's work include Machine Learning in Bioinformatics (7 papers), RNA and protein synthesis mechanisms (6 papers) and Genomics and Phylogenetic Studies (5 papers). Jiu-Xin Tan is often cited by papers focused on Machine Learning in Bioinformatics (7 papers), RNA and protein synthesis mechanisms (6 papers) and Genomics and Phylogenetic Studies (5 papers). Jiu-Xin Tan collaborates with scholars based in China and Russia. Jiu-Xin Tan's co-authors include Zimei Zhang, Wei Chen, Hao Lin, Hao Lv, Fanny Dao, Fang Wang, Cuixia Chen, Hua Tang, Hui Ding and Zhao‐Yue Zhang and has published in prestigious journals such as Molecules, Genomics and Briefings in Bioinformatics.

In The Last Decade

Jiu-Xin Tan

8 papers receiving 495 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jiu-Xin Tan China	7	452	70	45	24	24	8	502
Hasan Zulfiqar China	15	677 1.5×	93 1.3×	98 2.2×	15 0.6×	53 2.2×	27	815
Zimei Zhang China	10	473 1.0×	113 1.6×	63 1.4×	8 0.3×	25 1.0×	26	621
Zhijun Liao China	12	449 1.0×	121 1.7×	48 1.1×	6 0.3×	44 1.8×	35	556
Shi-Shi Yuan China	9	260 0.6×	33 0.5×	34 0.8×	7 0.3×	22 0.9×	10	317
Juan Felipe Beltrán United States	8	230 0.5×	31 0.4×	29 0.6×	17 0.7×	30 1.3×	13	383
Dongxu Xiang Australia	8	531 1.2×	60 0.9×	44 1.0×	10 0.4×	35 1.5×	8	646
Ya-Wei Zhao China	7	621 1.4×	123 1.8×	70 1.6×	18 0.8×	16 0.7×	8	667
Rouh‐Mei Hu Taiwan	12	200 0.4×	48 0.7×	7 0.2×	68 2.8×	24 1.0×	23	369
Qinhu Zhang China	11	488 1.1×	74 1.1×	26 0.6×	8 0.3×	39 1.6×	42	582
Youngjun Park South Korea	8	171 0.4×	61 0.9×	34 0.8×	7 0.3×	16 0.7×	14	265

Countries citing papers authored by Jiu-Xin Tan

Since Specialization

Citations

This map shows the geographic impact of Jiu-Xin Tan'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 Jiu-Xin Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiu-Xin Tan more than expected).

Fields of papers citing papers by Jiu-Xin Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jiu-Xin Tan. 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 Jiu-Xin Tan. The network helps show where Jiu-Xin Tan may publish in the future.

Co-authorship network of co-authors of Jiu-Xin Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Jiu-Xin Tan. A scholar is included among the top collaborators of Jiu-Xin Tan 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 Jiu-Xin Tan. Jiu-Xin Tan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Zhang, Zimei, Jiu-Xin Tan, Fang Wang, et al.. (2020). Early Diagnosis of Hepatocellular Carcinoma Using Machine Learning Method. Frontiers in Bioengineering and Biotechnology. 8. 254–254. 82 indexed citations

2.

Su, Wei, Fang Wang, Jiu-Xin Tan, et al.. (2020). The prediction of human DNase I hypersensitive sites based on DNA sequence information. Chemometrics and Intelligent Laboratory Systems. 209. 104223–104223. 6 indexed citations

3.

Lv, Hao, Fanny Dao, Zheng-Xing Guan, et al.. (2019). iDNA6mA-Rice: A Computational Tool for Detecting N6-Methyladenine Sites in Rice. Frontiers in Genetics. 10. 793–793. 61 indexed citations

4.

Tan, Jiu-Xin, Zimei Zhang, Cuixia Chen, et al.. (2019). Identification of hormone binding proteins based on machine learning methods. Mathematical Biosciences & Engineering. 16(4). 2466–2480. 128 indexed citations

5.

Lv, Hao, et al.. (2019). Evaluation of different computational methods on 5-methylcytosine sites identification. Briefings in Bioinformatics. 21(3). 982–995. 136 indexed citations

6.

Liu, Guoqing, Guoqing Liu, Guojun Liu, et al.. (2018). DNA physical properties outperform sequence compositional information in classifying nucleosome-enriched and -depleted regions. Genomics. 111(5). 1167–1175. 12 indexed citations

7.

Tan, Jiu-Xin, Hao Lv, Fang Wang, et al.. (2018). A Survey for Predicting Enzyme Family Classes Using Machine Learning Methods. Current Drug Targets. 20(5). 540–550. 36 indexed citations

8.

Tan, Jiu-Xin, Fanny Dao, Hao Lv, Pengmian Feng, & Hui Ding. (2018). Identifying Phage Virion Proteins by Using Two-Step Feature Selection Methods. Molecules. 23(8). 2000–2000. 41 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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