Kujin Tang

633 total citations
8 papers, 339 citations indexed

About

Kujin Tang is a scholar working on Molecular Biology, Ecology and Artificial Intelligence. According to data from OpenAlex, Kujin Tang has authored 8 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Ecology and 2 papers in Artificial Intelligence. Recurrent topics in Kujin Tang's work include Genomics and Phylogenetic Studies (7 papers), Machine Learning in Bioinformatics (4 papers) and RNA and protein synthesis mechanisms (3 papers). Kujin Tang is often cited by papers focused on Genomics and Phylogenetic Studies (7 papers), Machine Learning in Bioinformatics (4 papers) and RNA and protein synthesis mechanisms (3 papers). Kujin Tang collaborates with scholars based in United States, China and France. Kujin Tang's co-authors include Fengzhu Sun, Jie Ren, Jed A. Fuhrman, Yang Young Lu, Michael S. Waterman, Xin Bai, J. Cesar Ignacio‐Espinoza, Jonathan Braun, Weili Wang and Nathan A. Ahlgren and has published in prestigious journals such as Nucleic Acids Research, Genome biology and Frontiers in Microbiology.

In The Last Decade

Kujin Tang

8 papers receiving 337 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kujin Tang United States	6	281	117	72	51	29	8	339
Binghang Liu China	5	305 1.1×	101 0.9×	64 0.9×	69 1.4×	17 0.6×	9	380
Hani Z. Girgis United States	11	364 1.3×	58 0.5×	143 2.0×	73 1.4×	44 1.5×	18	458
Oren Avram Israel	9	174 0.6×	54 0.5×	80 1.1×	47 0.9×	11 0.4×	21	288
Guillaume Holley Iceland	8	214 0.8×	31 0.3×	44 0.6×	59 1.2×	59 2.0×	12	266
Vitor C. Piro Germany	8	179 0.6×	84 0.7×	25 0.3×	12 0.2×	23 0.8×	13	218
Lyam Baudry France	8	215 0.8×	91 0.8×	96 1.3×	39 0.8×	4 0.1×	9	284
Hanno Teeling Germany	3	303 1.1×	233 2.0×	45 0.6×	12 0.2×	11 0.4×	3	357
Krister M. Swenson Canada	10	239 0.9×	30 0.3×	107 1.5×	173 3.4×	51 1.8×	35	301
Chris-André Leimeister Germany	9	425 1.5×	49 0.4×	82 1.1×	85 1.7×	138 4.8×	11	455
Alaleh Azhir United States	5	245 0.9×	17 0.1×	89 1.2×	56 1.1×	12 0.4×	15	350

Countries citing papers authored by Kujin Tang

Since Specialization

Citations

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

Fields of papers citing papers by Kujin Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kujin Tang. 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 Kujin Tang. The network helps show where Kujin Tang may publish in the future.

Co-authorship network of co-authors of Kujin Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Kujin Tang. A scholar is included among the top collaborators of Kujin Tang 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 Kujin Tang. Kujin Tang 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:

8 of 8 papers shown

1.

Wang, Weili, Jie Ren, Kujin Tang, et al.. (2020). A network-based integrated framework for predicting virus–prokaryote interactions. NAR Genomics and Bioinformatics. 2(2). lqaa044–lqaa044. 84 indexed citations

2.

Tang, Kujin, Jie Ren, & Fengzhu Sun. (2019). Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression. Genome biology. 20(1). 266–266. 17 indexed citations

3.

Zieleziński, Andrzej, Hani Z. Girgis, Guillaume Bernard, et al.. (2019). Benchmarking of alignment-free sequence comparison methods. Genome biology. 20(1). 144–144. 123 indexed citations

4.

Tang, Kujin, Jie Ren, Richard Cronn, et al.. (2018). Alignment-free genome comparison enables accurate geographic sourcing of white oak DNA. BMC Genomics. 19(1). 896–896. 5 indexed citations

5.

Tang, Kujin, Yang Young Lu, & Fengzhu Sun. (2018). Background Adjusted Alignment-Free Dissimilarity Measures Improve the Detection of Horizontal Gene Transfer. Frontiers in Microbiology. 9. 711–711. 5 indexed citations

6.

Ren, Jie, Xin Bai, Yang Young Lu, et al.. (2018). Alignment-Free Sequence Analysis and Applications. PubMed. 1(1). 93–114. 56 indexed citations

7.

Bai, Xin, Kujin Tang, Jie Ren, Michael S. Waterman, & Fengzhu Sun. (2017). Optimal choice of word length when comparing two Markov sequences using a χ 2-statistic. BMC Genomics. 18(S6). 732–732. 5 indexed citations

8.

Lu, Yang Young, Kujin Tang, Jie Ren, et al.. (2017). CAFE: aCcelerated Alignment-FrEe sequence analysis. Nucleic Acids Research. 45(W1). W554–W559. 44 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.

Explore authors with similar magnitude of impact