Ying Ju

About

Ying Ju is a scholar working on Molecular Biology, Cancer Research and Computational Theory and Mathematics. According to data from OpenAlex, Ying Ju has authored 33 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 5 papers in Cancer Research and 5 papers in Computational Theory and Mathematics. Recurrent topics in Ying Ju’s work include Machine Learning in Bioinformatics (21 papers), RNA and protein synthesis mechanisms (14 papers) and Genomics and Phylogenetic Studies (8 papers). Ying Ju is often cited by papers focused on Machine Learning in Bioinformatics (21 papers), RNA and protein synthesis mechanisms (14 papers) and Genomics and Phylogenetic Studies (8 papers). Ying Ju collaborates with scholars based in China and Japan. Ying Ju's co-authors include Quan Zou, Dehui Yin, Hua Tang, Yamei Luo, Ziyu Lin, Xiangxiang Zeng, Chenggang Song, Haoyu Zhang, Meihong Wu and Shixiang Wan and has published in prestigious journals such as Bioinformatics, PLoS ONE and Analytical Biochemistry.

In The Last Decade

Co-authorship network of co-authors of Ying Ju i

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Fields of papers citing papers by Ying Ju

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Ying Ju

Since Specialization

Citations

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

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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