Xin Cong

94 total papers · 1.3k total citations
38 papers, 841 citations indexed

About

Xin Cong is a scholar working on Artificial Intelligence, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Xin Cong has authored 38 papers receiving a total of 841 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Molecular Biology and 6 papers in Infectious Diseases. Recurrent topics in Xin Cong's work include Viral gastroenteritis research and epidemiology (6 papers), Herpesvirus Infections and Treatments (5 papers) and Animal Disease Management and Epidemiology (4 papers). Xin Cong is often cited by papers focused on Viral gastroenteritis research and epidemiology (6 papers), Herpesvirus Infections and Treatments (5 papers) and Animal Disease Management and Epidemiology (4 papers). Xin Cong collaborates with scholars based in China, United States and United Kingdom. Xin Cong's co-authors include Yuan Sun, Yuzi Luo, Yongfeng Li, Jin Yuan, Hua-Ji Qiu, Chunhua Wang, Li Su, Yimin Wang, Jianlin Lei and Na Li and has published in prestigious journals such as PLoS ONE, Cancer Research and Journal of Virology.

In The Last Decade

Xin Cong

35 papers receiving 834 citations

Hit Papers

normalize citations (0→100%) normalize lifespan (0→100%) sort by overperformance

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Xin Cong	321	162	144	143	135	38	841
Pei‐Yu Lee	108 0.3×	91 0.6×	54 0.4×	131 0.9×	72 0.5×	54	959
Sen Hu	330 1.0×	132 0.8×	14 0.1×	104 0.7×	82 0.6×	33	737
Dan Heller	110 0.3×	62 0.4×	34 0.2×	265 1.9×	162 1.2×	32	758
Hoang Vu Dang	83 0.3×	142 0.9×	88 0.6×	42 0.3×	118 0.9×	55	774
Richard Howey	94 0.3×	301 1.9×	122 0.8×	39 0.3×	133 1.0×	28	974
Kevin W. Bock	248 0.8×	18 0.1×	37 0.3×	54 0.4×	319 2.4×	36	1.0k
Tiago Luís	77 0.2×	115 0.7×	16 0.1×	136 1.0×	50 0.4×	32	734
Yang Song	238 0.7×	160 1.0×	405 2.8×	49 0.3×	159 1.2×	62	770
Diane S. Leland	413 1.3×	17 0.1×	45 0.3×	43 0.3×	311 2.3×	21	1.0k
Fang Yuan	447 1.4×	81 0.5×	12 0.1×	30 0.2×	107 0.8×	46	1.0k

Countries citing papers authored by Xin Cong

Since Specialization

Citations

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

Fields of papers citing papers by Xin Cong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xin Cong

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

All Works

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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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