Sheng Long

9 papers and 137 indexed citations i.

About

Sheng Long is a scholar working on Cancer Research, Genetics and Molecular Biology. According to data from OpenAlex, Sheng Long has authored 9 papers receiving a total of 137 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Cancer Research, 2 papers in Genetics and 1 paper in Molecular Biology. Recurrent topics in Sheng Long’s work include Genomics and Rare Diseases (2 papers), Cancer Genomics and Diagnostics (2 papers) and COVID-19 diagnosis using AI (1 paper). Sheng Long is often cited by papers focused on Genomics and Rare Diseases (2 papers), Cancer Genomics and Diagnostics (2 papers) and COVID-19 diagnosis using AI (1 paper). Sheng Long collaborates with scholars based in United States, United Kingdom and China. Sheng Long's co-authors include Randall J. Olsen, Rashi M. Thakur, Robert Olson, Paul Christensen, Jimmy Gollihar, Akanksha Batajoo, Madison Shyer, Guy Williams, Jessica Cambric and Matthew Ojeda Saavedra and has published in prestigious journals such as American Journal Of Pathology, American Journal of Clinical Pathology and Frontiers in Pharmacology.

In The Last Decade

Co-authorship network of co-authors of Sheng Long i

Fields of papers citing papers by Sheng Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Sheng Long

Since Specialization
Citations

This map shows the geographic impact of Sheng Long'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 Sheng Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheng Long 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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2025