Brian Y. Soong

650 total citations
3 papers, 36 citations indexed

About

Brian Y. Soong is a scholar working on Infectious Diseases, Molecular Biology and Neurology. According to data from OpenAlex, Brian Y. Soong has authored 3 papers receiving a total of 36 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Infectious Diseases, 1 paper in Molecular Biology and 1 paper in Neurology. Recurrent topics in Brian Y. Soong's work include COVID-19 epidemiological studies (1 paper), Single-cell and spatial transcriptomics (1 paper) and CRISPR and Genetic Engineering (1 paper). Brian Y. Soong is often cited by papers focused on COVID-19 epidemiological studies (1 paper), Single-cell and spatial transcriptomics (1 paper) and CRISPR and Genetic Engineering (1 paper). Brian Y. Soong collaborates with scholars based in United States. Brian Y. Soong's co-authors include Rebecca J. Carlson, Paul C. Blainey, David Feldman, Avtar Singh, Daisy W. Leung, Alexandra S. Reynolds, Alexander W. Charney, Adityanarayanan Radhakrishnan, Pushkala Jayaraman and Caroline Uhler and has published in prestigious journals such as Nature Protocols, Nature Microbiology and npj Digital Medicine.

In The Last Decade

Brian Y. Soong

3 papers receiving 36 citations

Peers

Brian Y. Soong
Clarence K. Mah United States
Pankti Shah United States
A Grossman United States
Alex Alderton United Kingdom
Rong Pan China
Fangting Zuo China
William R. Orchard United Kingdom
Gemechu Mekonnen United States
Julian Hennies Germany
Raphael Kfuri‐Rubens Germany
Clarence K. Mah United States
Brian Y. Soong
Citations per year, relative to Brian Y. Soong Brian Y. Soong (= 1×) peers Clarence K. Mah

Countries citing papers authored by Brian Y. Soong

Since Specialization
Citations

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

Fields of papers citing papers by Brian Y. Soong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian Y. Soong. 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 Brian Y. Soong. The network helps show where Brian Y. Soong may publish in the future.

Co-authorship network of co-authors of Brian Y. Soong

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

All Works

3 of 3 papers shown
1.
Carlson, Rebecca J., J. J. Patten, Brian Y. Soong, et al.. (2025). Single-cell image-based screens identify host regulators of Ebola virus infection dynamics. Nature Microbiology. 10(8). 1989–2002. 3 indexed citations
2.
Jayaraman, Pushkala, Brian Y. Soong, Alexandra S. Reynolds, et al.. (2024). Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension. npj Digital Medicine. 7(1). 233–233. 5 indexed citations
3.
Feldman, David, et al.. (2022). Pooled genetic perturbation screens with image-based phenotypes. Nature Protocols. 17(2). 476–512. 28 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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2026