Jaclyn Smith

42 total papers · 9.3k total citations
6 papers, 33 citations indexed

About

Jaclyn Smith is a scholar working on Molecular Biology, Cancer Research and Computer Networks and Communications. According to data from OpenAlex, Jaclyn Smith has authored 6 papers receiving a total of 33 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Cancer Research and 2 papers in Computer Networks and Communications. Recurrent topics in Jaclyn Smith's work include Cancer Genomics and Diagnostics (3 papers), Gene expression and cancer classification (3 papers) and Algorithms and Data Compression (2 papers). Jaclyn Smith is often cited by papers focused on Cancer Genomics and Diagnostics (3 papers), Gene expression and cancer classification (3 papers) and Algorithms and Data Compression (2 papers). Jaclyn Smith collaborates with scholars based in United Kingdom, United States and Switzerland. Jaclyn Smith's co-authors include Amir Shaikhha, Dan Olteanu, Michael Benedikt, Jake Lin, Takahiro Tsujikawa, Joe W. Gray, Guillaume Thibault, Brian L. Hill, Christopher L. Corless and Yao Shi and has published in prestigious journals such as PLoS ONE, GigaScience and Proceedings of the ACM on Programming Languages.

In The Last Decade

Jaclyn Smith

6 papers receiving 32 citations

Author Peers

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

Author Last Decade Papers Cites
Jaclyn Smith 16 9 8 7 7 6 33
Frédéric Haziza 15 0.9× 11 1.2× 3 0.4× 8 1.1× 5 0.7× 7 33
Alex Ozdemir 27 1.7× 10 1.1× 8 1.0× 4 0.6× 8 41
Minta Thomas 15 0.9× 8 0.9× 1 0.1× 7 1.0× 4 0.6× 8 51
Gianluca Mittone 16 1.0× 12 1.3× 7 0.9× 3 0.4× 7 38
Leonard Dervishi 16 1.0× 15 1.7× 5 0.7× 5 0.7× 6 37
Axel Legay 20 1.3× 11 1.2× 14 1.8× 3 0.4× 7 50
Yann Thierry-Mieg 14 0.9× 11 1.2× 5 0.6× 3 0.4× 6 47
Noomene Ben Henda 19 1.2× 10 1.1× 3 0.4× 4 0.6× 7 45
Antonio Arbona 13 0.8× 13 1.4× 2 0.3× 9 1.3× 5 51
Aohan Zeng 46 2.9× 5 0.6× 3 0.4× 14 2.0× 6 71

Countries citing papers authored by Jaclyn Smith

Since Specialization
Citations

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

Fields of papers citing papers by Jaclyn Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaclyn Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Jaclyn Smith. A scholar is included among the top collaborators of Jaclyn Smith 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 Jaclyn Smith. Jaclyn Smith 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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