Nina Lane

19 total papers · 409 total citations
10 papers, 354 citations indexed

About

Nina Lane is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Biochemistry. According to data from OpenAlex, Nina Lane has authored 10 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Pathology and Forensic Medicine and 4 papers in Biochemistry. Recurrent topics in Nina Lane's work include Heme Oxygenase-1 and Carbon Monoxide (6 papers), Alcohol Consumption and Health Effects (5 papers) and Cannabis and Cannabinoid Research (3 papers). Nina Lane is often cited by papers focused on Heme Oxygenase-1 and Carbon Monoxide (6 papers), Alcohol Consumption and Health Effects (5 papers) and Cannabis and Cannabinoid Research (3 papers). Nina Lane collaborates with scholars based in Canada, United States and United Kingdom. Nina Lane's co-authors include Joseph Fomusi Ndisang, Ashok Jadhav, Lucy C. Fairclough, Jonathan Corne, R. A. Robins, Rajni Chibbar, Dayan B. Goodenowe, Tara Smith, Paul L. Wood and Darryl Jackson and has published in prestigious journals such as Circulation, Endocrinology and American Journal of Physiology-Endocrinology and Metabolism.

In The Last Decade

Nina Lane

10 papers receiving 345 citations

Author Peers

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

Author Last Decade Papers Cites
Nina Lane 223 102 58 48 45 10 354
Rossana Ballerio 154 0.7× 79 0.8× 51 0.9× 45 0.9× 36 0.8× 10 375
Cosimo Marzocca 214 1.0× 81 0.8× 72 1.2× 61 1.3× 56 1.2× 14 403
X. Chen 88 0.4× 101 1.0× 37 0.6× 25 0.5× 42 0.9× 6 328
Trinidad Parra 89 0.4× 82 0.8× 26 0.4× 20 0.4× 23 0.5× 10 391
Yuichi Shinoda 117 0.5× 96 0.9× 27 0.5× 17 0.4× 27 0.6× 13 367
Paula Urquhart 173 0.8× 45 0.4× 20 0.3× 97 2.0× 78 1.7× 11 380
Boris Betz 119 0.5× 48 0.5× 26 0.4× 33 0.7× 28 0.6× 14 398
Georg Berndt 247 1.1× 38 0.4× 60 1.0× 52 1.1× 61 1.4× 7 387
Inae Jang 146 0.7× 86 0.8× 23 0.4× 21 0.4× 13 0.3× 9 394
Jun Zhang 104 0.5× 44 0.4× 36 0.6× 20 0.4× 109 2.4× 15 311

Countries citing papers authored by Nina Lane

Since Specialization
Citations

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

Fields of papers citing papers by Nina Lane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Lane

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