Jennifer Lin

99 papers receiving 3.5k citations

Jennifer Lin's Hit Papers

How open science helps researchers succeed 2016 · 476 citations
4760+3+6Years since publication100200300400

Peers

Jennifer Lin
Comparison fields: 5 of 175
  • Information Systems and Management 334
  • Statistics, Probability and Uncertainty 309
  • Cancer Research 375
  • Pathology and Forensic Medicine 314
  • Genetics 511
Replace Khusru Asadullah with:
Khusru Asadullah Germany
Muin J. Khoury United States
Martin Dugas Germany
Alawi Alsheikh‐Ali United Arab Emirates
Michael J. Becich United States
Mario Falchi United Kingdom
Jonathan Kimmelman Canada
L. Michelle Bennett United States
Azhar Hussain Pakistan
Carol Friedman United States
Jennifer Lin relative to Khusru Asadullah Germany Khusru Asadullah's profile →
Citations per field
00.5×2.6×
Khusru Asadullah · 1×
Citations per year

Countries citing papers authored by Jennifer Lin

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jennifer Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jennifer Lin Line = papers co-authored together Jennifer Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 107 papers — load more, or switch the sort, to bring in the rest.

#Work
1
How open science helps researchers succeed
Hit paper breakdown →
2016476
2 2002303
3 2007139
4 2012132
5 2000131
6 2000124
7 2016123
8 2010118
9 2008101
10 202098
11 201296
12 200587
13 200487
14 201584
15 200682
16 202081
17 201281
18 201378
19 200777
20 201576

About Jennifer Lin

Jennifer Lin is a scholar working on Genetics, Surgery, Molecular Biology, Oncology and Cancer Research, having authored 107 papers that have together received 3.7k indexed citations. Recurring topics across this work include Cancer, Lipids, and Metabolism (10 papers), Research Data Management Practices (9 papers), Scientific Computing and Data Management (8 papers), Anesthesia and Pain Management (8 papers), Genetic Associations and Epidemiology (7 papers), scientometrics and bibliometrics research (6 papers), Nutritional Studies and Diet (5 papers) and Acute Ischemic Stroke Management (5 papers). The work is most often cited by research in Information Systems and Management (334 citations), Statistics, Probability and Uncertainty (309 citations), Cancer Research (375 citations), Pathology and Forensic Medicine (314 citations) and Genetics (511 citations). Jennifer Lin has collaborated with scholars based in United States, United Kingdom and Vietnam. Frequent co-authors include Shumin M. Zhang, JoAnn E. Manson, Julie E. Buring, Brian K. Suarez, I‐Min Lee, Robert Culverhouse, Theodore Reich, Nancy R. Cook, Bryan R. Cullen and Edward L. Giovannucci. Their work appears in journals such as Cancer Research, Genetic Epidemiology, American Journal of Clinical Nutrition, Journal of Virology and Stroke.

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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