Lynn Connolly

5.0k citations
38 papers · 3.6k indexed · 1 hit paper · h-index 21

Lynn Connolly

36 papers receiving 3.5k citations

Hit Papers

Aminoglycosides: An Overview7142016202620192022200400600

Peers

Lynn Connolly
Comparison fields: 5 of 145
  • Molecular Medicine 880
  • Endocrinology 488
  • Applied Microbiology and Biotechnology 141
  • Infectious Diseases 882
  • Genetics 951
Replace Abigail L. Manson with:
Abigail L. Manson United States
Teruo Kirikae Japan
Teruo Kirikae Japan
G Satta Italy
Samuel M. Moskowitz United States
Shin‐ichi Yokota Japan
Timothy Palzkill United States
Mark W. Eshoo United States
P.J. Stogios Canada
Gee W. Lau United States
Lynn Connolly relative to Abigail L. Manson United States Abigail L. Manson's profile →
Citations per field
00.5×2.9×
Abigail L. Manson · 1×
Citations per year

Countries citing papers authored by Lynn Connolly

Since Specialization
Citations

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

Fields of papers citing papers by Lynn Connolly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Lynn Connolly, 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 Lynn Connolly Line = papers co-authored together Lynn Connolly links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20237
2 20211
3 20212
4 2019148
5 20182
6 201739
7 201726
8
Aminoglycosides: An Overviewbreakdown →
2016714
9 201597
10 201440
11 201114
12 2011398
13 2009392
14 20096
15 2007161
16 2006244
17 1999207
18 1997283
19 199785
20 1988154

About Lynn Connolly

Lynn Connolly is a scholar working on Molecular Medicine, Infectious Diseases and Epidemiology, having authored 38 papers that have together received 3.6k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (14 papers), Tuberculosis Research and Epidemiology (8 papers), Antibiotics Pharmacokinetics and Efficacy (8 papers), Mycobacterium research and diagnosis (7 papers), Urinary Tract Infections Management (5 papers), Bacterial Genetics and Biotechnology (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Regulation of Appetite and Obesity (3 papers). The work is most often cited by research in Molecular Medicine (880 citations), Endocrinology (488 citations) and Applied Microbiology and Biotechnology (141 citations). Lynn Connolly has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Carol A. Gross, Kevin M. Krause, Alejandro De Las Peñas, Alisa W. Serio, Timothy R. Kane, Jeffery S. Cox, Lalita Ramakrishnan, Holly Ramage, Paul H. Edelstein and Olivier Humbert. Their work appears in journals such as New England Journal of Medicine, Cell and Genes & Development.

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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