LJ Lesko

1.4k citations
10 papers · 1.0k · 1 hit paper · h-index 9

Impact in

Papers in

LJ Lesko

10 papers receiving 997 citations

LJ Lesko's Hit Papers

Sobol Sensitivity Analysis: A Tool to Guide the Development and Evaluation of Systems Pharmacology Models 2015 · 326 citations
3260+3+7Years since publication100200300

Peers

LJ Lesko
Comparison fields: 5 of 157
  • Pharmacology 175
  • Statistics and Probability 105
  • Transplantation 20
  • Pediatrics, Perinatology and Child Health 119
  • Statistics, Probability and Uncertainty 49
Replace Amit Roy with:
Amit Roy United States
A R Henderson Canada
Jianrong Zhang China
Martin Schumacher Austria
Xiangyang Ye United States
Harry Burke United States
O Yoshida Japan
Yu Guan United States
Xianghui Chen China
James J. Zimmerman United States
LJ Lesko relative to Amit Roy United States Amit Roy's profile →
Citations per field
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Amit Roy · 1×
Citations per year

Countries citing papers authored by LJ Lesko

Since Specialization
Citations

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

Fields of papers citing papers by LJ Lesko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside LJ Lesko, 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 LJ Lesko Line = papers co-authored together LJ Lesko links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Sobol Sensitivity Analysis: A Tool to Guide the Development and Evaluation of Systems Pharmacology Models
Hit paper breakdown →
2015326
2 2001313
3 2008121
4 201384
5 201550
6 200849
7 201141
8 201615
9 201614
10 20166

About LJ Lesko

LJ Lesko is a scholar working on Pharmacology, Pediatrics, Perinatology and Child Health, Cardiology and Cardiovascular Medicine, Internal Medicine and Computational Theory and Mathematics, having authored 10 papers that have together received 1.0k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (6 papers), Pharmaceutical studies and practices (4 papers), Venous Thromboembolism Diagnosis and Management (2 papers), Statistical Methods in Clinical Trials (2 papers), Atrial Fibrillation Management and Outcomes (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Computational Drug Discovery Methods (2 papers) and Metabolism and Genetic Disorders (1 paper). The work is most often cited by research in Pharmacology (175 citations), Statistics and Probability (105 citations), Transplantation (20 citations), Pediatrics, Perinatology and Child Health (119 citations) and Statistics, Probability and Uncertainty (49 citations). LJ Lesko has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Atkinson Aj, Stephan Schmidt, Malcolm Rowland, Jeffrey S. Barrett, Peng Zhao, Amin Rostami‐Hodjegan, Janet Woodcock, D. R. Abernethy, JS Leeder and L Zhang. Their work appears in journals such as Clinical Pharmacology & Therapeutics, CPT Pharmacometrics & Systems Pharmacology and The Annual Review of Pharmacology and Toxicology.

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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