Harvey Motulsky

11.8k citations
85 papers · 9.3k indexed · 4 hit papers · h-index 37

Harvey Motulsky

82 papers receiving 8.9k citations

Hit Papers

Detecting outliers when fitting data with no...1.1k198720262000201350010001.5k

Peers

Harvey Motulsky
Comparison fields: 5 of 216
  • Cellular and Molecular Neuroscience 2.0k
  • Behavioral Neuroscience 291
  • Biological Psychiatry 146
  • Molecular Biology 3.7k
  • Physiology 212
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Citations per field
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Citations per year

Countries citing papers authored by Harvey Motulsky

Since Specialization
Citations

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

Fields of papers citing papers by Harvey Motulsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 202212
3 201911
4 201974
5 201443
6
Detecting outliers when fitting data with nonlinear regression – a new method based on robust nonlinear regression and the false discovery ratebreakdown →
20061133
7
Fitting models to biological data using linear and nonlinear regression : a practical guide to curve fittingbreakdown →
20041620
8
Fitting Models to Biological Data Using Linear and Nonlinear Regressionbreakdown →
20041118
9 19912
10 1990124
11 19893
12 1989101
13 1989234
14 198831
15 19889
16
Compartmentation of alpha 2-adrenergic receptors in human erythroleukemia (HEL) cells.
198721
17
Alpha/sub 2/-adrenergic receptors on a platelet precursor cell line, HEL
19861
18 19769
19 197410
20 19739

About Harvey Motulsky

Harvey Motulsky is a scholar working on Cellular and Molecular Neuroscience, Animal Science and Zoology and Statistics and Probability, having authored 85 papers that have together received 9.3k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (49 papers), Neuropeptides and Animal Physiology (23 papers), Pharmacological Effects and Assays (15 papers), Cancer, Stress, Anesthesia, and Immune Response (9 papers), Ion channel regulation and function (8 papers), Neuroscience and Neuropharmacology Research (6 papers), Meta-analysis and systematic reviews (6 papers) and Statistical Methods in Clinical Trials (5 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (2.0k citations), Behavioral Neuroscience (291 citations) and Biological Psychiatry (146 citations). Harvey Motulsky has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Arthur Christopoulos, Paul A. Insel, Lennart A. Ransnäs, Ronald E. Brown, L C Mahan, Martin C. Michel, Alan S. Maisel, Antonio DeBlasi, Kevin O’Reilly and Michael G. Ziegler. Their work appears in journals such as Molecular Pharmacology, Circulation Research, Trends in Pharmacological Sciences, Journal of Cardiovascular Pharmacology and Journal of Biological Chemistry.

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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