Laszlo Hackler

65 papers receiving 3.2k citations

Laszlo Hackler's Hit Papers

A potent and selective endogenous agonist for the µ-opiate receptor 1997 · 1.2k citations
1.2k0+9+19Years since publication2505007501000

Peers

Laszlo Hackler
Comparison fields: 5 of 137
  • Cellular and Molecular Neuroscience 1.8k
  • Physiology 915
  • Nutrition and Dietetics 507
  • Endocrine and Autonomic Systems 214
  • Food Science 531
Replace H. Teschemacher with:
H. Teschemacher Germany
Kousaku Ohinata Japan
Tohru Fushiki Japan
Donatus Nöhr Germany
Flavia Mulè Italy
Hisayuki Uneyama Japan
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Lina Wang China
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Citations per year

Countries citing papers authored by Laszlo Hackler

Since Specialization
Citations

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

Fields of papers citing papers by Laszlo Hackler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A potent and selective endogenous agonist for the µ-opiate receptor
Hit paper breakdown →
19971152
2 1997166
3 1983150
4 1980149
5 1981120
6 1999118
7 198096
8 197779
9 201577
10 198369
11 199767
12 196565
13 196258
14 199754
15 199851
16 199451
17 200047
18 198446
19 199336
20 200136

About Laszlo Hackler

Laszlo Hackler is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Plant Science, Food Science and Physiology, having authored 67 papers that have together received 3.4k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (16 papers), Receptor Mechanisms and Signaling (10 papers), Macrophage Migration Inhibitory Factor (8 papers), Phytase and its Applications (8 papers), Pain Mechanisms and Treatments (7 papers), Food composition and properties (7 papers), Proteins in Food Systems (7 papers) and Chemical Synthesis and Analysis (6 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.8k citations), Physiology (915 citations), Nutrition and Dietetics (507 citations), Endocrine and Autonomic Systems (214 citations) and Food Science (531 citations). Laszlo Hackler has collaborated with scholars based in United States, Canada and India. Frequent co-authors include James E. Zadina, Lin-Jun Ge, Abba J. Kastin, Abba J. Kastin, K. H. Steinkraus, Abba J. Kastin, Mahmood Hasan Khan, Jerry M. Rivers, Victoria Akerstrom and P.J. Van Soest. Their work appears in journals such as Journal of Food Science, Journal of Nutrition, Journal of Agricultural and Food Chemistry, Peptides and American Journal of Enology and Viticulture.

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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