Daniel Grandt

62 papers receiving 2.2k citations

Daniel Grandt's Hit Papers

The use of health information technology in seven nations 2008 · 275 citations
2750+6+12Years since publication50100150200250

Peers

Daniel Grandt
Comparison fields: 5 of 117
  • Endocrine and Autonomic Systems 517
  • Cellular and Molecular Neuroscience 731
  • Hepatology 269
  • Health Information Management 149
  • Gastroenterology 105
Replace Akihiro Nomura with:
Akihiro Nomura Japan
Stephen O’Neill United Kingdom
Alan Flint United States
Lin Song China
Johannes Ruige Belgium
Atanu Biswas India
Paul Cooper United Kingdom
Harrison J.L. Frank United States
Donna L. Smith United States
Erin Green United States
Daniel Grandt relative to Akihiro Nomura Japan Akihiro Nomura's profile →
Citations per field
00.5×20×40×52.5×
Akihiro Nomura · 1×
Citations per year

Countries citing papers authored by Daniel Grandt

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Grandt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994301
2 1993285
3
The use of health information technology in seven nations
Hit paper breakdown →
2008275
4 1995173
5 1989111
6 2004101
7 2004101
8 200471
9 199269
10 199759
11 199655
12 199454
13 200448
14 199245
15 200444
16 200839
17 199339
18 199031
19
[Proteolytic processing by dipeptidyl aminopeptidase IV generates receptor selectivity for peptide YY (PYY)].
199329
20 200427

About Daniel Grandt

Daniel Grandt is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Surgery, Oncology and Gastroenterology, having authored 64 papers that have together received 2.3k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (25 papers), Peptidase Inhibition and Analysis (12 papers), Gastrointestinal motility and disorders (6 papers), Liver Disease and Transplantation (6 papers), Receptor Mechanisms and Signaling (5 papers), Chemical Synthesis and Analysis (5 papers), Pharmaceutical Practices and Patient Outcomes (4 papers) and Hypothalamic control of reproductive hormones (4 papers). The work is most often cited by research in Endocrine and Autonomic Systems (517 citations), Cellular and Molecular Neuroscience (731 citations), Hepatology (269 citations), Health Information Management (149 citations) and Gastroenterology (105 citations). Daniel Grandt has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include H. Goebell, Peter Layer, Joseph R. Reeve, Winfried Häuser, Viktor E. Eysselein, M. Schimiczek, Peter Dahms, Rolf Mentlein, Ashish K. Jha and David W. Bates. Their work appears in journals such as Regulatory Peptides, Gastroenterology, Peptides, American Journal of Physiology-Gastrointestinal and Liver Physiology and Digestive Diseases and Sciences.

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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