Chris de Graaf

138 papers receiving 6.5k citations

Hit Papers

Impact of GPCR Structures on Drug Discovery 2020 · 245 citations
245201620262019202250100150200250

Peers

Chris de Graaf
Comparison fields: 5 of 133
  • Computational Theory and Mathematics 1.8k
  • Cellular and Molecular Neuroscience 1.8k
  • Molecular Biology 5.0k
  • Pharmacology 511
  • Radiology, Nuclear Medicine and Imaging 881
Replace David E. Gloriam with:
David E. Gloriam Denmark
Didier Rognan France
Miles Congreve United Kingdom
Maurizio Pellecchia United States
Jonathan D. Violin United States
Irina Kufareva United States
A.C.W. Pike United Kingdom
Peter Gmeiner Germany
Gye Won Han United States
Aashish Manglik United States
Chris de Graaf relative to David E. Gloriam Denmark David E. Gloriam's profile →
Citations per field
00.5×1.6×
David E. Gloriam · 1×
Citations per year

Countries citing papers authored by Chris de Graaf

Since Specialization
Citations

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

Fields of papers citing papers by Chris de Graaf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chris de Graaf. 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 Chris de Graaf. The network helps show where Chris de Graaf may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20250
3 20248
4 202414
5 20233
6 202013
7 201995
8 201851
9 201843
10 201811
11 201863
12 201760
13
Glucagon-Like Peptide-1 and Its Class B G Protein–Coupled Receptors: A Long March to Therapeutic Successes
Hit paper breakdown →
2016288
14 2011162
15
: The Pitfalls and Challenges of Predicting GPCR-Ligand Interactions.
20111
16 201112
17 201124
18 200715
19 20052
20 19851

About Chris de Graaf

Chris de Graaf is a scholar working on Computational Theory and Mathematics, Cellular and Molecular Neuroscience, Pharmacology, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 139 papers that have together received 6.7k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (78 papers), Computational Drug Discovery Methods (48 papers), Neuropeptides and Animal Physiology (35 papers), Chemical Synthesis and Analysis (30 papers), Monoclonal and Polyclonal Antibodies Research (24 papers), Chemokine receptors and signaling (17 papers), Pharmacogenetics and Drug Metabolism (16 papers) and Analytical Chemistry and Chromatography (14 papers). The work is most often cited by research in Computational Theory and Mathematics (1.8k citations), Cellular and Molecular Neuroscience (1.8k citations), Molecular Biology (5.0k citations), Pharmacology (511 citations) and Radiology, Nuclear Medicine and Imaging (881 citations). Chris de Graaf has collaborated with scholars based in Netherlands, United Kingdom and United States. Frequent co-authors include Iwan J. P. de Esch, Rob Leurs, Albert J. Kooistra, Raymond C. Stevens, Nico Vermeulen, Didier Rognan, Miles Congreve, Henry F. Vischer, Luc Roumen and Vsevolod Katritch. Their work appears in journals such as Journal of Medicinal Chemistry, Journal of Chemical Information and Modeling, Molecular Pharmacology, Nature Communications and British Journal of Pharmacology.

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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