Daniel G. Chain

1.5k citations
20 papers · 1.3k · h-index 13

Impact in

Papers in

Daniel G. Chain

19 papers receiving 1.3k citations

Peers

Daniel G. Chain
Comparison fields: 5 of 99
  • Biological Psychiatry 96
  • Cellular and Molecular Neuroscience 361
  • Immunology and Allergy 77
  • Cell Biology 202
  • Molecular Biology 695
Replace Mohammed A. Kashem with:
Mohammed A. Kashem United States
Ritchie Williamson United Kingdom
Nobuaki Okumura Japan
Marialaura Amadio Italy
Ryo Tanaka Japan
Ryan S. Westphal United States
Hyung Wook Nam United States
Daniel B. McClatchy United States
Shinji Tagami Japan
Christiane Volbracht Denmark
Daniel G. Chain relative to Mohammed A. Kashem United States Mohammed A. Kashem's profile →
Citations per field
00.5×1.7×
Mohammed A. Kashem · 1×
Citations per year

Countries citing papers authored by Daniel G. Chain

Since Specialization
Citations

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

Fields of papers citing papers by Daniel G. Chain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 1999346
2 1997321
3 1999159
4 2002144
5 199956
6 199950
7 199149
8 198847
9 198334
10 199030
11 199130
12 199018
13 198612
14 20229
15 19888
16 19927
17 20142
18 20231
19 20231
20 20240

About Daniel G. Chain

Daniel G. Chain is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Physiology, Pulmonary and Respiratory Medicine and Cell Biology, having authored 20 papers that have together received 1.3k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (5 papers), Ubiquitin and proteasome pathways (4 papers), Protease and Inhibitor Mechanisms (4 papers), Blood properties and coagulation (4 papers), Neuroscience and Neuropharmacology Research (3 papers), Neuropeptides and Animal Physiology (3 papers), Genetics and Neurodevelopmental Disorders (2 papers) and Amino Acid Enzymes and Metabolism (2 papers). The work is most often cited by research in Biological Psychiatry (96 citations), Cellular and Molecular Neuroscience (361 citations), Immunology and Allergy (77 citations), Cell Biology (202 citations) and Molecular Biology (695 citations). Daniel G. Chain has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Ashok N. Hegde, James H. Schwartz, Burkhard Pöeggeler, Miguel A. Pappolla, Eric R. Kandel, Andrea Casadio, Blas Frangione, Rawhi Omar, Jorge Ghiso and Shmuel Shaltiel. Their work appears in journals such as Alzheimer s & Dementia, FEBS Letters, Analytical Biochemistry, Biochemical and Biophysical Research Communications and Molecular Neurobiology.

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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