Daniel T. Babcock

892 citations
20 papers · 637 indexed · h-index 10
Topics
Neurobiology and Insect Physiology Research (12 papers)Invertebrate Immune Response Mechanisms (5 papers)Neuroscience and Neuropharmacology Research (2 papers)
Partner nations
United StatesFrance

In The Last Decade

Daniel T. Babcock

19 papers receiving 628 citations

Peers

Daniel T. Babcock
Comparison fields: 5 of 68
  • Cellular and Molecular Neuroscience 414
  • Molecular Biology 199
  • Insect Science 176
  • Immunology 159
  • Physiology 86
Replace Pei-Tseng Lee with:
Pei-Tseng Lee United States
Shin’Ichiro Satake Japan
Zhengmei Mao United States
Graham Huesmann United States
Maria L. Spletter Germany
Stefanie Schirmeier Germany
Shouzhen Xia United States
Hiroshi Ishimoto Japan
Christos Consoulas Greece
Paola Cognigni United Kingdom
Daniel T. Babcock relative to Pei-Tseng Lee United States Pei-Tseng Lee's profile →
Citations per field
00.5×1.7×
Pei-Tseng Lee · 1×
Citations per year

Countries citing papers authored by Daniel T. Babcock

Since Specialization
Citations

This map shows the geographic impact of Daniel T. Babcock'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 T. Babcock with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Babcock more than expected).

Fields of papers citing papers by Daniel T. Babcock

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel T. Babcock

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel T. Babcock. A scholar is included among the top collaborators of Daniel T. Babcock based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel T. Babcock. Daniel T. Babcock is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 2
4 2
5 6
6 7
7 6
8 13
9 19
10 7
11 98
12 54
13 17
14 36
15 1
16 89
17 7
18 119
19 141
20 12

About Daniel T. Babcock

Daniel T. Babcock is a scholar working on Aging, Cellular and Molecular Neuroscience and Sensory Systems, having authored 20 papers that have together received 637 indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (12 papers), Invertebrate Immune Response Mechanisms (5 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Aging (40 citations), Cellular and Molecular Neuroscience (414 citations) and Insect Science (176 citations). Daniel T. Babcock has collaborated with scholars based in United States and France. Frequent co-authors include Michael J. Galko, Barry Ganetzky, Christian R. Landry, Ju-Yeon Jo, Mark A. Krasnow, Yan Wang, Laurent Perrin, Howard B. Gutstein, Michael H. Shaw and Shanping Shi. Their work appears in journals such as Proceedings of the National Academy of Sciences, Current Biology and Genetics.

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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