Daniel T. Gray

1.2k citations
34 papers · 701 · h-index 15

Impact in

Papers in

Daniel T. Gray

32 papers receiving 688 citations

Peers

Daniel T. Gray
Comparison fields: 5 of 92
  • Dermatology 122
  • Neurology 111
  • Sensory Systems 63
  • Cognitive Neuroscience 246
  • Cellular and Molecular Neuroscience 153
Replace Tsutomu Oshima with:
Tsutomu Oshima Japan
Timothy E. O’Brien United States
I. Lorén Sweden
Alessia Antonelli Italy
Ramón Reñé Spain
Jiayu Fu China
Claudia Cinnante Italy
Igor Smirnov United States
Mark Gudesblatt United States
Dominic Thyagarajan Australia
Daniel T. Gray relative to Tsutomu Oshima Japan Tsutomu Oshima's profile →
Citations per field
00.5×6.8×
Tsutomu Oshima · 1×
Citations per year

Countries citing papers authored by Daniel T. Gray

Since Specialization
Citations

This map shows the geographic impact of Daniel T. Gray'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. Gray 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. Gray more than expected).

Fields of papers citing papers by Daniel T. Gray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997167
2 199586
3 201572
4 201539
5 201937
6 201634
7 202225
8 201424
9 201920
10 201320
11 201618
12 201317
13 201817
14 201816
15 201314
16
Examination of the early learning curve for transcatheter closure of patent ductus arteriosus using the rashkind occluder
199413
17 199713
18 202212
19 201811
20 20008

About Daniel T. Gray

Daniel T. Gray is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Neurology, Radiology, Nuclear Medicine and Imaging and Sensory Systems, having authored 34 papers that have together received 701 indexed citations. Recurring topics across this work include Neuroinflammation and Neurodegeneration Mechanisms (10 papers), Neuroscience and Neuropharmacology Research (10 papers), Memory and Neural Mechanisms (9 papers), Neural dynamics and brain function (7 papers), Hearing Loss and Rehabilitation (4 papers), Hearing, Cochlea, Tinnitus, Genetics (4 papers), Advanced Neuroimaging Techniques and Applications (3 papers) and Neuroscience and Music Perception (2 papers). The work is most often cited by research in Dermatology (122 citations), Neurology (111 citations), Sensory Systems (63 citations), Cognitive Neuroscience (246 citations) and Cellular and Molecular Neuroscience (153 citations). Daniel T. Gray has collaborated with scholars based in United States, Germany and Sweden. Frequent co-authors include Carol A. Barnes, James R. Engle, P. Lipa, Gregg H. Recanzone, C. A. Erickson, Antônio Thomé, Jane Thorburn, Annika Strandell, Per Lundorff and Bo Lindblom. Their work appears in journals such as Journal of Neuroscience, Frontiers in Aging Neuroscience, Behavioural Brain Research, Nature Communications and Cerebral Cortex.

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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