Daniel M. Bear

6.3k citations
35 papers · 4.2k · 2 hit papers · h-index 19

Impact in

Papers in

Daniel M. Bear

33 papers receiving 4.0k citations

Daniel M. Bear's Hit Papers

Widespread transcription at neuronal activity-regulated enhancers 2010 · 1.9k citations
1.9k0+16+32Years since publication50010001.5k

Peers

Daniel M. Bear
Comparison fields: 5 of 143
  • Cancer Research 697
  • Psychiatry and Mental health 676
  • Sensory Systems 193
  • Cognitive Neuroscience 667
  • Molecular Biology 2.0k
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Citations per year

Countries citing papers authored by Daniel M. Bear

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. Bear

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Widespread transcription at neuronal activity-regulated enhancers
Hit paper breakdown →
20101860
2
Quantitative Analysis of Interictal Behavior in Temporal Lobe Epilepsy
Hit paper breakdown →
1977692
3 2008368
4 1983192
5 2010139
6 1988115
7 2016105
8 2016100
9 198277
10 200773
11 198470
12 198762
13 198856
14 197345
15 202242
16 201936
17 198129
18 199222
19
Case 2: Behavioral changes with temporal lobe epilepsy: assessment and treatment.
198019
20
Task-driven convolutional recurrent models of the visual system
201816

About Daniel M. Bear

Daniel M. Bear is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health, Computer Vision and Pattern Recognition, Molecular Biology and Sensory Systems, having authored 35 papers that have together received 4.2k indexed citations. Recurring topics across this work include Epilepsy research and treatment (7 papers), Olfactory and Sensory Function Studies (4 papers), Biochemical Analysis and Sensing Techniques (4 papers), Psychosomatic Disorders and Their Treatments (3 papers), Visual Attention and Saliency Detection (3 papers), Neural dynamics and brain function (3 papers), Neurobiology and Insect Physiology Research (3 papers) and Memory and Neural Mechanisms (3 papers). The work is most often cited by research in Cancer Research (697 citations), Psychiatry and Mental health (676 citations), Sensory Systems (193 citations), Cognitive Neuroscience (667 citations) and Molecular Biology (2.0k citations). Daniel M. Bear has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include Paul Fedio, David A. Harmin, Eirene Markenscoff-Papadimitriou, Michael E. Greenberg, Jesse Gray, Tae-Kyung Kim, Martin Hemberg, Gabriel Kreiman, Paul F. Worley and Jing Wu. Their work appears in journals such as Journal of Vision, American Journal of Psychiatry, Journal of Neuropsychiatry, Neural Computation and Nature Communications.

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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