Daniel M. Bear

6.3k citations
30 papers · 3.8k · 2 hit papers · h-index 18

Impact in

Papers in

Daniel M. Bear

29 papers receiving 3.7k citations

Daniel M. Bear's Hit Papers

Widespread transcription at neuronal activity-regulated enhancers 2010 · 1.8k citations
1.8k0+16+32Years since publication50010001.5k

Peers

Daniel M. Bear
Comparison fields: 5 of 140
  • Cancer Research 697
  • Psychiatry and Mental health 633
  • Sensory Systems 170
  • Cognitive Neuroscience 613
  • 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 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Widespread transcription at neuronal activity-regulated enhancers
Hit paper breakdown →
20101786
2
Quantitative Analysis of Interictal Behavior in Temporal Lobe Epilepsy
Hit paper breakdown →
1977585
3 2008355
4 1983166
5 2010133
6 198899
7 201694
8 201690
9 200771
10 198268
11 198460
12 198755
13 198844
14 197342
15 202236
16 201935
17 198126
18 199222
19
Task-driven convolutional recurrent models of the visual system
201816
20
Case 2: Behavioral changes with temporal lobe epilepsy: assessment and treatment.
198014

About Daniel M. Bear

Daniel M. Bear is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health, Molecular Biology, Computer Vision and Pattern Recognition and Sensory Systems, having authored 30 papers that have together received 3.8k indexed citations. Recurring topics across this work include Epilepsy research and treatment (7 papers), Biochemical Analysis and Sensing Techniques (4 papers), Olfactory and Sensory Function Studies (4 papers), Visual Attention and Saliency Detection (3 papers), Memory and Neural Mechanisms (3 papers), Neurobiology and Insect Physiology Research (3 papers), Psychosomatic Disorders and Their Treatments (3 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Cancer Research (697 citations), Psychiatry and Mental health (633 citations), Sensory Systems (170 citations), Cognitive Neuroscience (613 citations) and Molecular Biology (2.0k citations). Daniel M. Bear has collaborated with scholars based in United States, Belgium and South Africa. Frequent co-authors include Paul Fedio, Eirene Markenscoff-Papadimitriou, Michael E. Greenberg, Tae-Kyung Kim, David A. Harmin, Martin Hemberg, Jesse Gray, Jing Wu, Haruhiko Bito and Scott Kuersten. Their work appears in journals such as Journal of Vision, American Journal of Psychiatry, Journal of Neuropsychiatry, Journal of Psychiatric Research and Current Biology.

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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