Daniel M. Bear

6.3k total citations · 2 hit papers
30 papers, 3.8k citations indexed

About

Daniel M. Bear is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health and Molecular Biology. According to data from OpenAlex, Daniel M. Bear has authored 30 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 7 papers in Psychiatry and Mental health and 4 papers in Molecular Biology. Recurrent topics in Daniel M. Bear's work include Epilepsy research and treatment (7 papers), Biochemical Analysis and Sensing Techniques (4 papers) and Olfactory and Sensory Function Studies (4 papers). Daniel M. Bear is often cited by papers focused on Epilepsy research and treatment (7 papers), Biochemical Analysis and Sensing Techniques (4 papers) and Olfactory and Sensory Function Studies (4 papers). Daniel M. Bear collaborates with scholars based in United States, Belgium and South Africa. Daniel M. Bear's co-authors include Paul Fedio, Michael E. Greenberg, Martin Hemberg, Tae-Kyung Kim, David A. Harmin, Jesse Gray, Eirene Markenscoff-Papadimitriou, Paul Worley, Haruhiko Bito and Scott Kuersten and has published in prestigious journals such as Nature, Cell and Nature Communications.

In The Last Decade

Daniel M. Bear

29 papers receiving 3.7k citations

Hit Papers

Widespread transcription at... 1977 2026 1993 2009 2010 1977 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel M. Bear United States 18 2.0k 697 633 613 455 30 3.8k
Theodore P. Rasmussen United States 39 3.0k 1.5× 791 1.1× 1.1k 1.8× 2.4k 3.9× 603 1.3× 91 7.1k
Edward I. Ginns United States 45 3.0k 1.5× 279 0.4× 383 0.6× 469 0.8× 975 2.1× 118 6.7k
Maja Bućan United States 40 4.1k 2.0× 542 0.8× 375 0.6× 730 1.2× 804 1.8× 102 7.3k
Carl Ernst Canada 34 2.1k 1.0× 414 0.6× 335 0.5× 476 0.8× 926 2.0× 71 4.5k
Matteo Caleo Italy 42 1.8k 0.9× 280 0.4× 550 0.9× 1.1k 1.7× 2.4k 5.2× 141 6.3k
Bert Gold United States 29 1.9k 1.0× 332 0.5× 366 0.6× 1.2k 2.0× 1.9k 4.3× 58 6.8k
Karen H. Friderici United States 31 3.0k 1.5× 863 1.2× 323 0.5× 352 0.6× 103 0.2× 65 4.5k
Serge Weis Germany 37 1.3k 0.6× 232 0.3× 553 0.9× 409 0.7× 846 1.9× 150 4.9k
Patricia M. White United States 27 1.2k 0.6× 264 0.4× 279 0.4× 1.0k 1.6× 304 0.7× 64 3.4k
Andrea Hermann Germany 29 1.7k 0.8× 150 0.2× 203 0.3× 824 1.3× 223 0.5× 74 3.6k

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-authorship network of co-authors of Daniel M. Bear

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Bear. A scholar is included among the top collaborators of Daniel M. Bear 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 M. Bear. Daniel M. Bear 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
1.
Bear, Daniel M., et al.. (2024). CD20/MS4A1 is a mammalian olfactory receptor expressed in a subset of olfactory sensory neurons that mediates innate avoidance of predators. Nature Communications. 15(1). 3360–3360. 3 indexed citations
2.
Tung, Hsiao-Yu Fish, Mingyu Ding, Zhenfang Chen, et al.. (2023). Evaluating physical scene understanding with objects consisting of different physical attributes in humans and machines. Journal of Vision. 23(9). 5622–5622. 3 indexed citations
3.
O’Connell, Thomas, et al.. (2023). Benchmarking Human Mid-Level Scene Understanding. Journal of Vision. 23(9). 5798–5798.
4.
Nayebi, Aran, Daniel M. Bear, Kohitij Kar, et al.. (2022). Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition. Neural Computation. 34(8). 1652–1675. 9 indexed citations
5.
Murray, Evan, Greg Andrews, Sung Jin Park, et al.. (2022). Spatial transcriptomic reconstruction of the mouse olfactory glomerular map suggests principles of odor processing. Nature Neuroscience. 25(4). 484–492. 36 indexed citations
6.
Li, Yunzhu, Kexin Yi, Daniel M. Bear, et al.. (2020). Visual Grounding of Learned Physical Models. 1. 5927–5936. 3 indexed citations
7.
Nayebi, Aran, Daniel M. Bear, Jonas Kubilius, et al.. (2018). Task-driven convolutional recurrent models of the visual system. Lirias (KU Leuven). 31. 5290–5301. 16 indexed citations
8.
Nayebi, Aran, Jonas Kubilius, Daniel M. Bear, et al.. (2018). Convolutional recurrent neural network models of dynamics in higher visual cortex. Journal of Vision. 18(10). 717–717. 2 indexed citations
9.
Bear, Daniel M., Jean‐Marc Lassance, Hopi E. Hoekstra, & Sandeep Robert Datta. (2016). The Evolving Neural and Genetic Architecture of Vertebrate Olfaction. Current Biology. 26(20). R1039–R1049. 90 indexed citations
10.
Greer, Paul L., Daniel M. Bear, Jean‐Marc Lassance, et al.. (2016). A Family of non-GPCR Chemosensors Defines an Alternative Logic for Mammalian Olfaction. Cell. 165(7). 1734–1748. 94 indexed citations
11.
Kim, Tae-Kyung, Martin Hemberg, Jesse Gray, et al.. (2010). Widespread transcription at neuronal activity-regulated enhancers. Nature. 465(7295). 182–187. 1786 indexed citations breakdown →
12.
Williams, Ashley, Yongxian Qian, Daniel M. Bear, & Constance R. Chu. (2010). Assessing degeneration of human articular cartilage with ultra-short echo time (UTE) T2* mapping. Osteoarthritis and Cartilage. 18(4). 539–546. 133 indexed citations
13.
Flavell, Steven W., Tae-Kyung Kim, Jesse Gray, et al.. (2008). Genome-Wide Analysis of MEF2 Transcriptional Program Reveals Synaptic Target Genes and Neuronal Activity-Dependent Polyadenylation Site Selection. Neuron. 60(6). 1022–1038. 355 indexed citations
14.
Pfaff, Kathleen L., et al.. (2007). The Zebra fish cassiopeia Mutant Reveals that SIL Is Required for Mitotic Spindle Organization. Molecular and Cellular Biology. 27(16). 5887–5897. 71 indexed citations
15.
Devinsky, Orrin, et al.. (1992). Aggressive behavior following exposure to cholinesterase inhibitors. Journal of Neuropsychiatry. 4(2). 189–194. 22 indexed citations
16.
Bear, Daniel M., et al.. (1989). Interictal behavior syndrome in temporal lobe epilepsy: the views of three experts. Journal of Neuropsychiatry. 1(3). 308–318. 4 indexed citations
17.
Devinsky, Orrin, Daniel M. Bear, & Bruce T. Volpe. (1988). Confusional States Following Posterior Cerebral Artery Infarction. Archives of Neurology. 45(2). 160–163. 44 indexed citations
18.
Weiger, Wendy A. & Daniel M. Bear. (1988). An approach to the neurology of aggression. Journal of Psychiatric Research. 22(2). 85–98. 99 indexed citations
19.
Bear, Daniel M., et al.. (1981). Increased autonomic responses to neutral and emotional stimuli in patients with temporal lobe epilepsy. American Journal of Psychiatry. 138(6). 843–845. 26 indexed citations
20.
Geschwind, Norman, et al.. (1980). Case 2: Behavioral changes with temporal lobe epilepsy: assessment and treatment.. PubMed. 41(3). 89–95. 14 indexed citations

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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