Daniel R. Hochbaum

3.6k citations
17 papers · 1.6k indexed · h-index 11

Impact in

    • Photoreceptor and optogenetics research
    • Neuroscience and Neural Engineering
    • Neuroscience and Neuropharmacology Research
  • Biophysics top 2%
    • Advanced Fluorescence Microscopy Techniques

Papers in

Daniel R. Hochbaum

17 papers receiving 1.5k citations

Peers

Daniel R. Hochbaum
Comparison fields: 5 of 106
  • Cellular and Molecular Neuroscience 842
  • Biophysics 186
  • Cognitive Neuroscience 397
  • Neurology 127
  • Developmental Neuroscience 55
Replace Min Jee Jang with:
Min Jee Jang South Korea
Amy Hu United States
Gerard Joey Broussard United States
J. Hasseman United States
Marco Dal Maschio Italy
Getahun Tsegaye United States
Helen H. Yang United States
Graham T. Holt United States
Michael R. Tadross United States
Boaz Mohar United States
Daniel R. Hochbaum relative to Min Jee Jang South Korea Min Jee Jang's profile →
Citations per field
00.5×1.5×2.2×
Min Jee Jang · 1×
Citations per year

Countries citing papers authored by Daniel R. Hochbaum

Since Specialization
Citations

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

Fields of papers citing papers by Daniel R. Hochbaum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 20248
2 20224
3 202133
4 202067
5 2019100
6 2017322
7 2017140
8 20176
9 201622
10 2014152
11 201429
12 20141
13 20133
14 2011280
15 2011342
16 201151
17 20101

About Daniel R. Hochbaum

Daniel R. Hochbaum is a scholar working on Aging, Biophysics, Cognitive Neuroscience, Cellular and Molecular Neuroscience and Neurology, having authored 17 papers that have together received 1.6k indexed citations. Recurring topics across this work include Neural dynamics and brain function (8 papers), Photoreceptor and optogenetics research (7 papers), Neuroscience and Neural Engineering (6 papers), Single-cell and spatial transcriptomics (2 papers), Cell Image Analysis Techniques (2 papers), Digital Imaging for Blood Diseases (1 paper), Neuroscience and Neuropharmacology Research (1 paper) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (842 citations), Biophysics (186 citations), Cognitive Neuroscience (397 citations), Neurology (127 citations) and Developmental Neuroscience (55 citations). Daniel R. Hochbaum has collaborated with scholars based in United States, Canada and Singapore. Frequent co-authors include Adam E. Cohen, Adam D. Douglass, Joel M. Kralj, Dougal Maclaurin, Bernardo L. Sabatini, Siniša Hrvatin, Michael E. Greenberg, M. Aurel Nagy, Keiramarie Robertson and Marcelo Cicconet. Their work appears in journals such as Nature Neuroscience, Nature Methods, Journal of the American Chemical Society, Nature Communications and Journal of Applied Physics.

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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