Jonathan M. Auerbach

4.1k citations
10 papers · 3.0k · 2 hit papers · h-index 10

Impact in

Papers in

Jonathan M. Auerbach

10 papers receiving 2.9k citations

Jonathan M. Auerbach's Hit Papers

Dopamine neurons derived from embryonic stem cells function in an animal model of Parkinson's disease 2002 · 1.3k citations
1.3k0+8+17Years since publication4008001.2k

Peers

Jonathan M. Auerbach
Comparison fields: 5 of 95
  • Developmental Neuroscience 874
  • Cellular and Molecular Neuroscience 1.2k
  • Molecular Biology 2.3k
  • Genetics 318
  • Neurology 175
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Citations per field
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Citations per year

Countries citing papers authored by Jonathan M. Auerbach

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan M. Auerbach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1
Dopamine neurons derived from embryonic stem cells function in an animal model of Parkinson's disease
Hit paper breakdown →
20021327
2
Efficient generation of midbrain and hindbrain neurons from mouse embryonic stem cells
Hit paper breakdown →
20001060
3 2006125
4 1997111
5 199895
6 200788
7 200083
8 200566
9 200752
10 200638

About Jonathan M. Auerbach

Jonathan M. Auerbach is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Developmental Neuroscience, Surgery and Cognitive Neuroscience, having authored 10 papers that have together received 3.0k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (8 papers), CRISPR and Genetic Engineering (6 papers), Neurogenesis and neuroplasticity mechanisms (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Nuclear Receptors and Signaling (1 paper), Receptor Mechanisms and Signaling (1 paper), 3D Printing in Biomedical Research (1 paper) and Memory and Neural Mechanisms (1 paper). The work is most often cited by research in Developmental Neuroscience (874 citations), Cellular and Molecular Neuroscience (1.2k citations), Molecular Biology (2.3k citations), Genetics (318 citations) and Neurology (175 citations). Jonathan M. Auerbach has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Ron McKay, Sang‐Hun Lee, Nadya Lumelsky, Lorenz Studer, John Nguyen, Jong‐Hoon Kim, Krys S. Bankiewicz, Rosario Sánchez‐Pernaute, Denise Gavin and José A. Rodríguez‐Gómez. Their work appears in journals such as Nature Biotechnology, Stem Cells, Journal of Neuroscience, BMC Biology and Current Protocols in Stem Cell 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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