John Ngai

24.2k total citations · 3 hit papers
78 papers, 8.6k citations indexed

About

John Ngai is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Sensory Systems. According to data from OpenAlex, John Ngai has authored 78 papers receiving a total of 8.6k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 31 papers in Cellular and Molecular Neuroscience and 30 papers in Sensory Systems. Recurrent topics in John Ngai's work include Olfactory and Sensory Function Studies (30 papers), Biochemical Analysis and Sensing Techniques (28 papers) and Neurobiology and Insect Physiology Research (24 papers). John Ngai is often cited by papers focused on Olfactory and Sensory Function Studies (30 papers), Biochemical Analysis and Sensing Techniques (28 papers) and Neurobiology and Insect Physiology Research (24 papers). John Ngai collaborates with scholars based in United States, Italy and Australia. John Ngai's co-authors include Davide Risso, Sandrine Dudoit, Terence P. Speed, Richard Axel, Russell B. Fletcher, Robert Vassar, Diya Das, Elizabeth Purdom, Nir Yosef and Kelly Street and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

John Ngai

76 papers receiving 8.4k citations

Hit Papers

Slingshot: cell lin... 1993 2026 2004 2015 2018 2014 1993 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Ngai United States 42 3.7k 2.9k 2.8k 2.1k 855 78 8.6k
Iván Rodríguez Switzerland 39 3.1k 0.8× 2.9k 1.0× 2.8k 1.0× 2.2k 1.0× 587 0.7× 68 7.5k
Randall R. Reed United States 59 7.2k 1.9× 5.0k 1.8× 3.9k 1.4× 2.8k 1.3× 560 0.7× 112 13.2k
Misao Suzuki Japan 41 2.8k 0.8× 1.6k 0.6× 979 0.3× 795 0.4× 1.4k 1.7× 91 6.4k
Hitoshi Sakano Japan 38 2.4k 0.7× 2.3k 0.8× 2.5k 0.9× 1.9k 0.9× 1.9k 2.2× 66 6.9k
Stavros Lomvardas United States 36 3.9k 1.1× 1.3k 0.5× 1.1k 0.4× 836 0.4× 652 0.8× 53 6.2k
Ricardo E. Dolmetsch United States 42 9.4k 2.5× 5.0k 1.7× 2.3k 0.8× 316 0.2× 1.5k 1.8× 69 14.6k
Bradley A. Schulte United States 53 4.1k 1.1× 672 0.2× 4.0k 1.4× 476 0.2× 962 1.1× 199 8.7k
Jonathan Pevsner United States 50 5.2k 1.4× 1.4k 0.5× 637 0.2× 639 0.3× 452 0.5× 120 9.6k
Rainer W. Friedrich Germany 43 1.4k 0.4× 3.5k 1.2× 2.5k 0.9× 879 0.4× 177 0.2× 94 6.4k
Frank Müller Germany 50 6.2k 1.7× 3.5k 1.2× 634 0.2× 408 0.2× 244 0.3× 166 8.9k

Countries citing papers authored by John Ngai

Since Specialization
Citations

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

Fields of papers citing papers by John Ngai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Ngai. 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 John Ngai. The network helps show where John Ngai may publish in the future.

Co-authorship network of co-authors of John Ngai

This figure shows the co-authorship network connecting the top 25 collaborators of John Ngai. A scholar is included among the top collaborators of John Ngai 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 John Ngai. John Ngai 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.
Kramer, Daniel J., Polina Kosillo, Drew Friedmann, et al.. (2021). Generation of a DAT-P2A-Flpo mouse line for intersectional genetic targeting of dopamine neuron subpopulations. Cell Reports. 35(6). 109123–109123. 14 indexed citations
2.
Naka, Alexander, Julia Veit, Rebecca K. Chance, et al.. (2019). Complementary networks of cortical somatostatin interneurons enforce layer specific control. eLife. 8. 75 indexed citations
3.
Kramer, Daniel J., Davide Risso, Polina Kosillo, John Ngai, & Helen S. Bateup. (2018). Combinatorial Expression ofGrpandNeurod6Defines Dopamine Neuron Populations with Distinct Projection Patterns and Disease Vulnerability. eNeuro. 5(3). ENEURO.0152–18.2018. 47 indexed citations
4.
Mukamel, Eran A. & John Ngai. (2018). Perspectives on defining cell types in the brain. Current Opinion in Neurobiology. 56. 61–68. 26 indexed citations
5.
Fletcher, Russell B., Melanie S. Prasol, José L. Estrada, et al.. (2011). p63 Regulates Olfactory Stem Cell Self-Renewal and Differentiation. Neuron. 72(5). 748–759. 99 indexed citations
6.
Cameron, Peter, Makoto Hiroi, John Ngai, & Kristin Scott. (2010). The molecular basis for water taste in Drosophila. Nature. 465(7294). 91–95. 214 indexed citations
7.
Vranizan, Karen, et al.. (2008). Early Anti-Oxidative and Anti-Proliferative Curcumin Effects on Neuroglioma Cells Suggest Therapeutic Targets. Neurochemical Research. 33(9). 1701–1710. 52 indexed citations
8.
Duggan, Cynthia, et al.. (2008). Foxg1Is Required for Development of the Vertebrate Olfactory System. Journal of Neuroscience. 28(20). 5229–5239. 83 indexed citations
9.
Alioto, Tyler & John Ngai. (2006). The repertoire of olfactory C family G protein-coupled receptors in zebrafish: candidate chemosensory receptors for amino acids. BMC Genomics. 7(1). 309–309. 72 indexed citations
10.
Ngai, John, et al.. (2005). Using Microarrays to Facilitate Positional Cloning: Identification of Tomosyn as an Inhibitor of Neurosecretion. PLoS Genetics. 1(1). e2–e2. 39 indexed citations
11.
Weidinger, Gilbert, et al.. (2005). The Sp1-Related Transcription Factors sp5 and sp5-like Act Downstream of Wnt/β-Catenin Signaling in Mesoderm and Neuroectoderm Patterning. Current Biology. 15(6). 489–500. 169 indexed citations
12.
Alioto, Tyler & John Ngai. (2005). The odorant receptor repertoire of teleost fish. BMC Genomics. 6(1). 173–173. 122 indexed citations
13.
Acher, Francine, et al.. (2004). Molecular Determinants of Ligand Selectivity in a Vertebrate Odorant Receptor. Journal of Neuroscience. 24(45). 10128–10137. 65 indexed citations
14.
Dı́az, Elva, Yongchao Ge, Jean Yang, et al.. (2002). Molecular Analysis of Gene Expression in the Developing Pontocerebellar Projection System. Neuron. 36(3). 417–434. 75 indexed citations
15.
Kratz, Erica, Jason C. Dugas, & John Ngai. (2002). Odorant receptor gene regulation: implications from genomic organization. Trends in Genetics. 18(1). 29–34. 47 indexed citations
16.
Fan, Jinhong & John Ngai. (2001). Onset of Odorant Receptor Gene Expression during Olfactory Sensory Neuron Regeneration. Developmental Biology. 229(1). 119–127. 6 indexed citations
17.
Dynes, Joseph L. & John Ngai. (1998). Pathfinding of Olfactory Neuron Axons to Stereotyped Glomerular Targets Revealed by Dynamic Imaging in Living Zebrafish Embryos. Neuron. 20(6). 1081–1091. 106 indexed citations
18.
Barth, Alison L., Jason C. Dugas, & John Ngai. (1997). Noncoordinate Expression of Odorant Receptor Genes Tightly Linked in the Zebrafish Genome. Neuron. 19(2). 359–369. 57 indexed citations
19.
Vassar, Robert, John Ngai, & Richard Axel. (1993). Spatial segregation of odorant receptor expression in the mammalian olfactory epithelium. Cell. 74(2). 309–318. 692 indexed citations breakdown →
20.
Chess, Andrew, et al.. (1992). Molecular Biology of Smell: Expression of the Multigene Family Encoding Putative Odorant Receptors. Cold Spring Harbor Symposia on Quantitative Biology. 57(0). 505–516. 27 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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