Desmond Smith

6.4k total citations · 1 hit paper
87 papers, 4.3k citations indexed

About

Desmond Smith is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Desmond Smith has authored 87 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Molecular Biology, 28 papers in Genetics and 10 papers in Cellular and Molecular Neuroscience. Recurrent topics in Desmond Smith's work include Gene expression and cancer classification (20 papers), Bioinformatics and Genomic Networks (18 papers) and Genetics and Neurodevelopmental Disorders (11 papers). Desmond Smith is often cited by papers focused on Gene expression and cancer classification (20 papers), Bioinformatics and Genomic Networks (18 papers) and Genetics and Neurodevelopmental Disorders (11 papers). Desmond Smith collaborates with scholars based in United States, France and Netherlands. Desmond Smith's co-authors include Edward M. Rubin, Arshad H. Khan, Richard M. Leahy, Simon R. Cherry, Richard Smith, Weijun Qian, Mary E. Stevens, Ting‐Ting Huang, Haruhiko Sago and Elaine J. Carlson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Nature Genetics.

In The Last Decade

Desmond Smith

82 papers receiving 4.2k citations

Hit Papers

A YAC Mouse Model for Hun... 1999 2026 2008 2017 1999 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Desmond Smith 2.5k 1.1k 1.0k 766 415 87 4.3k
Carrolee Barlow 5.3k 2.1× 1.2k 1.2× 767 0.8× 304 0.4× 717 1.7× 93 8.1k
Eric B. Dammer 3.6k 1.4× 525 0.5× 626 0.6× 110 0.1× 2.2k 5.4× 138 6.5k
Jeffrey N. Savas 3.9k 1.5× 514 0.5× 2.3k 2.3× 87 0.1× 1.0k 2.4× 94 7.4k
Lorene K. Langeberg 6.5k 2.6× 481 0.5× 2.1k 2.1× 167 0.2× 507 1.2× 73 8.2k
Fan Gao 4.5k 1.8× 486 0.5× 2.5k 2.5× 70 0.1× 1.2k 2.9× 123 7.8k
Éric Reiter 4.2k 1.7× 663 0.6× 2.2k 2.2× 497 0.6× 273 0.7× 103 5.8k
Simone Codeluppi 4.6k 1.8× 500 0.5× 1.2k 1.2× 142 0.2× 841 2.0× 32 6.9k
Naoyuki Inagaki 3.7k 1.5× 280 0.3× 2.7k 2.6× 155 0.2× 471 1.1× 104 7.2k
Jie Zhu 1.4k 0.5× 327 0.3× 1.9k 1.9× 444 0.6× 201 0.5× 121 4.1k
Joe G. Hollyfield 7.3k 2.9× 407 0.4× 2.5k 2.5× 201 0.3× 461 1.1× 211 10.5k

Countries citing papers authored by Desmond Smith

Since Specialization
Citations

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

Fields of papers citing papers by Desmond Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Desmond Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Desmond Smith. A scholar is included among the top collaborators of Desmond Smith 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 Desmond Smith. Desmond Smith 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.
Khan, Arshad H., et al.. (2022). Single-cell analysis of gene expression in the substantia nigra pars compacta of a pesticide-induced mouse model of Parkinson’s disease. Translational Neuroscience. 13(1). 255–269. 7 indexed citations
2.
Khan, Arshad H., Andy Lin, Richard T. Wang, et al.. (2020). Pooled analysis of radiation hybrids identifies loci for growth and drug action in mammalian cells. Genome Research. 30(10). 1458–1467. 1 indexed citations
3.
Hasin-Brumshtein, Yehudit, Arshad H. Khan, Farhad Hormozdiari, et al.. (2016). Hypothalamic transcriptomes of 99 mouse strains reveal trans eQTL hotspots, splicing QTLs and novel non-coding genes. eLife. 5. 23 indexed citations
4.
Smith, Desmond, et al.. (2012). Our journey with Alzheimer's disease. 59(2). 5. 2 indexed citations
5.
Park, Christopher C, Greg D. Gale, Simone de Jong, et al.. (2011). Gene networks associated with conditional fear in mice identified using a systems genetics approach. BMC Systems Biology. 5(1). 43–43. 62 indexed citations
6.
Lin, Andy, Richard T. Wang, Sangtae Ahn, Christopher C Park, & Desmond Smith. (2010). A genome-wide map of human genetic interactions inferred from radiation hybrid genotypes. Genome Research. 20(8). 1122–1132. 75 indexed citations
7.
Petyuk, Vladislav, Weijun Qian, Richard Smith, & Desmond Smith. (2009). Mapping protein abundance patterns in the brain using voxelation combined with liquid chromatography and mass spectrometry. Methods. 50(2). 77–84. 29 indexed citations
8.
An, Li, Hongbo Xie, Mark H. Chin, et al.. (2009). Analysis of multiplex gene expression maps obtained by voxelation. BMC Bioinformatics. 10(S4). S10–S10. 5 indexed citations
9.
Smith, Desmond. (2009). Mitochondrial dysfunction in mouse models of Parkinson’s disease revealed by transcriptomics and proteomics. Journal of Bioenergetics and Biomembranes. 41(6). 487–491. 22 indexed citations
11.
Khan, Arshad H., et al.. (2008). A genome-wide panel of congenic mice reveals widespread epistasis of behavior quantitative trait loci. Molecular Psychiatry. 14(6). 631–645. 24 indexed citations
12.
Petyuk, Vladislav, Weijun Qian, Mark H. Chin, et al.. (2007). Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography–mass spectrometry. Genome Research. 17(3). 328–336. 64 indexed citations
13.
Sforza, Daniel, Jacopo Annese, Dahai Liu, et al.. (2004). Anatomical Methods for Voxelation of the Mammalian Brain. Neurochemical Research. 29(6). 1299–1306. 1 indexed citations
14.
Liu, Dahai & Desmond Smith. (2003). Voxelation and gene expression tomography for the acquisition of 3-D gene expression maps in the brain. Methods. 31(4). 317–325. 19 indexed citations
15.
Leil, Tarek A., Alexei Ossadtchi, Thomas E. Nichols, Richard M. Leahy, & Desmond Smith. (2003). Genes regulated by learning in the hippocampus. Journal of Neuroscience Research. 71(6). 763–768. 35 indexed citations
16.
Brown, Vanessa M., Alexei Ossadtchi, Arshad H. Khan, et al.. (2002). High-Throughput Imaging of Brain Gene Expression. Genome Research. 12(2). 244–254. 41 indexed citations
17.
Brown, Vanessa M., Alexei Ossadtchi, Arshad H. Khan, et al.. (2002). Multiplex Three-Dimensional Brain Gene Expression Mapping in a Mouse Model of Parkinson's Disease. Genome Research. 12(6). 868–884. 37 indexed citations
18.
Leil, Tarek A., et al.. (2002). Finding new candidate genes for learning and memory. Journal of Neuroscience Research. 68(2). 127–137. 34 indexed citations
19.
Hodgson, John, N. Agopyan, Claire‐Anne Gutekunst, et al.. (1999). A YAC Mouse Model for Huntington’s Disease with Full-Length Mutant Huntingtin, Cytoplasmic Toxicity, and Selective Striatal Neurodegeneration. Neuron. 23(1). 181–192. 669 indexed citations breakdown →
20.
Smith, Desmond, Mary E. Stevens, Roderick T. Bronson, et al.. (1997). Functional screening of 2 Mb of human chromosome 21q22.2 in transgenic mice implicates minibrain in learning defects associated with Down syndrome. Nature Genetics. 16(1). 28–36. 253 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026