David M. Smith

19.8k total citations · 6 hit papers
258 papers, 15.4k citations indexed

About

David M. Smith is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Surgery. According to data from OpenAlex, David M. Smith has authored 258 papers receiving a total of 15.4k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Molecular Biology, 81 papers in Cellular and Molecular Neuroscience and 66 papers in Surgery. Recurrent topics in David M. Smith's work include Neuropeptides and Animal Physiology (71 papers), Receptor Mechanisms and Signaling (56 papers) and Pancreatic function and diabetes (42 papers). David M. Smith is often cited by papers focused on Neuropeptides and Animal Physiology (71 papers), Receptor Mechanisms and Signaling (56 papers) and Pancreatic function and diabetes (42 papers). David M. Smith collaborates with scholars based in United Kingdom, United States and Sweden. David M. Smith's co-authors include Stephen R. Bloom, Michael B. Sporn, Mohammad A. Ghatei, Lalage M. Wakefield, J. P. Hinson, S. Kapas, Charles A. Frolik, C. M. B. Edwards, Gillian M. Taylor and S.R. Bloom and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and JAMA.

In The Last Decade

David M. Smith

253 papers receiving 14.9k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A role for glucagon-like peptide-1 in the central regulation of feeding

1996 1.6k citations Mandy D. Turton, Donal O’Shea et al. profile →
Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes

2016 987 citations David M. Smith et al. profile →
Adrenomedullin, a Multifunctional Regulatory Peptide*

2000 642 citations David M. Smith et al. profile →
Distribution and modulation of the cellular receptor for transforming growth factor-beta.

1987 488 citations David M. Smith et al. profile →
Latent transforming growth factor-beta from human platelets. A high molecular weight complex containing precursor sequences.

1988 477 citations David M. Smith et al. profile →
Characterization of a membrane receptor for transforming growth factor-beta in normal rat kidney fibroblasts.

1984 440 citations David M. Smith et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David M. Smith United Kingdom	61	6.5k	4.4k	3.5k	3.3k	3.0k	258	15.4k
Gozoh Tsujimoto Japan	70	9.6k 1.5×	2.5k 0.6×	2.8k 0.8×	2.4k 0.7×	2.2k 0.7×	336	18.0k
Jens F. Rehfeld Denmark	65	4.3k 0.7×	4.5k 1.0×	3.7k 1.0×	5.6k 1.7×	2.2k 0.7×	415	14.9k
Mohan K. Raizada United States	75	9.9k 1.5×	2.8k 0.6×	4.2k 1.2×	2.3k 0.7×	1.6k 0.6×	434	22.2k
Thomas E. Adrian United States	71	6.4k 1.0×	6.5k 1.5×	2.8k 0.8×	5.3k 1.6×	2.6k 0.9×	512	19.6k
Anthony P. Davenport United Kingdom	75	7.4k 1.1×	4.4k 1.0×	2.1k 0.6×	4.5k 1.4×	1.6k 0.5×	340	22.7k
Detlev Ganten Germany	81	10.0k 1.5×	4.1k 0.9×	7.3k 2.1×	1.9k 0.6×	2.2k 0.8×	556	26.3k
Hiroo Imura Japan	74	7.5k 1.1×	4.3k 1.0×	6.6k 1.9×	3.3k 1.0×	1.9k 0.6×	755	24.4k
Anthony J. Harmar United Kingdom	56	7.9k 1.2×	8.8k 2.0×	1.3k 0.4×	1.5k 0.5×	3.3k 1.1×	133	18.7k
Paul A. Insel United States	90	15.1k 2.3×	4.4k 1.0×	1.9k 0.6×	1.9k 0.6×	1.0k 0.4×	405	25.1k
Daniel T. O’Connor United States	67	6.9k 1.1×	3.4k 0.8×	2.0k 0.6×	1.7k 0.5×	706 0.2×	368	15.7k

Countries citing papers authored by David M. Smith

Since Specialization

Citations

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

Fields of papers citing papers by David M. Smith

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David M. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of David M. Smith. A scholar is included among the top collaborators of David M. 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 David M. Smith. David M. Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Huddleston, John, Mónica Galiano, David M. Smith, et al.. (2026). Nomenclature for Tracking of Genetic Variation of Seasonal Influenza Viruses. Influenza and Other Respiratory Viruses. 20(2). e70230–e70230.

Ford, Brian E., Fiona Oakley, Rebecca J. Fairclough, et al.. (2024). Compromised chronic efficacy of a glucokinase activator AZD1656 in mouse models for common human GCKR variants. Biochemical Pharmacology. 229. 116499–116499. 1 indexed citations

Davies, Gareth M., Tiziana Monteverde, Jonathan Tart, et al.. (2024). High throughput application of the NanoBiT Biochemical Assay for the discovery of selective inhibitors of the interaction of PI3K-p110α with KRAS. SLAS DISCOVERY. 29(8). 100197–100197. 1 indexed citations

Pilling, James, et al.. (2024). An image-based screen for secreted proteins involved in breast cancer G0 cell cycle arrest. Scientific Data. 11(1). 868–868.

Mullooly, N, David M. Smith, & Davide Gianni. (2023). A multi-parametric high throughput assay for detecting beta-cell proliferation in dispersed primary islets. SLAS DISCOVERY. 28(2). 3–12. 2 indexed citations

Zhang, Yanchen, David M. Smith, Sara Fernandes‐Taylor, et al.. (2023). Rates of Detecting Thyroid Nodules Recommended for Biopsy with Ultrasound: Are All Indications Equal?. Thyroid. 33(12). 1434–1440. 2 indexed citations

Ford, Brian E., Suzannah J. Harnor, Céline Cano, et al.. (2020). Chronic glucokinase activator treatment activates liver Carbohydrate response element binding protein and improves hepatocyte ATP homeostasis during substrate challenge. Diabetes Obesity and Metabolism. 22(11). 1985–1994. 10 indexed citations

Marques, Vanda, Marta B. Afonso, Dean G. Brown, et al.. (2020). Phenotypic high-throughput screening platform identifies novel chemotypes for necroptosis inhibition. Cell Death Discovery. 6(1). 6–6. 16 indexed citations

Colomba, Audrey, Martina Fitzek, Roger George, et al.. (2020). A small molecule inhibitor of HER3: a proof-of-concept study. Biochemical Journal. 477(17). 3329–3347. 8 indexed citations

10.

Taiyab, Aftab, et al.. (2019). Investigating MRTF-A as a novel anti-fibrotic target in trabecular meshwork cells for open angle glaucoma. Investigative Ophthalmology & Visual Science. 60(9). 5148–5148. 1 indexed citations

11.

Kiss, Szilárd, Carlos Quezada-Ruiz, Kathleen Wilson, et al.. (2016). Real-world treatment patterns in injection cost and frequency for ranibizumab versus aflibercept in patients with wet age-related macular degeneration: A 2-year US claims analysis. Investigative Ophthalmology & Visual Science. 57(12). 3335–3335. 2 indexed citations

12.

Faddy, M. J. & David M. Smith. (2011). Analysis of count data with covariate dependence in both mean and variance. Journal of Applied Statistics. 38(12). 2683–2694. 19 indexed citations

13.

Domiati‐Saad, Rana, Göran B. Klintmalm, George J. Netto, et al.. (2005). Acute Graft versus Host Disease After Liver Transplantation: Patterns of Lymphocyte Chimerism. American Journal of Transplantation. 5(12). 2968–2973. 69 indexed citations

14.

Dakin, C. L., I. Gunn, C. J. Small, et al.. (2001). Oxyntomodulin Inhibits Food Intake in the Rat. Endocrinology. 142(10). 4244–4250. 226 indexed citations

15.

Satoh, Fumitoshi, Caroline J. Small, Mary Falzon, et al.. (2000). Characterization of Human and Rat Glucagon-Like Peptide-1 Receptors in the Neurointermediate Lobe: Lack of Coupling to Either Stimulation or Inhibition of Adenylyl Cyclase*. Endocrinology. 141(4). 1301–1309. 44 indexed citations

16.

O’Shea, Donal, David Morgan, Karim Meeran, et al.. (1997). Neuropeptide Y Induced Feeding in the Rat Is Mediated by a Novel Receptor¹. Endocrinology. 138(1). 196–202. 119 indexed citations

17.

Small, C. J., et al.. (1996). Glucagon-like peptide-1 (GLP-1) releases thyrotropin (TSH): characterization of binding sites for GLP-1 on alpha-TSH cells.. Endocrinology. 137(10). 4130–4138. 57 indexed citations

18.

Tyler, J. P. P., David M. Smith, & J. D. Biggers. (1980). Effect of steroids on oocyte maturation and atresia in mouse ovarian fragments in vitro. Reproduction. 58(1). 203–212. 22 indexed citations

19.

Smith, David M., et al.. (1980). Effects of steroids on mouse oocyte maturation in vitro. Reproduction. 60(2). 331–338. 61 indexed citations

20.

Smith, David M., et al.. (1978). Influences of season and age on maturation in vitro of rhesus monkey oocytes. Reproduction. 54(1). 91–95. 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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