D. Chambers

765 total citations
24 papers, 596 citations indexed

About

D. Chambers is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, D. Chambers has authored 24 papers receiving a total of 596 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Cell Biology and 6 papers in Physiology. Recurrent topics in D. Chambers's work include Muscle Physiology and Disorders (9 papers), melanin and skin pigmentation (5 papers) and Neurogenetic and Muscular Disorders Research (3 papers). D. Chambers is often cited by papers focused on Muscle Physiology and Disorders (9 papers), melanin and skin pigmentation (5 papers) and Neurogenetic and Muscular Disorders Research (3 papers). D. Chambers collaborates with scholars based in United Kingdom, United States and France. D. Chambers's co-authors include Ian J. Jackson, Vincent Hearing, Neal G. Copeland, Katsuhiko Tsukamoto, N.A. Jenkins, D.J. Gilbert, Peter S. Budd, Randall S. Johnson, Dorothy C. Bennett and Eugene M. Rinchik and has published in prestigious journals such as Nucleic Acids Research, The EMBO Journal and PLoS ONE.

In The Last Decade

D. Chambers

22 papers receiving 575 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Chambers United Kingdom 10 358 314 257 92 78 24 596
Peter S. Budd United Kingdom 10 426 1.2× 374 1.2× 196 0.8× 102 1.1× 156 2.0× 18 740
Eulalie Lasseaux France 12 330 0.9× 306 1.0× 157 0.6× 59 0.6× 56 0.7× 36 484
S. Brian Potterf United States 10 457 1.3× 391 1.2× 225 0.9× 124 1.3× 97 1.2× 10 720
Aaron J. Thomas United States 8 191 0.5× 255 0.8× 58 0.2× 43 0.5× 40 0.5× 11 542
Jean‐Marie Naeyaert Belgium 10 282 0.8× 135 0.4× 83 0.3× 145 1.6× 15 0.2× 13 497
Ritsuro Ideta Japan 13 133 0.4× 202 0.6× 60 0.2× 143 1.6× 100 1.3× 18 505
Emma Martínez‐Alonso Spain 14 350 1.0× 286 0.9× 54 0.2× 16 0.2× 30 0.4× 24 566
Xuanzhu Liu China 11 123 0.3× 224 0.7× 54 0.2× 24 0.3× 56 0.7× 14 333
Denis Moran United States 11 205 0.6× 258 0.8× 86 0.3× 24 0.3× 43 0.6× 19 458
Hugo Moreiras Portugal 8 190 0.5× 95 0.3× 55 0.2× 109 1.2× 53 0.7× 10 302

Countries citing papers authored by D. Chambers

Since Specialization
Citations

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

Fields of papers citing papers by D. Chambers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Chambers

This figure shows the co-authorship network connecting the top 25 collaborators of D. Chambers. A scholar is included among the top collaborators of D. Chambers 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 D. Chambers. D. Chambers 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.
Müller, Juliane S., Irina Zaharieva, Vicente A. Yépez, et al.. (2025). Multi-omics approach identifies a novel recessive pathogenic variant in the TNNT3 gene in two siblings with congenital myopathy. Neuromuscular Disorders. 52. 105415–105415.
2.
Catapano, Francesco, D. Chambers, Simran Singh, et al.. (2025). A comprehensive spatiotemporal map of dystrophin isoform expression in the developing and adult human brain. Acta Neuropathologica Communications. 13(1). 110–110. 2 indexed citations
3.
4.
Pérez‐Rodríguez, Diego, et al.. (2022). Somatic SNCA Copy Number Variants in Multiple System Atrophy are Related to Pathology and Inclusions. Movement Disorders. 38(2). 338–342. 6 indexed citations
5.
Munot, Pinki, Silvia Torelli, Adnan Manzur, et al.. (2021). TRAPPC11 ‐related muscular dystrophy with hypoglycosylation of alpha‐dystroglycan in skeletal muscle and brain. Neuropathology and Applied Neurobiology. 48(2). e12771–e12771. 17 indexed citations
6.
Sewry, Caroline A., L. Feng, D. Chambers, Emma Matthews, & Rahul Phadke. (2021). Importance of immunohistochemical evaluation of developmentally regulated myosin heavy chains in human muscle biopsies. Neuromuscular Disorders. 31(5). 371–384. 7 indexed citations
7.
Catapano, Francesco, Matthew J. Ellis, Silvia Torelli, et al.. (2021). The administration of antisense oligonucleotide golodirsen reduces pathological regeneration in patients with Duchenne muscular dystrophy. Acta Neuropathologica Communications. 9(1). 7–7. 29 indexed citations
8.
Stuckey, Daniel J., Derek Burke, Helen Prunty, et al.. (2020). Lentiviral Hematopoietic Stem Cell Gene Therapy Rescues Clinical Phenotypes in a Murine Model of Pompe Disease. Molecular Therapy — Methods & Clinical Development. 18. 558–570. 9 indexed citations
9.
Ellis, Matthew J., Francesco Catapano, Silvia Torelli, et al.. (2020). A high–throughput digital script for multiplexed immunofluorescent analysis and quantification of sarcolemmal and sarcomeric proteins in muscular dystrophies. Acta Neuropathologica Communications. 8(1). 53–53. 8 indexed citations
10.
Sardone, Valentina, Matthew J. Ellis, Silvia Torelli, et al.. (2018). A novel high-throughput immunofluorescence analysis method for quantifying dystrophin intensity in entire transverse sections of Duchenne muscular dystrophy muscle biopsy samples. PLoS ONE. 13(3). e0194540–e0194540. 17 indexed citations
11.
Hill, Neil, Kevin G. Murphy, Saima Saeed, et al.. (2017). Impact of ghrelin on body composition and muscle function in a long-term rodent model of critical illness. PLoS ONE. 12(8). e0182659–e0182659. 5 indexed citations
12.
Hill, Neil, Saima Saeed, Rahul Phadke, et al.. (2015). Detailed Characterization of a Long-Term Rodent Model of Critical Illness and Recovery. Critical Care Medicine. 43(3). e84–e96. 15 indexed citations
13.
14.
North, Rachel V., et al.. (1997). Does hyperglycaemia have an influence upon colour vision of patients with diabetes mellitus?. Ophthalmic and Physiological Optics. 17(2). 95–101. 4 indexed citations
15.
16.
Jackson, Ian J., D. Chambers, Katsuhiko Tsukamoto, et al.. (1992). A second tyrosinase-related protein, TRP-2, maps to and is mutated at the mouse slaty locus.. The EMBO Journal. 11(2). 527–535. 279 indexed citations
17.
Jackson, Ian J., D. Chambers, Peter S. Budd, & Randall S. Johnson. (1991). The tyrosinase-related protein-1 gene has a structure and promoter sequence very different from tyrosinase. Nucleic Acids Research. 19(14). 3799–3804. 73 indexed citations
18.
Lieschke, Graham J., et al.. (1990). Endometrial adenocarcinoma presenting as pituitary apoplexy. Australian and New Zealand Journal of Medicine. 20(1). 81–84. 13 indexed citations
19.
Jackson, Ian J., D. Chambers, Eugene M. Rinchik, & Dorothy C. Bennett. (1990). Characterization of TRP-1 mRNA levels in dominant and recessive mutations at the mouse brown (b) locus.. Genetics. 126(2). 451–459. 65 indexed citations
20.
Affara, Nabeel A., D. Chambers, J S O′Brien, et al.. (1989). Evidence for distinguishable transcripts of the putative testis determining gene (ZFY) and mapping of homologous cDNA sequences to chromosomes X,Y and 9. Nucleic Acids Research. 17(8). 2987–2999. 28 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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