Nick J. Dibb

968 total citations
10 papers, 643 citations indexed

About

Nick J. Dibb is a scholar working on Molecular Biology, Aging and Rheumatology. According to data from OpenAlex, Nick J. Dibb has authored 10 papers receiving a total of 643 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Aging and 2 papers in Rheumatology. Recurrent topics in Nick J. Dibb's work include Muscle Physiology and Disorders (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers) and Eosinophilic Disorders and Syndromes (2 papers). Nick J. Dibb is often cited by papers focused on Muscle Physiology and Disorders (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers) and Eosinophilic Disorders and Syndromes (2 papers). Nick J. Dibb collaborates with scholars based in United Kingdom, United States and Australia. Nick J. Dibb's co-authors include Stephen M. Dilworth, Clifford D. Mol, Jonathan Karn, Michael Krause, Ichiro Maruyama, D. M. Brown, Donald G. Moerman, R Waterston, Robert Winston and Rupa Sarkar and has published in prestigious journals such as Nucleic Acids Research, Nature reviews. Cancer and Journal of Molecular Biology.

In The Last Decade

Nick J. Dibb

10 papers receiving 633 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nick J. Dibb United Kingdom	9	482	166	134	84	64	10	643
Miao-Chia Lo United States	15	560 1.2×	60 0.4×	107 0.8×	18 0.2×	47 0.7×	19	693
Payam A. Gammage United Kingdom	17	1.6k 3.3×	275 1.7×	55 0.4×	32 0.4×	50 0.8×	25	1.8k
Martin D. Burkhalter Germany	15	609 1.3×	71 0.4×	23 0.2×	13 0.2×	117 1.8×	29	715
Vladimir E. Belozerov United States	11	429 0.9×	232 1.4×	12 0.1×	16 0.2×	129 2.0×	11	697
Nuria Martí Gutiérrez Spain	9	633 1.3×	152 0.9×	15 0.1×	11 0.1×	154 2.4×	13	846
Sanne M.M. Hensen Netherlands	10	182 0.4×	30 0.2×	26 0.2×	23 0.3×	36 0.6×	12	414
Jordan Wengrod United States	9	763 1.6×	94 0.6×	13 0.1×	15 0.2×	53 0.8×	9	875
Jiang-Cheng Shen United States	8	798 1.7×	370 2.2×	45 0.3×	6 0.1×	133 2.1×	8	1.0k
Helen King United Kingdom	10	544 1.1×	95 0.6×	6 0.0×	58 0.7×	103 1.6×	14	654
Hinke G. Kazemier Netherlands	13	691 1.4×	178 1.1×	16 0.1×	15 0.2×	112 1.8×	16	829

Countries citing papers authored by Nick J. Dibb

Since Specialization

Citations

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

Fields of papers citing papers by Nick J. Dibb

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nick J. Dibb. 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 Nick J. Dibb. The network helps show where Nick J. Dibb may publish in the future.

Co-authorship network of co-authors of Nick J. Dibb

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

All Works

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10 of 10 papers shown

Cao, Benjamin, Robert A. Brown, Nick J. Dibb, et al.. (2020). Glycosylated Nanoparticles Derived from RAFT Polymerization for Effective Drug Delivery to Macrophages. ACS Applied Bio Materials. 3(9). 5775–5786. 10 indexed citations

Chandrashekran, Anil, Colin Casimir, Nick J. Dibb, Carol Readhead, & Robert Winston. (2016). Generating Transgenic Mice by Lentiviral Transduction of Spermatozoa Followed by In Vitro Fertilization and Embryo Transfer. Methods in molecular biology. 1448. 95–106. 2 indexed citations

Tan, Geok Chin, Elcie Chan, Attila Molnár, et al.. (2014). 5′ isomiR variation is of functional and evolutionary importance. Nucleic Acids Research. 42(14). 9424–9435. 180 indexed citations

Kapustin, Yuri, Elcie Chan, Rupa Sarkar, et al.. (2011). Cryptic splice sites and split genes. Nucleic Acids Research. 39(14). 5837–5844. 32 indexed citations

Skobridis, Konstantinos, Vassiliki Theodorou, Roberta Sala, et al.. (2009). Novel Imatinib Derivatives with Altered Specificity between Bcr–Abl and FMS, KIT, and PDGF Receptors. ChemMedChem. 5(1). 130–139. 17 indexed citations

Dibb, Nick J., Stephen M. Dilworth, & Clifford D. Mol. (2004). Switching on kinases: oncogenic activation of BRAF and the PDGFR family. Nature reviews. Cancer. 4(9). 718–727. 150 indexed citations

Dibb, Nick J., Stephen M. Dilworth, & Clifford D. Mol. (2004). Opinion: Switching on kinases: oncogenic activation of BRAF and the PDGFR family. 15 indexed citations

Dibb, Nick J., Ichiro Maruyama, Michael Krause, & Jonathan Karn. (1989). Sequence analysis of the complete Caenorhabditis elegans myosin heavy chain gene family. Journal of Molecular Biology. 205(3). 603–613. 103 indexed citations

Dibb, Nick J., et al.. (1985). Sequence analysis of mutations that affect the synthesis, assembly and enzymatic activity of the unc-54 myosin heavy chain of Caenorhabditis elegans. Journal of Molecular Biology. 183(4). 543–551. 117 indexed citations

10.

Karn, Jonathan, Nick J. Dibb, & David M. Miller. (1985). Cloning Nematode Myosin Genes. PubMed. 6. 185–237. 17 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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