Chris Lumb

593 total citations
8 papers, 313 citations indexed

About

Chris Lumb is a scholar working on Molecular Biology, Insect Science and Pharmacology. According to data from OpenAlex, Chris Lumb has authored 8 papers receiving a total of 313 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Insect Science and 2 papers in Pharmacology. Recurrent topics in Chris Lumb's work include Insect Resistance and Genetics (6 papers), Cholinesterase and Neurodegenerative Diseases (2 papers) and CRISPR and Genetic Engineering (2 papers). Chris Lumb is often cited by papers focused on Insect Resistance and Genetics (6 papers), Cholinesterase and Neurodegenerative Diseases (2 papers) and CRISPR and Genetic Engineering (2 papers). Chris Lumb collaborates with scholars based in Australia, Germany and United States. Chris Lumb's co-authors include Philip Batterham, Charles Robin, Phillip J. Daborn, Henry Chung, Lee Willoughby, Trent Perry, Jason Somers, Paul Battlay, Robert T. Good and Alexandre Fournier‐Level and has published in prestigious journals such as Genetics, Insect Biochemistry and Molecular Biology and Insect Molecular Biology.

In The Last Decade

Chris Lumb

8 papers receiving 308 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chris Lumb Australia	8	228	213	77	48	39	8	313
Xuan‐Zhao Jiang China	13	288 1.3×	281 1.3×	86 1.1×	71 1.5×	38 1.0×	19	401
Caroline McCart United Kingdom	5	312 1.4×	232 1.1×	157 2.0×	56 1.2×	66 1.7×	5	445
Tian‐Xing Jing China	11	180 0.8×	215 1.0×	119 1.5×	18 0.4×	43 1.1×	24	306
Yongan Tan China	11	226 1.0×	202 0.9×	100 1.3×	66 1.4×	69 1.8×	28	340
Tianhua Du China	12	314 1.4×	338 1.6×	156 2.0×	20 0.4×	25 0.6×	22	465
Xuechun Feng United States	10	254 1.1×	184 0.9×	94 1.2×	32 0.7×	33 0.8×	13	336
Huahua Sun China	12	267 1.2×	316 1.5×	86 1.1×	114 2.4×	76 1.9×	25	436
Fei Yin China	11	329 1.4×	291 1.4×	191 2.5×	20 0.4×	29 0.7×	26	422
G. Sharath Chandra India	12	347 1.5×	180 0.8×	112 1.5×	49 1.0×	48 1.2×	22	410
Oxana Skoková Habuštová Czechia	12	188 0.8×	228 1.1×	192 2.5×	41 0.9×	33 0.8×	32	315

Countries citing papers authored by Chris Lumb

Since Specialization

Citations

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

Fields of papers citing papers by Chris Lumb

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chris Lumb

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

All Works

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8 of 8 papers shown

Ding, Jie, Chris Lumb, Nicholas A. Veldhuis, et al.. (2022). The effect of substance P and its common in vivo‐formed metabolites on MRGPRX2 and human mast cell activation. Pharmacology Research & Perspectives. 10(4). e00990–e00990. 7 indexed citations

Perry, Trent, Felipe Martelli, Chris Lumb, et al.. (2021). Role of nicotinic acetylcholine receptor subunits in the mode of action of neonicotinoid, sulfoximine and spinosyn insecticides in Drosophila melanogaster. Insect Biochemistry and Molecular Biology. 131. 103547–103547. 49 indexed citations

Schmidt, Joshua M., Paul Battlay, Robert T. Good, et al.. (2017). Insights into DDT Resistance from the Drosophila melanogaster Genetic Reference Panel. Genetics. 207(3). 1181–1193. 41 indexed citations

Remnant, Emily J., Chris Lumb, Janice Chan, et al.. (2016). Evolution, Expression, and Function of Nonneuronal Ligand-Gated Chloride Channels inDrosophila melanogaster. G3 Genes Genomes Genetics. 6(7). 2003–2012. 10 indexed citations

Somers, Jason, et al.. (2015). In vivo functional analysis of the Drosophila melanogaster nicotinic acetylcholine receptor Dα6 using the insecticide spinosad. Insect Biochemistry and Molecular Biology. 64. 116–127. 54 indexed citations

Chung, Henry, Adrian Boey, Chris Lumb, et al.. (2011). Induction of a detoxification gene in Drosophila melanogaster requires an interaction between tissue specific enhancers and a novel cis-regulatory element. Insect Biochemistry and Molecular Biology. 41(11). 863–871. 11 indexed citations

Willoughby, Lee, Henry Chung, Chris Lumb, et al.. (2006). A comparison of Drosophila melanogaster detoxification gene induction responses for six insecticides, caffeine and phenobarbital. Insect Biochemistry and Molecular Biology. 36(12). 934–942. 133 indexed citations

Chen, Zhenjun, Charles Robin, John A. Damiano, et al.. (2006). Positional cloning of a cyromazine resistance gene in Drosophila melanogaster. Insect Molecular Biology. 15(2). 181–186. 8 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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