Neil J. Ingham

2.9k total citations
48 papers, 1.2k citations indexed

About

Neil J. Ingham is a scholar working on Sensory Systems, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Neil J. Ingham has authored 48 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Sensory Systems, 20 papers in Molecular Biology and 20 papers in Cognitive Neuroscience. Recurrent topics in Neil J. Ingham's work include Hearing, Cochlea, Tinnitus, Genetics (33 papers), Hearing Loss and Rehabilitation (14 papers) and Neural dynamics and brain function (7 papers). Neil J. Ingham is often cited by papers focused on Hearing, Cochlea, Tinnitus, Genetics (33 papers), Hearing Loss and Rehabilitation (14 papers) and Neural dynamics and brain function (7 papers). Neil J. Ingham collaborates with scholars based in United Kingdom, United States and Germany. Neil J. Ingham's co-authors include Karen P. Steel, David McAlpine, Morag A. Lewis, Selina Pearson, Stefan Bleeck, Ian M. Winter, Walter Marcotti, Jacqueline K. White, Stuart L. Johnson and Stephanie Kuhn and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Neil J. Ingham

46 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Neil J. Ingham United Kingdom 22 608 521 403 137 136 48 1.2k
Brandon C. Cox United States 20 1.0k 1.7× 496 1.0× 389 1.0× 204 1.5× 131 1.0× 40 1.3k
Nicolas Grillet United States 19 974 1.6× 801 1.5× 286 0.7× 70 0.5× 254 1.9× 28 1.5k
Leona H. Gagnon United States 16 625 1.0× 493 0.9× 185 0.5× 52 0.4× 190 1.4× 28 1.1k
Daniel J. Jagger United Kingdom 27 1.0k 1.7× 778 1.5× 317 0.8× 51 0.4× 220 1.6× 56 1.6k
Hong-Bo Zhao United States 25 1.1k 1.7× 968 1.9× 336 0.8× 69 0.5× 204 1.5× 40 1.5k
Hainan Lang United States 26 1.3k 2.2× 484 0.9× 647 1.6× 128 0.9× 471 3.5× 47 1.8k
Nicolas Michalski France 19 952 1.6× 704 1.4× 301 0.7× 49 0.4× 324 2.4× 27 1.5k
Taha A. Jan United States 15 607 1.0× 540 1.0× 184 0.5× 165 1.2× 67 0.5× 37 1.1k
Henry J. Adler United States 18 707 1.2× 278 0.5× 285 0.7× 51 0.4× 144 1.1× 48 1.1k
Graham Nevill United Kingdom 14 1.2k 2.0× 624 1.2× 295 0.7× 139 1.0× 297 2.2× 17 1.5k

Countries citing papers authored by Neil J. Ingham

Since Specialization
Citations

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

Fields of papers citing papers by Neil J. Ingham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Neil J. Ingham

This figure shows the co-authorship network connecting the top 25 collaborators of Neil J. Ingham. A scholar is included among the top collaborators of Neil J. Ingham 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 Neil J. Ingham. Neil J. Ingham 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.
Ceriani, Federico, Joshua W. Giles, Neil J. Ingham, et al.. (2025). A machine-learning-based approach to predict early hallmarks of progressive hearing loss. Hearing Research. 464. 109328–109328.
2.
Ingham, Neil J., et al.. (2024). Two new mouse alleles of Ocm and Slc26a5. Hearing Research. 452. 109109–109109.
3.
Chen, Jing, et al.. (2024). A new mutation of Sgms1 causes gradual hearing loss associated with a reduced endocochlear potential. Hearing Research. 451. 109091–109091. 2 indexed citations
4.
Morin, Matías, et al.. (2023). Insights into the pathophysiology of DFNA44 hearing loss associated with CCDC50 frameshift variants. Disease Models & Mechanisms. 16(8). 1 indexed citations
5.
Ingham, Neil J., et al.. (2023). Reversal of an existing hearing loss by gene activation in Spns2 mutant mice. Proceedings of the National Academy of Sciences. 120(34). e2307355120–e2307355120. 3 indexed citations
6.
Lewis, Morag A., Neil J. Ingham, Jing Chen, et al.. (2022). Identification and characterisation of spontaneous mutations causing deafness from a targeted knockout programme. BMC Biology. 20(1). 67–67. 2 indexed citations
7.
Lewis, Morag A., et al.. (2020). Hearing impairment due to Mir183/96/182 mutations suggests both loss-of-function and gain-of-function effects. Disease Models & Mechanisms. 14(2). 18 indexed citations
8.
Ingham, Neil J., et al.. (2020). Functional analysis of candidate genes from genome-wide association studies of hearing. Hearing Research. 387. 107879–107879. 13 indexed citations
9.
Ingham, Neil J., et al.. (2020). Synaptojanin2 Mutation Causes Progressive High-frequency Hearing Loss in Mice. Frontiers in Cellular Neuroscience. 14. 561857–561857. 9 indexed citations
10.
11.
Ingham, Neil J., et al.. (2016). Enhancement of forward suppression begins in the ventral cochlear nucleus. Brain Research. 1639. 13–27. 12 indexed citations
12.
Ingham, Neil J., Selina Pearson, Morag A. Lewis, et al.. (2016). S1PR2 variants associated with auditory function in humans and endocochlear potential decline in mouse. Scientific Reports. 6(1). 28964–28964. 27 indexed citations
13.
Morozko, Eva L., Neil J. Ingham, Rashmi Chandra, et al.. (2014). ILDR1 null mice, a model of human deafness DFNB42, show structural aberrations of tricellular tight junctions and degeneration of auditory hair cells. Human Molecular Genetics. 24(3). 609–624. 45 indexed citations
14.
Norgett, Elizabeth E., Zoe Golder, Beatriz Lorente-Cánovas, et al.. (2012). Atp6v0a4 knockout mouse is a model of distal renal tubular acidosis with hearing loss, with additional extrarenal phenotype. Proceedings of the National Academy of Sciences. 109(34). 13775–13780. 49 indexed citations
15.
Hilton, Jennifer, Morag A. Lewis, M’hamed Grati, et al.. (2011). Exome sequencing identifies a missense mutation in Isl1associated with low penetrance otitis media in dearisch mice. Genome biology. 12(9). R90–R90. 21 indexed citations
16.
Scimemi, Pietro, Paromita Majumder, Romolo Daniele De Siati, et al.. (2010). The human deafness-associated connexin 30 T5M mutation causes mild hearing loss and reduces biochemical coupling among cochlear non-sensory cells in knock-in mice. Human Molecular Genetics. 19(24). 4759–4773. 58 indexed citations
17.
Bortolozzi, Mario, Francesca Di Leva, Martin Hrabě de Angelis, et al.. (2008). The Novel Mouse Mutation Oblivion Inactivates the PMCA2 Pump and Causes Progressive Hearing Loss. PLoS Genetics. 4(10). e1000238–e1000238. 58 indexed citations
18.
19.
Ingham, Neil J., et al.. (1995). Visual movement and pattern are important for the development of a map of auditory space in the guinea pig superior colliculus. Experimental Brain Research. 106(2). 257–64. 6 indexed citations
20.
Binns, K. E., et al.. (1994). The effects of monocular enucleation on the representation of auditory space in the superior colliculus of the guinea-pig. Brain Research. 636(2). 348–352. 10 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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