Steve D.M. Brown

970 total citations
8 papers, 522 citations indexed

About

Steve D.M. Brown is a scholar working on Molecular Biology, Sensory Systems and Cell Biology. According to data from OpenAlex, Steve D.M. Brown has authored 8 papers receiving a total of 522 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Sensory Systems and 1 paper in Cell Biology. Recurrent topics in Steve D.M. Brown's work include Hearing, Cochlea, Tinnitus, Genetics (4 papers), Biomedical Text Mining and Ontologies (3 papers) and Bioinformatics and Genomic Networks (2 papers). Steve D.M. Brown is often cited by papers focused on Hearing, Cochlea, Tinnitus, Genetics (4 papers), Biomedical Text Mining and Ontologies (3 papers) and Bioinformatics and Genomic Networks (2 papers). Steve D.M. Brown collaborates with scholars based in United Kingdom, United States and Finland. Steve D.M. Brown's co-authors include John Kendrick‐Jones, Karen P. Steel, Philomena Mburu, M. Cope, Hilary Gates, John M. Hancock, Ann‐Marie Mallon, Tarja Joensuu, Eeva-Marja Sankila and Gonzalo Blanco and has published in prestigious journals such as Nucleic Acids Research, Nature Genetics and Genome Research.

In The Last Decade

Steve D.M. Brown

8 papers receiving 515 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Steve D.M. Brown United Kingdom 7 354 316 106 68 63 8 522
Atteeq U. Rehman United States 12 373 1.1× 315 1.0× 118 1.1× 93 1.4× 65 1.0× 19 588
Shaheen Khan United States 7 330 0.9× 294 0.9× 83 0.8× 88 1.3× 46 0.7× 10 550
Sonia M. Rocha-Sanchez United States 15 390 1.1× 325 1.0× 58 0.5× 79 1.2× 67 1.1× 23 751
Sigrid Wayne United States 11 344 1.0× 364 1.2× 115 1.1× 55 0.8× 74 1.2× 19 543
Sébastien Chardenoux France 8 308 0.9× 383 1.2× 120 1.1× 47 0.7× 75 1.2× 9 521
Asadollah Aghaie France 13 641 1.8× 403 1.3× 153 1.4× 76 1.1× 97 1.5× 16 904
Alice Emptoz France 6 316 0.9× 430 1.4× 90 0.8× 55 0.8× 132 2.1× 6 545
Elise Pepermans France 9 334 0.9× 287 0.9× 75 0.7× 43 0.6× 48 0.8× 12 486
Meghan C. Drummond United States 8 242 0.7× 271 0.9× 72 0.7× 48 0.7× 61 1.0× 10 409
Karina Lezirovitz Brazil 12 245 0.7× 300 0.9× 111 1.0× 58 0.9× 77 1.2× 39 503

Countries citing papers authored by Steve D.M. Brown

Since Specialization
Citations

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

Fields of papers citing papers by Steve D.M. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Steve D.M. Brown

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

All Works

8 of 8 papers shown
1.
Giese, Arnaud P. J., Andrew Parker, Steve D.M. Brown, et al.. (2025). CIB2 function is distinct from that of whirlin in the organization of sterocilia architecture. Disease Models & Mechanisms. 18(3). 1 indexed citations
2.
Parker, Andrew, Sally H. Cross, Ian J. Jackson, et al.. (2015). The goya mutation identifies distinct novel roles for MAP3K1 in cochlear sensory hair cell development and survival. Disease Models & Mechanisms. 8(12). 1555–68. 11 indexed citations
3.
Gates, Hilary, Ann‐Marie Mallon, & Steve D.M. Brown. (2010). High-throughput mouse phenotyping. Methods. 53(4). 394–404. 24 indexed citations
4.
Blake, Andrew, Simon Greenaway, Amanda R. Pickard, et al.. (2009). MouseBook: an integrated portal of mouse resources. Nucleic Acids Research. 38(suppl_1). D593–D599. 14 indexed citations
5.
Brown, Steve D.M., John M. Hancock, & Hilary Gates. (2006). Understanding Mammalian Genetic Systems: The Challenge of Phenotyping in the Mouse. PLoS Genetics. 2(8). e118–e118. 65 indexed citations
6.
Mallon, Ann‐Marie, Laurens Wilming, James Gilbert, et al.. (2004). Organization and Evolution of a Gene-Rich Region of the Mouse Genome: A 12.7-Mb Region Deleted in the Del(13)Svea36H Mouse. Genome Research. 14(10a). 1888–1901. 23 indexed citations
7.
Mburu, Philomena, et al.. (1997). Mutations in the myosin VIIA gene cause non-syndromic recessive deafness. Nature Genetics. 16(2). 188–190. 359 indexed citations
8.
Joensuu, Tarja, Gonzalo Blanco, Leenamaija Pakarinen, et al.. (1996). Refined Mapping of the Usher Syndrome Type III Locus on Chromosome 3, Exclusion of Candidate Genes, and Identification of the Putative Mouse Homologous Region. Genomics. 38(3). 255–263. 25 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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