Kim H. Brown

985 total citations
27 papers, 715 citations indexed

About

Kim H. Brown is a scholar working on Genetics, Molecular Biology and Physiology. According to data from OpenAlex, Kim H. Brown has authored 27 papers receiving a total of 715 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Genetics, 12 papers in Molecular Biology and 7 papers in Physiology. Recurrent topics in Kim H. Brown's work include Reproductive biology and impacts on aquatic species (7 papers), Fish Ecology and Management Studies (6 papers) and Genetic diversity and population structure (6 papers). Kim H. Brown is often cited by papers focused on Reproductive biology and impacts on aquatic species (7 papers), Fish Ecology and Management Studies (6 papers) and Genetic diversity and population structure (6 papers). Kim H. Brown collaborates with scholars based in United States, Singapore and Finland. Kim H. Brown's co-authors include Gary H. Thorgaard, James J. Nagler, Ruth B. Phillips, Irvin R. Schultz, Robert E. Drew, Krista M. Nichols, Paul Wheeler, Kimberly P. Dobrinski, Charles Lee and Roy G. Danzmann and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Oncogene and Scientific Reports.

In The Last Decade

Kim H. Brown

26 papers receiving 696 citations

Peers

Kim H. Brown

GENET

NLC

PHYSI

Thaovi Nguyen France

Lene Kleppe Norway

Noèlia Díaz Spain

Carlos Frederico Ceccon Lanes Brazil

Allyse Ferrara United States

Rute S.T. Martins Portugal

Colin McGowan Canada

Yusuke Takehana Japan

Rajini Sreenivasan Australia

Jérôme Montfort France

Thaovi Nguyen France

Kim H. Brown

266 ×0.7

GENET

149 ×0.6

71 ×0.5

NLC

170 ×1.3

253 ×2.2

PHYSI

Citations per year, relative to Kim H. Brown Kim H. Brown (= 1×) peers Thaovi Nguyen

Countries citing papers authored by Kim H. Brown

Since Specialization

Citations

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

Fields of papers citing papers by Kim H. Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kim H. 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 Kim H. Brown. The network helps show where Kim H. Brown may publish in the future.

Co-authorship network of co-authors of Kim H. Brown

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

All Works

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20 of 20 papers shown

Wilson, Charles B., et al.. (2018). An Interrogation of Shared and Unique Copy Number Variants Across Genetically Distinct Zebrafish Strains. Zebrafish. 16(1). 29–36. 4 indexed citations

Arumilli, Meharji, et al.. (2018). Assembly and Analysis of Unmapped Genome Sequence Reads Reveal Novel Sequence and Variation in Dogs. Scientific Reports. 8(1). 10862–10862. 4 indexed citations

Brown, Kim H., et al.. (2018). Baseline mRNA expression differs widely between common laboratory strains of zebrafish. Scientific Reports. 8(1). 4780–4780. 21 indexed citations

Brown, Kim H., et al.. (2016). Pseudo- De Novo Assembly and Analysis of Unmapped Genome Sequence Reads in Wild Zebrafish Reveal Novel Gene Content. Zebrafish. 13(2). 95–102. 12 indexed citations

Brown, Kim H., et al.. (2016). Anchored pseudo-de novo assembly of human genomes identifies extensive sequence variation from unmapped sequence reads. Human Genetics. 135(7). 727–740. 5 indexed citations

Phillips, Ruth B., et al.. (2015). Comparative Analysis of the Shared Sex-Determination Region (SDR) among Salmonid Fishes. Genome Biology and Evolution. 7(7). 1972–1987. 46 indexed citations

Brown, Kim H., et al.. (2014). Phenotypic Variation in the Model Organism, Danio Rerio. PDXScholar (Portland State University).

Chen, Eleanor Y., Kimberly P. Dobrinski, Kim H. Brown, et al.. (2013). Cross-Species Array Comparative Genomic Hybridization Identifies Novel Oncogenic Events in Zebrafish and Human Embryonal Rhabdomyosarcoma. PLoS Genetics. 9(8). e1003727–e1003727. 27 indexed citations

Rudner, Lynnie A., Kim H. Brown, Kimberly P. Dobrinski, et al.. (2011). Shared acquired genomic changes in zebrafish and human T-ALL. Oncogene. 30(41). 4289–4296. 35 indexed citations

10.

Dobrinski, Kimberly P., Kim H. Brown, Jennifer L. Freeman, & Charles Lee. (2011). Molecular Cytogenetic Methodologies and a BAC Probe Panel Resource for Genomic Analyses in the Zebrafish. Methods in cell biology. 104. 237–257. 5 indexed citations

11.

Brown, Kim H., Kimberly P. Dobrinski, Arthur S. Lee, et al.. (2011). Extensive genetic diversity and substructuring among zebrafish strains revealed through copy number variant analysis. Proceedings of the National Academy of Sciences. 109(2). 529–534. 93 indexed citations

12.

Brown, Kim H., Irvin R. Schultz, & James J. Nagler. (2008). Lack of a heritable reproductive defect in the offspring of male rainbow trout exposed to the environmental estrogen 17α-ethynylestradiol. Aquatic Toxicology. 91(1). 71–74. 11 indexed citations

13.

Brown, Kim H., et al.. (2008). Effect of parental exposure to trenbolone and the brominated flame retardant BDE-47 on fertility in rainbow trout (Oncorhynchus mykiss). Marine Environmental Research. 66(1). 47–49. 10 indexed citations

14.

Brown, Kim H., Irvin R. Schultz, J.G. Cloud, & James J. Nagler. (2008). Aneuploid sperm formation in rainbow trout exposed to the environmental estrogen 17α-ethynylestradiol. Proceedings of the National Academy of Sciences. 105(50). 19786–19791. 28 indexed citations

15.

Brown, Kim H., Irvin R. Schultz, & James J. Nagler. (2007). Reduced embryonic survival in rainbow trout resulting from paternal exposure to the environmental estrogen 17α-ethynylestradiol during late sexual maturation. Reproduction. 134(5). 659–666. 37 indexed citations

16.

Brown, Kim H., et al.. (2006). Use of androgenesis for estimating maternal and mitochondrial genome effects on development and oxygen consumption in rainbow trout, Oncorhynchus mykiss. Comparative Biochemistry and Physiology Part B Biochemistry and Molecular Biology. 143(4). 415–421. 23 indexed citations

17.

Brown, Kim H., Robert E. Drew, Lee A. Weber, & Gary H. Thorgaard. (2006). Intraspecific variation in the rainbow trout mitochondrial DNA genome. Comparative Biochemistry and Physiology Part D Genomics and Proteomics. 1(2). 219–226. 15 indexed citations

18.

Brown, Kim H., et al.. (2004). Equivalent Survival and Different Development Rates in Reciprocal Apache Trout × Rainbow Trout Hybrids. Copeia. 2004(2). 378–382. 4 indexed citations

19.

Nichols, Krista M., William P. Young, Roy G. Danzmann, et al.. (2003). A consolidated linkage map for rainbow trout (Oncorhynchus mykiss). Animal Genetics. 34(2). 102–115. 173 indexed citations

20.

Brown, Kim H. & Gary H. Thorgaard. (2002). Mitochondrial and nuclear inheritance in an androgenetic line of rainbow trout, Oncorhynchus mykiss. Aquaculture. 204(3-4). 323–335. 23 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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