Linda Morrison

1.0k total citations
20 papers, 819 citations indexed

About

Linda Morrison is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Linda Morrison has authored 20 papers receiving a total of 819 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Genetics, 6 papers in Endocrinology, Diabetes and Metabolism and 5 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Linda Morrison's work include Animal Behavior and Reproduction (5 papers), Animal Ecology and Behavior Studies (3 papers) and Genetic Associations and Epidemiology (3 papers). Linda Morrison is often cited by papers focused on Animal Behavior and Reproduction (5 papers), Animal Ecology and Behavior Studies (3 papers) and Genetic Associations and Epidemiology (3 papers). Linda Morrison collaborates with scholars based in United States, Austria and United Kingdom. Linda Morrison's co-authors include Wayne K. Potts, Ryk Ward, Charles N. Rotimi, Richard Cooper, Dustin J. Penn, Petteri Ilmonen, Kristy Damjanovich, Duane A. Tewksbury, James S. Ruff and Shawn Meagher and has published in prestigious journals such as Circulation, Nature Communications and Journal of the American College of Cardiology.

In The Last Decade

Linda Morrison

20 papers receiving 800 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Linda Morrison United States 13 279 270 262 160 116 20 819
Tomás J. Acosta Japan 26 93 0.3× 124 0.5× 531 2.0× 240 1.5× 24 0.2× 78 1.8k
M. Piechotta Germany 21 31 0.1× 161 0.6× 310 1.2× 115 0.7× 20 0.2× 65 1.1k
G. Kann France 19 31 0.1× 213 0.8× 604 2.3× 281 1.8× 35 0.3× 58 1.6k
Ruan R. Daros Brazil 14 51 0.2× 111 0.4× 337 1.3× 63 0.4× 33 0.3× 37 974
F.A. Khan India 21 42 0.2× 44 0.2× 346 1.3× 242 1.5× 22 0.2× 93 1.2k
T. M. Nett United States 27 17 0.1× 428 1.6× 741 2.8× 195 1.2× 41 0.4× 60 2.4k
Missaka P.B. Wijayagunawardane Japan 19 43 0.2× 51 0.2× 241 0.9× 129 0.8× 14 0.1× 40 1.1k
Flávia L. Lopes Brazil 21 32 0.1× 62 0.2× 854 3.3× 442 2.8× 22 0.2× 62 2.0k
R. A. Dailey United States 30 28 0.1× 200 0.7× 1.3k 5.1× 118 0.7× 41 0.4× 83 2.5k
M. Mihm Ireland 24 83 0.3× 165 0.6× 1.2k 4.4× 267 1.7× 10 0.1× 42 2.5k

Countries citing papers authored by Linda Morrison

Since Specialization
Citations

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

Fields of papers citing papers by Linda Morrison

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linda Morrison

This figure shows the co-authorship network connecting the top 25 collaborators of Linda Morrison. A scholar is included among the top collaborators of Linda Morrison 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 Linda Morrison. Linda Morrison 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.
Ruff, James S., et al.. (2017). Mouse fitness measures reveal incomplete functional redundancy of Hox paralogous group 1 proteins. PLoS ONE. 12(4). e0174975–e0174975. 2 indexed citations
2.
Ruff, James S., Linda Morrison, Adam Nelson, et al.. (2017). Sexual selection constrains the body mass of male but not female mice. Ecology and Evolution. 7(4). 1271–1275. 9 indexed citations
3.
Ruff, James S., et al.. (2016). Rofecoxib-induced deleterious effects escape detection by organismal performance assays. Journal of Pharmaceutical Negative Results. 7(1). 4–4. 3 indexed citations
4.
Ruff, James S., et al.. (2016). Quantification of cerivastatin toxicity supports organismal performance assays as an effective tool during pharmaceutical safety assessment. Evolutionary Applications. 9(5). 685–696. 14 indexed citations
5.
Kubinak, Jason L., W. Zac Stephens, Ray Soto, et al.. (2015). MHC variation sculpts individualized microbial communities that control susceptibility to enteric infection. Nature Communications. 6(1). 8642–8642. 126 indexed citations
6.
Ruff, James S., et al.. (2015). Fitness Assays Reveal Incomplete Functional Redundancy of the HoxA1 and HoxB1 Paralogs of Mice. Genetics. 201(2). 727–736. 7 indexed citations
7.
Ruff, James S., et al.. (2014). Compared to Sucrose, Previous Consumption of Fructose and Glucose Monosaccharides Reduces Survival and Fitness of Female Mice. Journal of Nutrition. 145(3). 434–441. 19 indexed citations
8.
9.
Ruff, James S., et al.. (2013). Human-relevant levels of added sugar consumption increase female mortality and lower male fitness in mice. Nature Communications. 4(1). 2245–2245. 59 indexed citations
10.
Ilmonen, Petteri, Dustin J. Penn, Kristy Damjanovich, et al.. (2008). Experimental infection magnifies inbreeding depression in house mice. Journal of Evolutionary Biology. 21(3). 834–841. 55 indexed citations
11.
Ilmonen, Petteri, et al.. (2007). Major Histocompatibility Complex Heterozygosity Reduces Fitness in Experimentally Infected Mice. Genetics. 176(4). 2501–2508. 64 indexed citations
12.
McClelland, Erin E., Kristy Damjanovich, Kyle M. Gardner, et al.. (2004). Infection-dependent phenotypes in MHC-congenic mice are not due to MHC: can we trust congenic animals?. BMC Immunology. 5(1). 14–14. 10 indexed citations
13.
Carroll, Lara, Shawn Meagher, Linda Morrison, Dustin J. Penn, & Wayne K. Potts. (2004). FITNESS EFFECTS OF A SELFISH GENE (THE MUS T COMPLEX) ARE REVEALED IN AN ECOLOGICAL CONTEXT. Evolution. 58(6). 1318–1328. 57 indexed citations
14.
Carroll, Lara, Shawn Meagher, Linda Morrison, Dustin J. Penn, & Wayne K. Potts. (2004). FITNESS EFFECTS OF A SELFISH GENE (THE MUS T COMPLEX) ARE REVEALED IN AN ECOLOGICAL CONTEXT. Evolution. 58(6). 1318–1318. 3 indexed citations
15.
16.
Rotimi, Charles N., Richard Cooper, Olufemi J. Ogunbiyi, et al.. (1997). Hypertension, Serum Angiotensinogen, and Molecular Variants of the Angiotensinogen Gene Among Nigerians. Circulation. 95(10). 2348–2350. 86 indexed citations
17.
Forrester, Terrence, Norma McFarlane‐Anderson, Rainford Wilks, et al.. (1996). Angiotensinogen and blood pressure among blacks: findings from a community survey in Jamaica. Journal of Hypertension. 14(3). 315–321. 48 indexed citations
18.
Marshall, Hiram W., Linda Morrison, Lily Wu, et al.. (1994). Apolipoprotein polymorphisms fail to define risk of coronary artery disease. Results of a prospective, angiographically controlled study.. Circulation. 89(2). 567–577. 66 indexed citations
19.
Rotimi, Charles N., et al.. (1994). Angiotensinogen gene in human hypertension. Lack of an association of the 235T allele among African Americans.. Hypertension. 24(5). 591–594. 144 indexed citations
20.
Kapustka, Lawrence A., et al.. (1988). Dinitrogen Fixation in the Wet Meadows and Emergent Zones of Two Nebraska Sandhills Lakes. The American Midland Naturalist. 120(2). 398–398. 1 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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