Peggy R. Biga

1.2k total citations
39 papers, 909 citations indexed

About

Peggy R. Biga is a scholar working on Molecular Biology, Aquatic Science and Genetics. According to data from OpenAlex, Peggy R. Biga has authored 39 papers receiving a total of 909 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 13 papers in Aquatic Science and 11 papers in Genetics. Recurrent topics in Peggy R. Biga's work include Muscle Physiology and Disorders (16 papers), Aquaculture Nutrition and Growth (13 papers) and Physiological and biochemical adaptations (9 papers). Peggy R. Biga is often cited by papers focused on Muscle Physiology and Disorders (16 papers), Aquaculture Nutrition and Growth (13 papers) and Physiological and biochemical adaptations (9 papers). Peggy R. Biga collaborates with scholars based in United States, France and Canada. Peggy R. Biga's co-authors include Frederick W. Goetz, Jean‐Charles Gabillard, Iban Seiliez, Ben M. Meyer, Kenneth D. Cain, Ronald W. Hardy, G. T. Schelling, Troy Ott, Kenneth Overturf and Pierre‐Yves Rescan and has published in prestigious journals such as PLoS ONE, Aquaculture and Journal of Experimental Biology.

In The Last Decade

Peggy R. Biga

38 papers receiving 891 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peggy R. Biga United States 18 378 290 260 206 130 39 909
Daniel García de la serrana Spain 20 402 1.1× 574 2.0× 332 1.3× 367 1.8× 306 2.4× 43 1.2k
Neil A. Richardson Australia 18 368 1.0× 355 1.2× 155 0.6× 204 1.0× 117 0.9× 41 988
Emilio J. Vélez Spain 19 168 0.4× 437 1.5× 110 0.4× 254 1.2× 187 1.4× 38 780
Lori A. Manzon Canada 11 182 0.5× 213 0.7× 134 0.5× 213 1.0× 81 0.6× 12 672
Angèle Tingaud‐Sequeira France 20 418 1.1× 181 0.6× 324 1.2× 186 0.9× 104 0.8× 32 1.2k
Niels A. Andersen Australia 18 297 0.8× 133 0.5× 277 1.1× 370 1.8× 155 1.2× 36 1.1k
Peng Hu China 19 715 1.9× 219 0.8× 200 0.8× 356 1.7× 326 2.5× 50 1.4k
Oriane Marchand France 9 392 1.0× 132 0.5× 223 0.9× 88 0.4× 91 0.7× 12 845
Huapu Chen China 25 301 0.8× 441 1.5× 538 2.1× 121 0.6× 259 2.0× 101 1.6k
Geir K. Totland Norway 20 369 1.0× 498 1.7× 141 0.5× 151 0.7× 194 1.5× 34 1.3k

Countries citing papers authored by Peggy R. Biga

Since Specialization
Citations

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

Fields of papers citing papers by Peggy R. Biga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peggy R. Biga. 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 Peggy R. Biga. The network helps show where Peggy R. Biga may publish in the future.

Co-authorship network of co-authors of Peggy R. Biga

This figure shows the co-authorship network connecting the top 25 collaborators of Peggy R. Biga. A scholar is included among the top collaborators of Peggy R. Biga 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 Peggy R. Biga. Peggy R. Biga 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.
Cleveland, Beth M., et al.. (2024). Remodeling of the epigenetic landscape in rainbow trout, Oncorhynchus mykiss, offspring in response to maternal choline intake. Comparative Biochemistry and Physiology Part D Genomics and Proteomics. 52. 101348–101348. 2 indexed citations
2.
Biga, Peggy R., Jingyue Duan, Tom Young, et al.. (2024). Hallmarks of aging: A user’s guide for comparative biologists. Ageing Research Reviews. 104. 102616–102616. 6 indexed citations
3.
Türkmen, Serhat, et al.. (2024). Direct actions of growth hormone in rainbow trout, Oncorhynchus mykiss, skeletal muscle cells in vitro. Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 297. 111725–111725. 2 indexed citations
4.
Cleveland, Beth M., et al.. (2024). Maternal dietary choline levels cause transcriptome shift due to genotype-by-diet interactions in rainbow trout (Oncorhynchus mykiss). Comparative Biochemistry and Physiology Part D Genomics and Proteomics. 49. 101193–101193. 1 indexed citations
5.
Riddle, Nicole C., Peggy R. Biga, Anne M. Bronikowski, et al.. (2023). Comparative analysis of animal lifespan. GeroScience. 46(1). 171–181. 6 indexed citations
6.
Bronikowski, Anne M., Richard P. Meisel, Peggy R. Biga, et al.. (2022). Sex‐specific aging in animals: Perspective and future directions. Aging Cell. 21(2). e13542–e13542. 51 indexed citations
7.
Biga, Peggy R., et al.. (2019). Teneurins and Teneurin C-Terminal Associated Peptide (TCAP) in Metabolism: What’s Known in Fish?. Frontiers in Neuroscience. 13. 177–177. 2 indexed citations
8.
Latimer, Mary N., et al.. (2018). Physiological and Molecular Mechanisms of Methionine Restriction. Frontiers in Endocrinology. 9. 217–217. 19 indexed citations
9.
Latimer, Mary N., Noah D. Sabin, Aurélie Le Cam, et al.. (2017). miR-210 expression is associated with methionine-induced differentiation of trout satellite cells. Journal of Experimental Biology. 220(Pt 16). 2932–2938. 19 indexed citations
10.
Biga, Peggy R., et al.. (2017). Distribution of H3K27me3, H3K9me3, and H3K4me3 along autophagy-related genes highly expressed in starved zebrafish myotubes. Biology Open. 6(11). 1720–1725. 15 indexed citations
11.
McCormick, Stephen D., et al.. (2017). A comparative evaluation of crowding stress on muscle HSP90 and myostatin expression in salmonids. Aquaculture. 483. 141–148. 15 indexed citations
12.
Biga, Peggy R., et al.. (2017). The validation of a sensitive, non-toxic in vivo metabolic assay applicable across zebrafish life stages. Comparative Biochemistry and Physiology Part C Toxicology & Pharmacology. 208. 29–37. 14 indexed citations
13.
14.
Seiliez, Iban, et al.. (2014). Preparation of Primary Myogenic Precursor Cell/Myoblast Cultures from Basal Vertebrate Lineages. Journal of Visualized Experiments. 24 indexed citations
15.
Remily, Ethan A., et al.. (2014). The effects of exogenous cortisol on myostatin transcription in rainbow trout, Oncorhynchus mykiss. Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 175. 57–63. 14 indexed citations
16.
Smith, Daniel L., et al.. (2013). Sarcopenia and piscines: the case for indeterminate-growing fish as unique genetic model organisms in aging and longevity research. Frontiers in Genetics. 4. 159–159. 20 indexed citations
17.
Goetz, Frederick W., et al.. (2013). Physiological differences between lean and siscowet lake trout morphotypes: Are these metabolotypes?. Canadian Journal of Fisheries and Aquatic Sciences. 71(3). 427–435. 27 indexed citations
18.
Gabillard, Jean‐Charles, Peggy R. Biga, Pierre‐Yves Rescan, & Iban Seiliez. (2013). Revisiting the paradigm of myostatin in vertebrates: Insights from fishes. General and Comparative Endocrinology. 194. 45–54. 67 indexed citations
19.
Biga, Peggy R., et al.. (2009). Growth hormone differentially regulates growth and growth-related gene expression in closely related fish species. Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 154(4). 465–473. 47 indexed citations
20.
Biga, Peggy R., G. T. Schelling, Ronald W. Hardy, et al.. (2003). The effects of recombinant bovine somatotropin (rbST) on tissue IGF-I, IGF-I receptor, and GH mRNA levels in rainbow trout, Oncorhynchus mykiss. General and Comparative Endocrinology. 135(3). 324–333. 87 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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