Nina Santi

1.6k total citations
23 papers, 1.2k citations indexed

About

Nina Santi is a scholar working on Immunology, Animal Science and Zoology and Aquatic Science. According to data from OpenAlex, Nina Santi has authored 23 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Immunology, 8 papers in Animal Science and Zoology and 7 papers in Aquatic Science. Recurrent topics in Nina Santi's work include Aquaculture disease management and microbiota (16 papers), Animal Virus Infections Studies (8 papers) and Aquaculture Nutrition and Growth (6 papers). Nina Santi is often cited by papers focused on Aquaculture disease management and microbiota (16 papers), Animal Virus Infections Studies (8 papers) and Aquaculture Nutrition and Growth (6 papers). Nina Santi collaborates with scholars based in Norway, France and United States. Nina Santi's co-authors include Øystein Evensen, Vikram N. Vakharia, Haichen Song, Thomas Moen, Nathalie Mitton, T.H.E. Meuwissen, John Violos, Aris Leivadeas, Sissel Kjøglum and Dimitrios Spatharakis and has published in prestigious journals such as PLoS ONE, Journal of Virology and Genetics.

In The Last Decade

Nina Santi

23 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
Nina Santi Norway 16 651 318 288 265 163 23 1.2k
Chao Pei China 19 736 1.1× 180 0.6× 97 0.3× 143 0.5× 74 0.5× 85 1.2k
Yang Ding China 21 658 1.0× 180 0.6× 129 0.4× 48 0.2× 77 0.5× 77 1.5k
Sissel Kjøglum Norway 15 640 1.0× 368 1.2× 512 1.8× 135 0.5× 17 0.1× 18 1.2k
Liqun Lu China 26 1.3k 2.0× 279 0.9× 180 0.6× 263 1.0× 12 0.1× 150 2.2k
Zilong Tan China 9 413 0.6× 291 0.9× 32 0.1× 27 0.1× 36 0.2× 20 758
Mehdi Sargolzaei Canada 35 78 0.1× 56 0.2× 3.6k 12.6× 582 2.2× 95 0.6× 123 4.6k
Shuling Yan China 23 482 0.7× 102 0.3× 165 0.6× 91 0.3× 69 0.4× 66 1.6k
Li Jiang China 28 129 0.2× 66 0.2× 1.3k 4.6× 110 0.4× 49 0.3× 134 2.8k
Nusrat Jahan Bangladesh 12 141 0.2× 89 0.3× 107 0.4× 111 0.4× 36 0.2× 38 651
Ricardo Pong‐Wong United Kingdom 29 117 0.2× 144 0.5× 3.2k 11.3× 308 1.2× 8 0.0× 105 4.2k

Countries citing papers authored by Nina Santi

Since Specialization
Citations

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

Fields of papers citing papers by Nina Santi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Santi

This figure shows the co-authorship network connecting the top 25 collaborators of Nina Santi. A scholar is included among the top collaborators of Nina Santi 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 Nina Santi. Nina Santi 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.
Violos, John, et al.. (2024). FeD-TST: Federated Temporal Sparse Transformers for QoS Prediction in Dynamic IoT Networks. IEEE Transactions on Network and Service Management. 22(2). 1055–1069. 3 indexed citations
2.
3.
Violos, John, et al.. (2022). Toward QoS Prediction Based on Temporal Transformers for IoT Applications. IEEE Transactions on Network and Service Management. 19(4). 4010–4027. 20 indexed citations
4.
Avgeris, Marios, Dimitrios Spatharakis, Nina Santi, et al.. (2021). Task offloading in Edge and Cloud Computing: A survey on mathematical, artificial intelligence and control theory solutions. Computer Networks. 195. 108177–108177. 183 indexed citations
5.
Jin, Yang, Rolf Erik Olsen, Keshuai Li, et al.. (2020). Comparative transcriptomics reveals domestication‐associated features of Atlantic salmon lipid metabolism. Molecular Ecology. 29(10). 1860–1872. 13 indexed citations
6.
Jin, Yang, Rolf Erik Olsen, Nina Santi, et al.. (2018). Transcriptional development of phospholipid and lipoprotein metabolism in different intestinal regions of Atlantic salmon (Salmo salar) fry. BMC Genomics. 19(1). 253–253. 10 indexed citations
7.
Jin, Yang, Rolf Erik Olsen, Nina Santi, et al.. (2018). A systemic study of lipid metabolism regulation in salmon fingerlings and early juveniles fed plant oil. British Journal Of Nutrition. 120(6). 653–664. 12 indexed citations
8.
Dettleff, Phillip, Thomas Moen, Nina Santi, & Victor D. Martínez. (2017). Transcriptomic analysis of spleen infected with infectious salmon anemia virus reveals distinct pattern of viral replication on resistant and susceptible Atlantic salmon ( Salmo salar ). Fish & Shellfish Immunology. 61. 187–193. 30 indexed citations
9.
Burgerhout, Erik, Maren Mommens, Hanne Johnsen, et al.. (2017). Genetic background and embryonic temperature affect DNA methylation and expression of myogenin and muscle development in Atlantic salmon (Salmo salar). PLoS ONE. 12(6). e0179918–e0179918. 67 indexed citations
10.
Munang’andu, Hetron Mweemba, et al.. (2016). A Systematic Approach towards Optimizing a Cohabitation Challenge Model for Infectious Pancreatic Necrosis Virus in Atlantic Salmon (Salmo salar L.). PLoS ONE. 11(2). e0148467–e0148467. 17 indexed citations
11.
Moen, Thomas, Jacob Torgersen, Nina Santi, et al.. (2015). Epithelial Cadherin Determines Resistance to Infectious Pancreatic Necrosis Virus in Atlantic Salmon. Genetics. 200(4). 1313–1326. 124 indexed citations
12.
Moen, Thomas, et al.. (2014). Genomic prediction in an admixed population of Atlantic salmon (Salmo salar). Frontiers in Genetics. 5. 402–402. 148 indexed citations
13.
14.
Munang’andu, Hetron Mweemba, et al.. (2013). Immunogenicity and Cross Protective Ability of the Central VP2 Amino Acids of Infectious Pancreatic Necrosis Virus in Atlantic Salmon (Salmo salar L.). PLoS ONE. 8(1). e54263–e54263. 25 indexed citations
15.
Marjara, Inderjit S., et al.. (2013). Stress-Induced Reversion to Virulence of Infectious Pancreatic Necrosis Virus in Naïve Fry of Atlantic Salmon (Salmo salar L.). PLoS ONE. 8(2). e54656–e54656. 35 indexed citations
16.
Santi, Nina, et al.. (2007). The interferon response is involved in nervous necrosis virus acute and persistent infection in zebrafish infection model. Molecular Immunology. 45(4). 1146–1152. 88 indexed citations
17.
Santi, Nina, Hilde Sindre, Haichen Song, et al.. (2005). Infectious pancreatic necrosis virus induces apoptosis in vitro and in vivo independent of VP5 expression. Virology. 342(1). 13–25. 45 indexed citations
18.
Song, Haichen, Nina Santi, Øystein Evensen, & Vikram N. Vakharia. (2005). Molecular Determinants of Infectious Pancreatic Necrosis Virus Virulence and Cell Culture Adaptation. Journal of Virology. 79(16). 10289–10299. 100 indexed citations
19.
Santi, Nina, Haichen Song, Vikram N. Vakharia, & Øystein Evensen. (2005). Infectious Pancreatic Necrosis Virus VP5 Is Dispensable for Virulence and Persistence. Journal of Virology. 79(14). 9206–9216. 64 indexed citations
20.
Santi, Nina, Vikram N. Vakharia, & Øystein Evensen. (2004). Identification of putative motifs involved in the virulence of infectious pancreatic necrosis virus. Virology. 322(1). 31–40. 110 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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