Seong-In Lim

618 total citations
42 papers, 493 citations indexed

About

Seong-In Lim is a scholar working on Infectious Diseases, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, Seong-In Lim has authored 42 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Infectious Diseases, 20 papers in Agronomy and Crop Science and 14 papers in Animal Science and Zoology. Recurrent topics in Seong-In Lim's work include Animal Disease Management and Epidemiology (20 papers), Viral gastroenteritis research and epidemiology (16 papers) and Animal Virus Infections Studies (14 papers). Seong-In Lim is often cited by papers focused on Animal Disease Management and Epidemiology (20 papers), Viral gastroenteritis research and epidemiology (16 papers) and Animal Virus Infections Studies (14 papers). Seong-In Lim collaborates with scholars based in South Korea, Vietnam and United States. Seong-In Lim's co-authors include Dong-Jun An, Jae‐Young Song, Yong Kwan Kim, Hye-Young Jeoung, In‐Soo Cho, Bang‐Hun Hyun, Joong‐Bok Lee, SeEun Choe, Daesub Song and Ki-Sun Kim and has published in prestigious journals such as Journal of Virology, Biochemical and Biophysical Research Communications and Vaccine.

In The Last Decade

Seong-In Lim

42 papers receiving 482 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seong-In Lim South Korea	14	252	237	197	141	117	42	493
Danielle Gava Brazil	14	235 0.9×	242 1.0×	251 1.3×	149 1.1×	81 0.7×	50	546
Apisit Kittawornrat United States	16	371 1.5×	428 1.8×	223 1.1×	201 1.4×	83 0.7×	22	662
Feng-Xue Wang China	15	326 1.3×	322 1.4×	111 0.6×	298 2.1×	78 0.7×	43	626
Chris Rademacher United States	10	280 1.1×	290 1.2×	260 1.3×	131 0.9×	107 0.9×	24	528
Melanie Prarat United States	11	132 0.5×	135 0.6×	178 0.9×	95 0.7×	113 1.0×	15	439
Masoud Reza Seyfi Abad Shapouri Iran	9	275 1.1×	202 0.9×	62 0.3×	87 0.6×	66 0.6×	66	395
Aaron Singrey United States	13	484 1.9×	455 1.9×	262 1.3×	263 1.9×	56 0.5×	20	735
Mudasser Habib Pakistan	11	189 0.8×	165 0.7×	62 0.3×	149 1.1×	72 0.6×	33	438
Shinobu Tsuchiaka Japan	13	259 1.0×	211 0.9×	105 0.5×	49 0.3×	122 1.0×	27	442
Pierfrancesco Pinto Italy	13	350 1.4×	245 1.0×	122 0.6×	162 1.1×	138 1.2×	20	468

Countries citing papers authored by Seong-In Lim

Since Specialization

Citations

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

Fields of papers citing papers by Seong-In Lim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seong-In Lim. 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 Seong-In Lim. The network helps show where Seong-In Lim may publish in the future.

Co-authorship network of co-authors of Seong-In Lim

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Lim, Seong-In, Minji Kim, Mijung Kwon, et al.. (2023). Assessment of Equine Influenza Virus Status in the Republic of Korea from 2020 to 2022. Viruses. 15(10). 2135–2135. 3 indexed citations

Park, Gyunam, Jihye Shin, SeEun Choe, et al.. (2023). Safety and Immunogenicity of Chimeric Pestivirus KD26_E2LOM in Piglets and Calves. Vaccines. 11(10). 1622–1622. 2 indexed citations

Lim, Seong-In, Mijung Kwon, SeEun Choe, et al.. (2023). First Detection of Influenza D Virus Infection in Cattle and Pigs in the Republic of Korea. Microorganisms. 11(7). 1751–1751. 7 indexed citations

Choe, SeEun, Gyunam Park, Ki-Sun Kim, et al.. (2023). Efficacy of an orally administered classical swine fever live marker vaccine (Flc-LOM-BErns strain) in pigs. Vaccine. 41(49). 7377–7386. 1 indexed citations

Jeong, So Yeon, et al.. (2021). Effects of natural killer cell-derived exosomes in canine mammary tumor model. 45(3). 129–137. 1 indexed citations

Lim, Seong-In, SeEun Choe, Ki-Sun Kim, et al.. (2019). Assessment of the efficacy of an attenuated live marker classical swine fever vaccine (Flc-LOM-BErns) in pregnant sows. Vaccine. 37(27). 3598–3604. 21 indexed citations

An, Dong-Jun, Seong-In Lim, SeEun Choe, et al.. (2018). Evolutionary dynamics of classical swine fever virus in South Korea: 1987–2017. Veterinary Microbiology. 225. 79–88. 16 indexed citations

Kim, Yong Kwan, et al.. (2016). Molecular characterization of the spike and ORF3 genes of porcine epidemic diarrhea virus in the Philippines. Archives of Virology. 161(5). 1323–1328. 17 indexed citations

Lim, Seong-In, Jae‐Young Song, Bang‐Hun Hyun, et al.. (2016). Safety of classical swine fever virus vaccine strain LOM in pregnant sows and their offspring. Vaccine. 34(17). 2021–2026. 19 indexed citations

10.

Kim, Yong Kwan, et al.. (2015). A novel assay for detecting canine parvovirus using a quartz crystal microbalance biosensor. Journal of Virological Methods. 219. 23–27. 13 indexed citations

11.

Jeoung, Hye-Young, Seong-In Lim, Yong Kwan Kim, et al.. (2015). Serological prevalence of viral agents that induce reproductive failure in South Korean wild boar. BMC Veterinary Research. 11(1). 78–78. 18 indexed citations

12.

Kim, Yong Kwan, Seong-In Lim, In‐Soo Cho, et al.. (2015). A novel diagnostic approach to detecting porcine epidemic diarrhea virus: The lateral immunochromatography assay. Journal of Virological Methods. 225. 4–8. 22 indexed citations

13.

Lim, Seong-In, Hye-Young Jeoung, Yong Kwan Kim, et al.. (2014). Serological evidence for influenza virus infection in Korean wild boars. Journal of Veterinary Medical Science. 77(1). 109–112. 9 indexed citations

14.

An, Dong-Jun, et al.. (2014). Genetic characterization of porcine circovirus type 2 in the Korean wild boar population. Veterinary Microbiology. 169(3-4). 147–153. 8 indexed citations

15.

Kim, Yong Kwan, et al.. (2014). The CSFV DNAChip: A novel diagnostic assay for classical swine fever virus. Journal of Virological Methods. 204. 44–48. 1 indexed citations

16.

Lee, Ki‐Eun, Seong-In Lim, Hwan‐Won Choi, et al.. (2014). Plasmid-mediated AmpC β-lactamase (CMY-2) gene in Salmonella typhimurium isolated from diarrheic pigs in South Korea. BMC Research Notes. 7(1). 329–329. 10 indexed citations

17.

Lim, Seong-In, et al.. (2014). Molecular evolution of kobuviruses in cats. Archives of Virology. 160(2). 537–541. 5 indexed citations

18.

Jeoung, Hye-Young, Seong-In Lim, Jae‐Young Song, et al.. (2013). A novel canine influenza H3N2 virus isolated from cats in an animal shelter. Veterinary Microbiology. 165(3-4). 281–286. 58 indexed citations

19.

Lim, Seong-In, et al.. (2013). Genome Sequence of Bovine Viral Diarrhea Virus Strain 10JJ-SKR, Belonging to Genotype 1d. Genome Announcements. 1(4). 7 indexed citations

20.

Pham, Dinh‐Chuong, Seong-In Lim, Sukchan Lee, et al.. (2010). An RNA-hydrolyzing recombinant antibody exhibits an antiviral activity against classical swine fever virus. Biochemical and Biophysical Research Communications. 395(4). 484–489. 30 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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