Pora Kim

3.3k total citations
53 papers, 1.2k citations indexed

About

Pora Kim is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Pora Kim has authored 53 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Molecular Biology, 14 papers in Cancer Research and 5 papers in Oncology. Recurrent topics in Pora Kim's work include RNA modifications and cancer (16 papers), Bioinformatics and Genomic Networks (10 papers) and Cancer Genomics and Diagnostics (9 papers). Pora Kim is often cited by papers focused on RNA modifications and cancer (16 papers), Bioinformatics and Genomic Networks (10 papers) and Cancer Genomics and Diagnostics (9 papers). Pora Kim collaborates with scholars based in United States, China and South Korea. Pora Kim's co-authors include Zhongming Zhao, Xiaobo Zhou, Junfei Zhao, Min Zhao, Ramkrishna Mitra, Mengyuan Yang, Sijia Wu, Peilin Jia, Jiajia Liu and Huifen Lu and has published in prestigious journals such as Nucleic Acids Research, BMC Bioinformatics and Acta Neuropathologica.

In The Last Decade

Pora Kim

50 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
Pora Kim United States 19 916 464 213 170 89 53 1.2k
Yari Ciani Italy 18 933 1.0× 482 1.0× 213 1.0× 394 2.3× 56 0.6× 27 1.4k
Zibin Jiang United States 11 577 0.6× 358 0.8× 140 0.7× 287 1.7× 79 0.9× 18 937
Xuefeng Fang China 17 666 0.7× 413 0.9× 159 0.7× 365 2.1× 82 0.9× 57 1.1k
Daniel Nicorici Finland 14 761 0.8× 461 1.0× 152 0.7× 187 1.1× 92 1.0× 28 1.1k
Fábio Pittella Silva Brazil 16 1.2k 1.4× 230 0.5× 145 0.7× 216 1.3× 85 1.0× 35 1.6k
Haixin Lei China 21 963 1.1× 405 0.9× 104 0.5× 239 1.4× 76 0.9× 28 1.3k
Hyunchul Jung South Korea 14 894 1.0× 385 0.8× 189 0.9× 357 2.1× 121 1.4× 26 1.3k
Anne Fassl Germany 15 579 0.6× 253 0.5× 206 1.0× 323 1.9× 50 0.6× 22 921
Robert Cornelison United States 18 770 0.8× 230 0.5× 115 0.5× 297 1.7× 100 1.1× 29 1.1k
David C. Corney United States 13 1.2k 1.3× 932 2.0× 212 1.0× 288 1.7× 81 0.9× 17 1.6k

Countries citing papers authored by Pora Kim

Since Specialization
Citations

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

Fields of papers citing papers by Pora Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pora Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Pora Kim. A scholar is included among the top collaborators of Pora Kim 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 Pora Kim. Pora Kim 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.
Yu, Huan, et al.. (2025). Spatial2GWAS: a database for linking spatial transcriptomic regions with GWAS traits. Nucleic Acids Research. 54(D1). D1309–D1320. 1 indexed citations
2.
Liu, Jiajia, Surendra S. Negi, Xiaobo Zhou, et al.. (2025). AllergenAI: a deep learning model predicting allergenicity based on protein sequence. BMC Bioinformatics. 26(1). 279–279.
3.
Kumar, Himansu & Pora Kim. (2024). Artificial intelligence in fusion protein three‐dimensional structure prediction: Review and perspective. Clinical and Translational Medicine. 14(8). e1789–e1789. 6 indexed citations
4.
Qian, Xiaohua, Hua Tan, Weiling Zhao, et al.. (2024). Radiogenomics-Based Risk Prediction of Glioblastoma Multiforme with Clinical Relevance. Genes. 15(6). 718–718. 3 indexed citations
5.
Wu, Sijia, Mengyuan Yang, Yanfei Wang, et al.. (2023). Genetic control of RNA editing in neurodegenerative disease. Briefings in Bioinformatics. 24(2). 6 indexed citations
6.
Huang, Kexin, Tiangang Wang, Qingxuan Li, et al.. (2023). AgeAnnoMO: a knowledgebase of multi-omics annotation for animal aging. Nucleic Acids Research. 52(D1). D822–D834. 3 indexed citations
7.
Kumar, Himansu, et al.. (2023). FusionNeoAntigen: a resource of fusion gene-specific neoantigens. Nucleic Acids Research. 52(D1). D1276–D1288. 9 indexed citations
8.
Wu, Sijia, et al.. (2023). The Potential Regulation of A-to-I RNA Editing on Genes in Parkinson’s Disease. Genes. 14(4). 919–919. 6 indexed citations
9.
Kumar, Himansu, et al.. (2023). FusionPDB: a knowledgebase of human fusion proteins. Nucleic Acids Research. 52(D1). D1289–D1304. 5 indexed citations
10.
Feng, Yuzhou, Lin Yang, Yanfei Wang, et al.. (2023). COV2Var, a function annotation database of SARS-CoV-2 genetic variation. Nucleic Acids Research. 52(D1). D701–D713. 9 indexed citations
11.
Wang, Yanfei, et al.. (2022). Phenotype-Genotype analysis of caucasian patients with high risk of osteoarthritis. Frontiers in Genetics. 13. 922658–922658. 2 indexed citations
12.
Kim, Pora, Hua Tan, Jiajia Liu, Himansu Kumar, & Xiaobo Zhou. (2022). FusionAI, a DNA-sequence-based deep learning protocol reduces the false positives of human fusion gene prediction. STAR Protocols. 3(1). 101185–101185. 2 indexed citations
13.
Kim, Pora, Hua Tan, Jiajia Liu, et al.. (2021). FusionGDB 2.0: fusion gene annotation updates aided by deep learning. Nucleic Acids Research. 50(D1). D1221–D1230. 22 indexed citations
14.
Tan, Hua, Pora Kim, Peiqing Sun, & Xiaobo Zhou. (2020). miRactDB characterizes miRNA–gene relation switch between normal and cancer tissues across pan-cancer. Briefings in Bioinformatics. 22(3). 12 indexed citations
15.
Phi, Ji Hoon, Ae Kyung Park, Semin Lee, et al.. (2018). Genomic analysis reveals secondary glioblastoma after radiotherapy in a subset of recurrent medulloblastomas. Acta Neuropathologica. 135(6). 939–953. 25 indexed citations
16.
Kim, Pora, Peilin Jia, & Zhongming Zhao. (2016). Kinase impact assessment in the landscape of fusion genes that retain kinase domains: a pan-cancer study. Briefings in Bioinformatics. 19(3). bbw127–bbw127. 25 indexed citations
17.
Zhao, Min, Pora Kim, Ramkrishna Mitra, Junfei Zhao, & Zhongming Zhao. (2015). TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes. Nucleic Acids Research. 44(D1). D1023–D1031. 262 indexed citations
18.
Jung, Yeonjoo, Pora Kim, Heeyoung Lee, et al.. (2015). VAMP2–NRG1 Fusion Gene is a Novel Oncogenic Driver of Non–Small-Cell Lung Adenocarcinoma. Journal of Thoracic Oncology. 10(7). 1107–1111. 27 indexed citations
19.
Kim, Pora, Feixiong Cheng, Junfei Zhao, & Zhongming Zhao. (2015). ccmGDB: a database for cancer cell metabolism genes. Nucleic Acids Research. 44(D1). D959–D968. 37 indexed citations
20.
Kim, Pora, et al.. (2005). Prediction of Mammalian MicroRNA Targets - Comparative Genomics Approach with Longer 3' UTR Databases. Genomics & Informatics. 3(3). 53–62. 2 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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