Mira Han

6.6k total citations · 1 hit paper
40 papers, 2.2k citations indexed

About

Mira Han is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Mira Han has authored 40 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 14 papers in Genetics and 11 papers in Plant Science. Recurrent topics in Mira Han's work include Genomics and Phylogenetic Studies (11 papers), Chromosomal and Genetic Variations (8 papers) and RNA and protein synthesis mechanisms (6 papers). Mira Han is often cited by papers focused on Genomics and Phylogenetic Studies (11 papers), Chromosomal and Genetic Variations (8 papers) and RNA and protein synthesis mechanisms (6 papers). Mira Han collaborates with scholars based in United States, South Korea and Ethiopia. Mira Han's co-authors include Matthew W. Hahn, Christian M. Zmasek, Jose Lugo-Martinez, Gregg W.C. Thomas, Jin Ho Chung, Casey McGrath, Jeffery P. Demuth, Claudio Casola, Richard P. Meisel and Dong Hun Lee and has published in prestigious journals such as Scientific Reports, Genetics and Biochemical and Biophysical Research Communications.

In The Last Decade

Mira Han

39 papers receiving 2.2k citations

Hit Papers

Estimating Gene Gain and Loss Rates in the Presence of Er... 2013 2026 2017 2021 2013 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mira Han United States 21 1.3k 677 619 290 255 40 2.2k
Harm Nijveen Netherlands 20 1.7k 1.4× 734 1.1× 1.4k 2.2× 265 0.9× 299 1.2× 54 3.7k
Diyan Li China 33 2.3k 1.8× 727 1.1× 335 0.5× 134 0.5× 180 0.7× 253 4.1k
Terence D. Murphy United States 20 1.9k 1.5× 495 0.7× 731 1.2× 131 0.5× 193 0.8× 41 2.7k
Wen Huang United States 37 1.2k 1.0× 1.7k 2.5× 418 0.7× 349 1.2× 281 1.1× 114 3.4k
Mitali Mukerji India 29 1.6k 1.2× 556 0.8× 559 0.9× 293 1.0× 278 1.1× 138 3.0k
Sonia Tarazona Spain 10 1.4k 1.1× 328 0.5× 489 0.8× 97 0.3× 153 0.6× 14 2.4k
Zhenglong Gu United States 29 2.9k 2.3× 923 1.4× 1.0k 1.7× 103 0.4× 136 0.5× 101 4.0k
Ravi K. Patel United States 18 2.2k 1.7× 562 0.8× 1.5k 2.4× 298 1.0× 371 1.5× 30 4.1k
Lisa Baird United States 28 1.4k 1.1× 700 1.0× 1.0k 1.7× 143 0.5× 106 0.4× 77 3.0k
Atsushi Kurabayashi Japan 29 1.1k 0.9× 502 0.7× 192 0.3× 191 0.7× 262 1.0× 73 1.9k

Countries citing papers authored by Mira Han

Since Specialization
Citations

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

Fields of papers citing papers by Mira Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mira Han

This figure shows the co-authorship network connecting the top 25 collaborators of Mira Han. A scholar is included among the top collaborators of Mira Han 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 Mira Han. Mira Han 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.
Chen, Xiangning, Mira Han, Vishwajit L. Nimgaonkar, et al.. (2025). Classification of schizophrenia, bipolar disorder and major depressive disorder with comorbid traits and deep learning algorithms. Schizophrenia. 11(1). 14–14. 3 indexed citations
2.
Davis, James, Lingkun Gu, Sylvan C. Baca, et al.. (2024). Disruption of the OsWRKY71 transcription factor gene results in early rice seed germination under normal and cold stress conditions. BMC Plant Biology. 24(1). 1090–1090. 4 indexed citations
5.
Wu, Qing, Fatma Nasoz, Jong-Yun Jung, et al.. (2021). Machine learning approaches for the prediction of bone mineral density by using genomic and phenotypic data of 5130 older men. Scientific Reports. 11(1). 4482–4482. 18 indexed citations
6.
Tillett, Richard, et al.. (2021). The essential but enigmatic regulatory role of HERVH in pluripotency. Trends in Genetics. 38(1). 12–21. 21 indexed citations
7.
Rushton, Paul J., et al.. (2021). Dynamic differential evolution schemes of WRKY transcription factors in domesticated and wild rice. Scientific Reports. 11(1). 14887–14887. 7 indexed citations
8.
Wu, Qing, et al.. (2020). Machine Learning Approaches for Fracture Risk Assessment: A Comparative Analysis of Genomic and Phenotypic Data in 5130 Older Men. Calcified Tissue International. 107(4). 353–361. 25 indexed citations
9.
Kim, Bong Soo, Chong Won Choi, Hyoseung Shin, et al.. (2019). Comparison of the Gut Microbiota of Centenarians in Longevity Villages of South Korea with Those of Other Age Groups. Journal of Microbiology and Biotechnology. 29(3). 429–440. 101 indexed citations
10.
Han, Mira, et al.. (2019). Paired-end mappability of transposable elements in the human genome. Mobile DNA. 10(1). 29–29. 31 indexed citations
11.
Han, Mira, et al.. (2017). UV irradiation to mouse skin decreases hippocampal neurogenesis and synaptic protein expression via HPA axis activation. Scientific Reports. 7(1). 15574–15574. 39 indexed citations
12.
Burke, Molly K., et al.. (2017). Genome-Wide Analysis of Starvation-Selected Drosophila melanogaster—A Genetic Model of Obesity. Molecular Biology and Evolution. 35(1). 50–65. 35 indexed citations
13.
Han, Mira, Hee Soon Shin, Soon‐Tae Lee, et al.. (2016). Lycopersicon esculentum Extract Enhances Cognitive Function and Hippocampal Neurogenesis in Aged Mice. Nutrients. 8(11). 679–679. 11 indexed citations
14.
Cheng, Yao, Jang-Hee Oh, Chi-Hyun Park, et al.. (2016). Vasoactive intestinal peptide stimulates melanogenesis in B16F10 mouse melanoma cells via CREB/MITF/tyrosinase signaling. Biochemical and Biophysical Research Communications. 477(3). 336–342. 23 indexed citations
15.
Graves, Joseph L., Kate L. Hertweck, Mark Phillips, et al.. (2016). Genomics of Parallel Experimental Evolution in Drosophila. Molecular Biology and Evolution. 34(4). msw282–msw282. 51 indexed citations
16.
Oh, Jang-Hee, Mira Han, Yao Cheng, et al.. (2015). UV irradiation-induced production of monoglycosylated biglycan through downregulation of xylosyltransferase 1 in cultured human dermal fibroblasts. Journal of Dermatological Science. 79(1). 20–29. 8 indexed citations
17.
Han, Mira, Gregg W.C. Thomas, Jose Lugo-Martinez, & Matthew W. Hahn. (2013). Estimating Gene Gain and Loss Rates in the Presence of Error in Genome Assembly and Annotation Using CAFE 3. Molecular Biology and Evolution. 30(8). 1987–1997. 584 indexed citations breakdown →
18.
Han, Mira. (2012). Characterizing gene movements between chromosomes in Drosophila. Fly. 6(2). 121–125. 1 indexed citations
19.
Han, Mira, Jeffery P. Demuth, Casey McGrath, Claudio Casola, & Matthew W. Hahn. (2009). Adaptive evolution of young gene duplicates in mammals. Genome Research. 19(5). 859–867. 141 indexed citations
20.
Hahn, Matthew W., et al.. (2007). Gene Family Evolution across 12 Drosophila Genomes. PLoS Genetics. 3(11). e197–e197. 266 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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