Mee J. Kim

1.3k total citations
12 papers, 905 citations indexed

About

Mee J. Kim is a scholar working on Molecular Biology, Oncology and Surgery. According to data from OpenAlex, Mee J. Kim has authored 12 papers receiving a total of 905 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Oncology and 1 paper in Surgery. Recurrent topics in Mee J. Kim's work include Genomics and Chromatin Dynamics (5 papers), Drug Transport and Resistance Mechanisms (4 papers) and RNA Research and Splicing (4 papers). Mee J. Kim is often cited by papers focused on Genomics and Chromatin Dynamics (5 papers), Drug Transport and Resistance Mechanisms (4 papers) and RNA Research and Splicing (4 papers). Mee J. Kim collaborates with scholars based in United States, Russia and Israel. Mee J. Kim's co-authors include Nadav Ahituv, Robin P. Smith, Jay Shendure, Rupali P Patwardhan, Joseph B. Hiatt, Dalit May, Choli Lee, Daniela Witten, Gregory M. Cooper and L Pennacchio and has published in prestigious journals such as Nature Genetics, Nature Biotechnology and PLoS ONE.

In The Last Decade

Mee J. Kim

12 papers receiving 895 citations

Peers

Countries citing papers authored by Mee J. Kim

Since Specialization

Citations

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

Fields of papers citing papers by Mee J. Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mee J. Kim

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

All Works

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12 of 12 papers shown

#	Work	Indexed citations
1	Rare Variants in the ABCG2 Promoter Modulate In Vivo Activity 2018 ·Drug Metabolism and Disposition ·(unknown), Mee J. Kim, Robin P. Smith, Nadav Ahituv, Deanna L. Kroetz	8
2	ABCG2 regulatory single-nucleotide polymorphisms alter in vivo enhancer activity and expression 2017 ·Pharmacogenetics and Genomics ·(unknown), Mee J. Kim, Aparna Chhibber, Robin P. Smith, Nadav Ahituv, Deanna L. Kroetz	6
3	In Vivo Hepatic Enhancer Elements in the Human ABCG2 Locus 2016 ·Drug Metabolism and Disposition ·(unknown), Mee J. Kim, Robin P. Smith, Xiaomin Liang, Nadav Ahituv, Deanna L. Kroetz	5
4	Systematic Dissection of Coding Exons at Single Nucleotide Resolution Supports an Additional Role in Cell-Specific Transcriptional Regulation 2014 ·PLoS Genetics ·Ramon Y. Birnbaum, Rupali P Patwardhan, Mee J. Kim, Gregory M. Findlay, Beth Martin, Jingjing Zhao, Robert J.A. Bell, Robin P. Smith, Angel A. Ku, Jay Shendure, Nadav Ahituv	31
5	Genetic Association Study of Adiposity and Melanocortin-4 Receptor (MC4R) Common Variants: Replication and Functional Characterization of Non-Coding Regions 2014 ·PLoS ONE ·Daniel S. Evans, Melissa A. Calton, Mee J. Kim, Pui–Yan Kwok, Iva Miljkovic, Tamara Harris, Annemarie Koster, Yongmei Liu, Gregory J. Tranah, Nadav Ahituv, Wen-Chi Hsueh, Christian Vaisse	18
6	Sequence signatures extracted from proximal promoters can be used to predict distal enhancers 2013 ·Genome biology ·Leila Taher, Robin P. Smith, Mee J. Kim, Nadav Ahituv, Ivan Ovcharenko	26
7	Functional characterization ofSIM1-associated enhancers 2013 ·Human Molecular Genetics ·Mee J. Kim, Nir Oksenberg, Thomas J. Hoffmann, Christian Vaisse, Nadav Ahituv	9
8	The Hydrodynamic Tail Vein Assay as a Tool for the Study of Liver Promoters and Enhancers 2013 ·Methods in molecular biology ·Mee J. Kim, Nadav Ahituv	32
9	Massively parallel decoding of mammalian regulatory sequences supports a flexible organizational model 2013 ·Nature Genetics ·Robin P. Smith, Leila Taher, Rupali P Patwardhan, Mee J. Kim, Fumitaka Inoue, Jay Shendure, Ivan Ovcharenko, Nadav Ahituv	172
10	Coding exons function as tissue-specific enhancers of nearby genes 2012 ·Genome Research ·Ramon Y. Birnbaum, E. Josephine Clowney, (unknown), Mee J. Kim, Jingjing Zhao, Takayuki Yamanaka, (unknown), Shoa L. Clarke, Aaron M. Wenger, Loan Nguyen, Fiorella Gurrieri, David B. Everman, Charles E. Schwartz, Ohad S. Birk, Gill Bejerano, Stavros Lomvardas, Nadav Ahituv	166
11	Massively parallel functional dissection of mammalian enhancers in vivo 2012 ·Nature Biotechnology ·Rupali P Patwardhan, Joseph B. Hiatt, Daniela Witten, Mee J. Kim, Robin P. Smith, Dalit May, Choli Lee, (unknown), (unknown), Gregory M. Cooper, Nadav Ahituv, L Pennacchio, Jay Shendure	387
12	Identification and characterization of novel polymorphisms in the basal promoter of the human transporter, MATE1 2009 ·Pharmacogenetics and Genomics ·Ji Ha Choi, Sook Wah Yee, Mee J. Kim, Loan Nguyen, Jeong Ho Lee, Ji‐One Kang, Stephanie Hesselson, Richard A. Castro, Doug Stryke, Susan J. Johns, Pui–Yan Kwok, Thomas E. Ferrin, Min Goo Lee, (unknown), Nadav Ahituv, Kathleen M. Giacomini	45

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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