Mimi Fang

413 total citations
11 papers, 273 citations indexed

About

Mimi Fang is a scholar working on Molecular Biology, Oncology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Mimi Fang has authored 11 papers receiving a total of 273 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Oncology and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Mimi Fang's work include Acute Lymphoblastic Leukemia research (3 papers), Immune Cell Function and Interaction (2 papers) and RNA Research and Splicing (2 papers). Mimi Fang is often cited by papers focused on Acute Lymphoblastic Leukemia research (3 papers), Immune Cell Function and Interaction (2 papers) and RNA Research and Splicing (2 papers). Mimi Fang collaborates with scholars based in United States, France and Switzerland. Mimi Fang's co-authors include Miles A. Pufall, Barbara D. Boyan, Zvi Schwartz, Raul Salinas, Raluca Gordân, Hashim M. Al‐Hashimi, Maria A. Schumacher, Martin Kampmann, Tali E. Haran and Honglue Shi and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Blood.

In The Last Decade

Mimi Fang

11 papers receiving 273 citations

Peers

Mimi Fang

PHEOH

GENET

IMMUN

PFM

Christoph Wenger Germany

Christina Quensel Germany

Fiona Norris Australia

Jessica Weaver United States

Tadayoshi Uezato Japan

Kevin Morrow United States

Jia Ping Tan China

Kristina Vartanian United States

Doran Khamis United Kingdom

Yuanxin Ye China

Christoph Wenger Germany

Mimi Fang

296 ×2.0

29 ×0.7

PHEOH

38 ×1.1

GENET

24 ×0.8

IMMUN

15 ×0.5

PFM

Citations per year, relative to Mimi Fang Mimi Fang (= 1×) peers Christoph Wenger

Countries citing papers authored by Mimi Fang

Since Specialization

Citations

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

Fields of papers citing papers by Mimi Fang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mimi Fang

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

All Works

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11 of 11 papers shown

Rodríguez, Felipe, Philippe Cuniasse, Mei-ling A. Joiner, et al.. (2023). A De Novo Sequence Variant in Barrier-to-Autointegration Factor Is Associated with Dominant Motor Neuronopathy. Cells. 12(6). 847–847. 2 indexed citations

Fang, Mimi, et al.. (2023). PI3Kδ Inhibition Potentiates Glucocorticoids in B-lymphoblastic Leukemia by Decreasing Receptor Phosphorylation and Enhancing Gene Regulation. Cancers. 16(1). 143–143. 1 indexed citations

Afek, Ariel, Honglue Shi, Atul Rangadurai, et al.. (2020). DNA mismatches reveal conformational penalties in protein–DNA recognition. Nature. 587(7833). 291–296. 84 indexed citations

Fang, Mimi, Michael A. Thomas, Bonnie L. Hall, et al.. (2020). Deacylcortivazol-like pyrazole regioisomers reveal a more accommodating expanded binding pocket for the glucocorticoid receptor. RSC Medicinal Chemistry. 12(2). 203–212. 3 indexed citations

Pufall, Miles A., et al.. (2019). Glucocorticoids Regulate the Splicing Factor MBNL1, a Potential Control Point for B-Cell Specification. Blood. 134(Supplement_1). 2478–2478. 1 indexed citations

Poulard, Coralie, Hye Na Kim, Mimi Fang, et al.. (2019). Relapse-associated AURKB blunts the glucocorticoid sensitivity of B cell acute lymphoblastic leukemia. Proceedings of the National Academy of Sciences. 116(8). 3052–3061. 31 indexed citations

Michaelson, Jacob J., Min‐Kyoo Shin, Jin‐Young Koh, et al.. (2017). Neuronal PAS Domain Proteins 1 and 3 Are Master Regulators of Neuropsychiatric Risk Genes. Biological Psychiatry. 82(3). 213–223. 26 indexed citations

Fang, Mimi, Dawne N. Shelton, Hongxing Yang, et al.. (2017). Suppression of B-cell development genes is key to glucocorticoid efficacy in treatment of acute lymphoblastic leukemia. Blood. 129(22). 3000–3008. 42 indexed citations

Hanna‐Wakim, Rima, Linda L. Yasukawa, Phillip Sung, et al.. (2009). Age‐Related Increase in the Frequency of CD4⁺T Cells That Produce Interferon‐γ in Response to Staphylococcal Enterotoxin B during Childhood. The Journal of Infectious Diseases. 200(12). 1921–1927. 26 indexed citations

10.

Fang, Mimi, René Olivares‐Navarrete, Marco Wieland, et al.. (2009). The role of phospholipase D in osteoblast response to titanium surface microstructure. Journal of Biomedical Materials Research Part A. 93A(3). 897–909. 13 indexed citations

11.

Boyan, Barbara D., et al.. (2007). 1α,25(OH)2D3 is an autocrine regulator of extracellular matrix turnover and growth factor release via ERp60 activated matrix vesicle metalloproteinases. The Journal of Steroid Biochemistry and Molecular Biology. 103(3-5). 467–472. 44 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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