Fang Fang
- Cancer Research top 1%
- Cancer-related molecular mechanisms research 5
- Genetics top 1%
- Hemoglobinopathies and Related Disorders 7
- Molecular Biology top 2%
- Epigenetics and DNA Methylation 40
- RNA modifications and cancer 21
- Cancer-related gene regulation 12
- Genomics and Chromatin Dynamics 8
- Histone Deacetylase Inhibitors Research 6
- Reproductive Medicine top 5%
- Genetics top 5%
- Hemoglobinopathies and Related Disorders 7
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- Blood groups and transfusion 6
- Co-authors
- Kenneth P. NephewDaniela MateiAndrew D. SmithŞevin TurcanAdriana HeguyAndrew KaufmanAgnès VialeLuc G.T. Morris
- Partner nations
- United StatesChinaCanada
In The Last Decade
Fang Fang
74 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Cancer Research 1.3k
- Genetics 896
- Molecular Biology 3.1k
- Reproductive Medicine 182
- Genetics 562
Countries citing papers authored by Fang Fang
This map shows the geographic impact of Fang 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 Fang Fang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fang Fang more than expected).
Fields of papers citing papers by Fang Fang
This network shows the impact of papers produced by Fang 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 Fang Fang. The network helps show where Fang Fang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fang Fang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 8 | |
| 2 | 2023 | 4 | |
| 3 | 2023 | 3 | |
| 4 | 2021 | 47 | |
| 5 | 2021 | 57 | |
| 6 | 2020 | 17 | |
| 7 | 片親胚の単一細胞トランスクリプトーム解析はヒト着床前発生に対する親起源効果を明らかにする【JST・京大機械翻訳】 | 2019 | 11 |
| 8 | 2018 | 6 | |
| 9 | 2018 | 25 | |
| 10 | 2017 | 78 | |
| 11 | 2016 | 22 | |
| 12 | 2016 | 20 | |
| 13 | 2014 | 81 | |
| 14 | 2014 | 120 | |
| 15 | Epigenetic targeting of ovarian cancer stem cells | 2014 | 1 |
| 16 | 2012 | 302 | |
| 17 | 2010 | 139 | |
| 18 | Modern Logistics of the Innovative Enterprise Security Management Strategy | 2008 | 0 |
| 19 | In vitro differentiation of human adipose-derived mesenchymal stem cells into endothelial-like cells | 2006 | 3 |
| 20 | Assessing phylogenetic relationships of Lycium samples using RAPD and entropy theory | 2005 | 7 |
About Fang Fang
Fang Fang is a scholar working on Genetics, Hematology and Molecular Biology, having authored 80 papers that have together received 4.5k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (40 papers), RNA modifications and cancer (21 papers), Cancer-related gene regulation (12 papers), Genomics and Chromatin Dynamics (8 papers), Hemoglobinopathies and Related Disorders (7 papers), Histone Deacetylase Inhibitors Research (6 papers), Blood groups and transfusion (6 papers) and Cancer-related molecular mechanisms research (5 papers). The work is most often cited by research in Cancer Research (1.3k citations), Genetics (896 citations) and Molecular Biology (3.1k citations). Fang Fang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Kenneth P. Nephew, Daniela Matei, Andrew D. Smith, Şevin Turcan, Adriana Heguy, Andrew Kaufman, Agnès Viale, Luc G.T. Morris, Olga A. Guryanova and Emrullah Yilmaz. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.