Li‐Fang Chu

3.2k citations
28 papers · 2.0k indexed · 1 hit paper · h-index 16
Topics
Single-cell and spatial transcriptomics (12 papers)Pluripotent Stem Cells Research (7 papers)CRISPR and Genetic Engineering (6 papers)

In The Last Decade

Li‐Fang Chu

28 papers receiving 2.0k citations

Hit Papers

Efficient genome engineering in human pluripotent stem ce...20132026201720212013100200300400500

Peers

Li‐Fang Chu
Comparison fields: 5 of 105
  • Molecular Biology 1.8k
  • Cancer Research 267
  • Genetics 187
  • Biophysics 117
  • Plant Science 111
Replace Sourav Choudhury with:
Sourav Choudhury India
Jonathan Y. Hsu United States
Kendell Clement United States
Jaime A. Rivera‐Pérez United States
Yonatan Stelzer Israel
Jonathan D. Chesnut United States
Eswar Prasad R. Iyer United States
Martin Teichmann France
Jim Kent United States
Li‐Fang Chu relative to Sourav Choudhury India Sourav Choudhury's profile →
Citations per field
00.5×5.4×
Sourav Choudhury · 1×
Citations per year

Countries citing papers authored by Li‐Fang Chu

Since Specialization
Citations

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

Fields of papers citing papers by Li‐Fang Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li‐Fang Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Li‐Fang Chu. A scholar is included among the top collaborators of Li‐Fang Chu 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 Li‐Fang Chu. Li‐Fang Chu 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
#WorkIndexed citations
1 2
2 2
3 54
4 5
5 4
6 2
7 47
8 8
9 25
10 105
11 190
12 46
13 14
14 39
15 116
16 21
17 105
18 159
19 10
20 29

About Li‐Fang Chu

Li‐Fang Chu is a scholar working on Molecular Biology, Urology and Cancer Research, having authored 28 papers that have together received 2.0k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (12 papers), Pluripotent Stem Cells Research (7 papers) and CRISPR and Genetic Engineering (6 papers). The work is most often cited by research in Business and International Management (82 citations), Aging (63 citations) and Molecular Biology (1.8k citations). Li‐Fang Chu has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include James A. Thomson, Ron Stewart, Zhonggang Hou, Christina Kendziorski, Ning Leng, Sara E. Howden, Yan Zhang, Nicholas E. Propson, Erik J. Sontheimer and Michael A. Newton. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

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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