Shi-Lung Lin

3.6k citations
55 papers · 2.7k indexed · h-index 23
    • MicroRNA in disease regulation 27
    • RNA Interference and Gene Delivery 23
    • CRISPR and Genetic Engineering 18
    • RNA Research and Splicing 15
    • Pluripotent Stem Cells Research 10
    • RNA modifications and cancer 7
    • RNA and protein synthesis mechanisms 4
    • Molecular Biology Techniques and Applications 3

Shi-Lung Lin

55 papers receiving 2.6k citations

Peers

Shi-Lung Lin
Comparison fields: 5 of 113
  • Cancer Research 1.4k
  • Molecular Biology 2.3k
  • Oncology 199
  • Developmental Neuroscience 30
  • Aging 12
Replace Dana Ridzon with:
Dana Ridzon United States
Hun‐Way Hwang United States
Marcella Cesana Italy
Govindasamy Amuthan United States
Andrew M. Arsham United States
Yang Lin United States
Giuseppe Zardo Italy
Thomas Treiber Germany
Shi-Lung Lin relative to Dana Ridzon United States Dana Ridzon's profile →
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Citations per year

Countries citing papers authored by Shi-Lung Lin

Since Specialization
Citations

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

Fields of papers citing papers by Shi-Lung Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shi-Lung Lin. 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 Shi-Lung Lin. The network helps show where Shi-Lung Lin may publish in the future.

Co-authorship network

The 22 scholars most cited alongside Shi-Lung Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shi-Lung Lin Line = papers co-authored together Shi-Lung Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201813
2 201512
3 20148
4 201210
5 201231
6 20126
7 201221
8 20121
9 2010148
10 2010259
11 201029
12 2008327
13 200824
14 200745
15 200644
16 20066
17 200486
18 200369
19 20032
20 20031

About Shi-Lung Lin

Shi-Lung Lin is a scholar working on Cancer Research, Molecular Biology and Developmental Neuroscience, having authored 55 papers that have together received 2.7k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (27 papers), RNA Interference and Gene Delivery (23 papers), CRISPR and Genetic Engineering (18 papers), RNA Research and Splicing (15 papers), Pluripotent Stem Cells Research (10 papers), RNA modifications and cancer (7 papers), RNA and protein synthesis mechanisms (4 papers) and Molecular Biology Techniques and Applications (3 papers). The work is most often cited by research in Cancer Research (1.4k citations), Molecular Biology (2.3k citations) and Oncology (199 citations). Shi-Lung Lin has collaborated with scholars based in United States, Taiwan and India. Frequent co-authors include Shao‐Yao Ying, Donald C. Chang, David T. Wu, Chun‐Hung Lin, Ye‐Guang Chen, David Chen, Joseph D. Miller, Qiang Wang, Da-Yu Wu and Cheng‐Ming Chuong. Their work appears in journals such as Nucleic Acids Research, Cancer Research and Biochemical and Biophysical Research Communications.

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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