Lin Shi

2.1k citations
51 papers · 1.5k · 1 hit paper · h-index 23

Impact in

Papers in

Lin Shi

49 papers receiving 1.5k citations

Lin Shi's Hit Papers

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer 2019 · 251 citations
2510+2+4Years since publication50100150200250

Peers

Lin Shi
Comparison fields: 5 of 108
  • Cancer Research 342
  • Horticulture 11
  • Molecular Biology 745
  • Oncology 257
  • Pulmonary and Respiratory Medicine 287
Replace Yi‐Hsiung Lin with:
Yi‐Hsiung Lin Taiwan
Kishore Guda United States
Jingdong Zhang China
Katarzyna Guzińska-Ustymowicz Poland
Hye Won Lee South Korea
Akira Mitoro Japan
Jianghong Wu China
Tomoyuki Nagai Japan
Chih‐Jung Chen Taiwan
Lin Shi relative to Yi‐Hsiung Lin Taiwan Yi‐Hsiung Lin's profile →
Citations per field
00.5×3.3×
Yi‐Hsiung Lin · 1×
Citations per year

Countries citing papers authored by Lin Shi

Since Specialization
Citations

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

Fields of papers citing papers by Lin Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lin Shi, 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 Lin Shi Line = papers co-authored together Lin Shi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer
Hit paper breakdown →
2019251
2 2017141
3 201579
4 201674
5 201669
6 200561
7 201754
8 201551
9 201645
10 201644
11 201641
12 201640
13 201536
14 202033
15 201733
16 201732
17 201830
18 201429
19 201929
20 201828

About Lin Shi

Lin Shi is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Cancer Research, Oncology and Rheumatology, having authored 51 papers that have together received 1.5k indexed citations. Recurring topics across this work include RNA modifications and cancer (10 papers), Bone and Dental Protein Studies (6 papers), MicroRNA in disease regulation (5 papers), Natural product bioactivities and synthesis (4 papers), RNA Research and Splicing (3 papers), Mesenchymal stem cell research (3 papers), Cancer-related molecular mechanisms research (3 papers) and Neonatal Respiratory Health Research (3 papers). The work is most often cited by research in Cancer Research (342 citations), Horticulture (11 citations), Molecular Biology (745 citations), Oncology (257 citations) and Pulmonary and Respiratory Medicine (287 citations). Lin Shi has collaborated with scholars based in China, United States and Greece. Frequent co-authors include Xiangdong Wang, Xiangdong Wang, Fen Yun, Chengshui Chen, Yongfeng Jia, Yulong Bao, Yongxia Chen, Xia Liu, Chen Chen and Li Wang. Their work appears in journals such as Clinical and Translational Medicine, Cell Biology and Toxicology, Cancer and Metastasis Reviews, Journal of Cellular and Molecular Medicine and Seminars in Cancer Biology.

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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