Xinxin Si

1.4k citations
48 papers · 1.1k · h-index 13

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • RNA modifications and cancer
    • Circular RNAs in diseases
    • RNA Research and Splicing
    • Epigenetics and DNA Methylation

Papers in

Xinxin Si

42 papers receiving 1.1k citations

Peers

Xinxin Si
Comparison fields: 5 of 93
  • Cancer Research 569
  • Molecular Biology 716
  • Endocrinology 32
  • Pharmacology 51
  • Molecular Medicine 14
Replace Ye Wang with:
Ye Wang China
Yicheng Zhao China
Tian Luan China
Dong Dong China
Nameun Kim South Korea
Feng Ren China
Alessia Stornetta United States
Xinxin Si relative to Ye Wang China Ye Wang's profile →
Citations per field
00.5×3.3×
Ye Wang · 1×
Citations per year

Countries citing papers authored by Xinxin Si

Since Specialization
Citations

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

Fields of papers citing papers by Xinxin Si

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016267
2 2018222
3 2016119
4 201565
5 202062
6 202037
7 202033
8 201230
9 202029
10 202016
11 201616
12 202413
13 202213
14 202412
15 202212
16 201911
17 201911
18 202211
19 20209
20 20239

About Xinxin Si

Xinxin Si is a scholar working on Molecular Biology, Pharmacology, Organic Chemistry, Computational Theory and Mathematics and Cancer Research, having authored 48 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), RNA modifications and cancer (6 papers), Cancer-related molecular mechanisms research (5 papers), Cholinesterase and Neurodegenerative Diseases (4 papers), Synthesis and biological activity (4 papers), Down syndrome and intellectual disability research (3 papers), Biosensors and Analytical Detection (2 papers) and Antibiotic Resistance in Bacteria (2 papers). The work is most often cited by research in Cancer Research (569 citations), Molecular Biology (716 citations), Endocrinology (32 citations), Pharmacology (51 citations) and Molecular Medicine (14 citations). Xinxin Si has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Erbao Zhang, Wei De, Jinfei Chen, Dandan Yin, Liang Han, Xuezhi He, Tongpeng Xu, Yongqian Shu, Lin Xu and Xiyi Lu. Their work appears in journals such as Oncotarget, Pharmacology, BMC Veterinary Research, Scientific Reports and Clinica Chimica Acta.

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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