Siying Ma

662 citations
23 papers · 460 · h-index 10

Impact in

    • Advanced biosensing and bioanalysis techniques
    • CRISPR and Genetic Engineering
    • RNA and protein synthesis mechanisms
    • Microbial Metabolic Engineering and Bioproduction
    • RNA Interference and Gene Delivery
    • Biosensors and Analytical Detection
    • Innovative Microfluidic and Catalytic Techniques Innovation

Papers in

Siying Ma

15 papers receiving 438 citations

Peers

Siying Ma
Comparison fields: 5 of 67
  • Molecular Biology 335
  • Biomedical Engineering 118
  • Nuclear Energy and Engineering 1
  • Hepatology 14
  • Genetics 51
Replace Taraka Sai Pavan Grandhi with:
Taraka Sai Pavan Grandhi United States
Mitsuru Ando Japan
Fangqi Peng China
Leonie Roos United Kingdom
Olivier Galy France
Yuefeng Shi China
Danny Wilbie Netherlands
Anindit Mukherjee United States
Lilin Ge China
Siying Ma relative to Taraka Sai Pavan Grandhi United States Taraka Sai Pavan Grandhi's profile →
Citations per field
00.5×10×15×19×
Taraka Sai Pavan Grandhi · 1×
Citations per year

Countries citing papers authored by Siying Ma

Since Specialization
Citations

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

Fields of papers citing papers by Siying Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011114
2 201283
3 201156
4 202251
5 201631
6 202330
7 201129
8 202419
9 202212
10 202311
11 20248
12 20238
13 20254
14 20242
15 20242
16 20240
17 20250
18 20240
19 20240
20 20250

About Siying Ma

Siying Ma is a scholar working on Molecular Biology, Materials Chemistry, Electrical and Electronic Engineering, Biomedical Engineering and Atmospheric Science, having authored 23 papers that have together received 460 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (5 papers), Advanced biosensing and bioanalysis techniques (4 papers), Climate variability and models (2 papers), Biosensors and Analytical Detection (2 papers), Ammonia Synthesis and Nitrogen Reduction (2 papers), Gas Sensing Nanomaterials and Sensors (2 papers), Gene Regulatory Network Analysis (2 papers) and Meteorological Phenomena and Simulations (2 papers). The work is most often cited by research in Molecular Biology (335 citations), Biomedical Engineering (118 citations), Nuclear Energy and Engineering (1 citation), Hepatology (14 citations) and Genetics (51 citations). Siying Ma has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Jingdong Tian, Nicholas Tang, Ishtiaq Saaem, Kevin P. White, Hui Gong, Nicolas Nègre, Hon Fai Chan, Kam W. Leong, Huan Liang and Can-Peng Li. Their work appears in journals such as Nature Communications, Talanta, European Polymer Journal, Food Science and Human Wellness and Drug Delivery.

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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