Baiya Li

404 citations
18 papers · 124 · h-index 7

Impact in

Papers in

    • Prion Diseases and Protein Misfolding 4
    • RNA modifications and cancer 3
    • Cancer-related gene regulation 2
    • RNA Research and Splicing 2
    • Cancer-related molecular mechanisms research 3

Baiya Li

17 papers receiving 124 citations

Peers

Baiya Li
Comparison fields: 5 of 42
  • Neurology 27
  • Cancer Research 18
  • Molecular Biology 81
  • Nutrition and Dietetics 15
  • Endocrinology, Diabetes and Metabolism 10
Replace Frances M. Pool with:
Frances M. Pool United Kingdom
Yulia Kargapolova Germany
Ivana Josipovic Germany
Motti Farbstein Israel
S. Soler Spain
Yorrick Jaspers Netherlands
Taekyeong Yoo South Korea
John B. G. Mackey United Kingdom
Baiya Li relative to Frances M. Pool United Kingdom Frances M. Pool's profile →
Citations per field
00.5×1.5×2.3×
Frances M. Pool · 1×
Citations per year

Countries citing papers authored by Baiya Li

Since Specialization
Citations

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

Fields of papers citing papers by Baiya Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 201332
2 201317
3 202311
4 20228
5 20198
6 20168
7 20197
8 20236
9 20216
10 20116
11 20204
12 20184
13 20152
14 20232
15 20251
16 20241
17 20151
18 20240

About Baiya Li

Baiya Li is a scholar working on Molecular Biology, Cancer Research, Endocrinology, Diabetes and Metabolism, Nutrition and Dietetics and Surgery, having authored 18 papers that have together received 124 indexed citations. Recurring topics across this work include Prion Diseases and Protein Misfolding (4 papers), RNA modifications and cancer (3 papers), Cancer-related molecular mechanisms research (3 papers), Cancer-related gene regulation (2 papers), Thyroid Cancer Diagnosis and Treatment (2 papers), Trace Elements in Health (2 papers), RNA Research and Splicing (2 papers) and Pharmacogenetics and Drug Metabolism (1 paper). The work is most often cited by research in Neurology (27 citations), Cancer Research (18 citations), Molecular Biology (81 citations), Nutrition and Dietetics (15 citations) and Endocrinology, Diabetes and Metabolism (10 citations). Baiya Li has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Qingzhong Kong, Yuan Shao, Robert B. Petersen, Brian A. Cobb, Wen‐Quan Zou, Pierluigi Gambetti, Tetsuyuki Kitamoto, Jean Laplanche, Jan Langeveld and Junsong Liu. Their work appears in journals such as PLoS ONE, Medicine, BioMed Research International, Advanced Functional Materials and Future Oncology.

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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