Ting Chen

19.4k citations
203 papers · 5.3k indexed · 4 hit papers · h-index 34

Impact in

Papers in

Ting Chen

187 papers receiving 5.2k citations

Hit Papers

G protein-coupled receptors (GPCRs): advances in structures, mechanisms and drug discovery 2024 · 171 citations
1712018202620202023100200300

Peers

Ting Chen
Comparison fields: 5 of 201
  • Health Informatics 72
  • Periodontics 155
  • Renewable Energy, Sustainability and the Environment 508
  • Molecular Biology 2.0k
  • Artificial Intelligence 729
Replace Jonas S. Almeida with:
Jonas S. Almeida United States
Le Zhang China
Yan Wang China
Bairong Shen China
Qian Li China
Kun Chen China
Yijun Chen China
Mohammad Ali Moni Australia
Jialiang Li Singapore
Weida Tong United States
Ting Chen relative to Jonas S. Almeida United States Jonas S. Almeida's profile →
Citations per field
00.5×10×13.4×
Jonas S. Almeida · 1×
Citations per year

Countries citing papers authored by Ting Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ting Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20257
4 20245
5 20245
6 20242
7 20241
8 202412
9 202424
10 20242
11 20243
12 20240
13 20249
14 202380
15 20212
16 2020137
17 201913
18 20181
19
mLDM: A New Hierarchical Bayesian Statistical Model for Sparse Microbial Association Discovery.
20162
20 201512

About Ting Chen

Ting Chen is a scholar working on Health Informatics, Molecular Biology, Artificial Intelligence, Family Practice and Health Information Management, having authored 203 papers that have together received 5.3k indexed citations. Recurring topics across this work include Gut microbiota and health (33 papers), Gene expression and cancer classification (13 papers), Genomics and Phylogenetic Studies (12 papers), Machine Learning in Healthcare (11 papers), Microbial Community Ecology and Physiology (9 papers), Genetic Associations and Epidemiology (9 papers), Topic Modeling (8 papers) and Probiotics and Fermented Foods (8 papers). The work is most often cited by research in Health Informatics (72 citations), Periodontics (155 citations), Renewable Energy, Sustainability and the Environment (508 citations), Molecular Biology (2.0k citations) and Artificial Intelligence (729 citations). Ting Chen has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Rui Jiang, James Kai‐sing Kung, Fengzhu Sun, Michael S. Waterman, Kui Zhang, Minghua Deng, Yang Bai, Xu Zhang, Ning Chen and Li Wang. Their work appears in journals such as Bioinformatics, Scientific Reports, The Science of The Total Environment, Briefings in Bioinformatics and Medicine.

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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