Sin Lam Tan
Impact in
-
- Genomics and Chromatin Dynamics
- RNA and protein synthesis mechanisms
- RNA Research and Splicing
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- RNA modifications and cancer
- Biomedical Text Mining and Ontologies
Papers in
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- Biomedical Text Mining and Ontologies 4
- Genomics and Chromatin Dynamics 3
- Bioinformatics and Genomic Networks 3
- Genomics and Phylogenetic Studies 2
- RNA Research and Splicing 2
- RNA and protein synthesis mechanisms 2
- Genetics 4
- Co-authors
- Vladimir B. Bajić (11 shared papers)Yutaka Suzuki (1 shared paper)Sumio Sugano (1 shared paper)Chikatoshi Kai (3 shared papers)Piero Carninci (3 shared papers)Yoshihide Hayashizaki (3 shared papers)Jun Kawai (3 shared papers)Rajesh Chowdhary (6 shared papers)
- Journals
- Nucleic Acids Research (4 papers)PLoS Genetics (2 papers)Nature Biotechnology (1 paper)PLoS ONE (1 paper)BMC Neurology (1 paper)
- Partner nations
- SingaporeUnited StatesChina
In The Last Decade
Sin Lam Tan
15 papers receiving 387 citations
Peers
Comparison fields: 5 of 73
- Molecular Biology 323
- Genetics 73
- Cancer Research 37
- Health Information Management 7
- Microbiology 8
Countries citing papers authored by Sin Lam Tan
This map shows the geographic impact of Sin Lam Tan'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 Sin Lam Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sin Lam Tan more than expected).
Fields of papers citing papers by Sin Lam Tan
This network shows the impact of papers produced by Sin Lam Tan. 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 Sin Lam Tan. The network helps show where Sin Lam Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Sin Lam Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 116 | |
| 2 | 2006 | 82 | |
| 3 | 2006 | 51 | |
| 4 | 2006 | 33 | |
| 5 | 2004 | 30 | |
| 6 | 2004 | 18 | |
| 7 | 2012 | 16 | |
| 8 | 2013 | 11 | |
| 9 | 2006 | 11 | |
| 10 | 2012 | 11 | |
| 11 | 2012 | 9 | |
| 12 | 2006 | 3 | |
| 13 | 2025 | 2 | |
| 14 | 2025 | 1 | |
| 15 | 2025 | 1 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 |
About Sin Lam Tan
Sin Lam Tan is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Cancer Research and Biomedical Engineering, having authored 18 papers that have together received 395 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Genomics and Chromatin Dynamics (3 papers), Cancer-related molecular mechanisms research (3 papers), Bioinformatics and Genomic Networks (3 papers), Genomics and Phylogenetic Studies (2 papers), RNA Research and Splicing (2 papers), Semantic Web and Ontologies (2 papers) and RNA and protein synthesis mechanisms (2 papers). The work is most often cited by research in Molecular Biology (323 citations), Genetics (73 citations), Cancer Research (37 citations), Health Information Management (7 citations) and Microbiology (8 citations). Sin Lam Tan has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Vladimir B. Bajić, Yutaka Suzuki, Sumio Sugano, Chikatoshi Kai, Piero Carninci, Yoshihide Hayashizaki, Jun Kawai, Rajesh Chowdhary, Christian Schönbach and Liang Yang. Their work appears in journals such as Nucleic Acids Research, PLoS Genetics, Nature Biotechnology, PLoS ONE and BMC Neurology.
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.