Tony Kam‐Thong

1.4k citations
10 papers · 688 indexed · 1 hit paper · h-index 6
Topics
Single-cell and spatial transcriptomics (2 papers)Parkinson's Disease Mechanisms and Treatments (2 papers)T-cell and B-cell Immunology (2 papers)
Partner nations
SwitzerlandGermanyItaly

In The Last Decade

Tony Kam‐Thong

9 papers receiving 670 citations

Hit Papers

An Introduction to Machine Learning20202026202220242020100200300400500

Peers

Tony Kam‐Thong
Comparison fields: 5 of 164
  • Molecular Biology 173
  • Artificial Intelligence 111
  • Oncology 82
  • Biomedical Engineering 62
  • Immunology 61
Replace Bernhard Steiert with:
Bernhard Steiert Germany
Tayaza Fadason New Zealand
Katie Ovens Canada
Yaqi Wang China
Balázs Bánfai Switzerland
Farhad Maleki Canada
Jingyang Gao China
Rizwan Qureshi Pakistan
Lucy Hutchinson Switzerland
Guoxing Yang China
Tony Kam‐Thong relative to Bernhard Steiert Germany Bernhard Steiert's profile →
Citations per field
00.5×1.5×1.9×
Bernhard Steiert · 1×
Citations per year

Countries citing papers authored by Tony Kam‐Thong

Since Specialization
Citations

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

Fields of papers citing papers by Tony Kam‐Thong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tony Kam‐Thong. 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 Tony Kam‐Thong. The network helps show where Tony Kam‐Thong may publish in the future.

Co-authorship network of co-authors of Tony Kam‐Thong

This figure shows the co-authorship network connecting the top 25 collaborators of Tony Kam‐Thong. A scholar is included among the top collaborators of Tony Kam‐Thong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tony Kam‐Thong. Tony Kam‐Thong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
#WorkIndexed citations
1 8
2 0
3 1
4 5
5 2
6 12
7 47
8
An Introduction to Machine Learningbreakdown →
503
9 107
10 3

About Tony Kam‐Thong

Tony Kam‐Thong is a scholar working on Immunology, Biophysics and Cognitive Neuroscience, having authored 10 papers that have together received 688 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (2 papers), Parkinson's Disease Mechanisms and Treatments (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Health Informatics (21 citations), Artificial Intelligence (111 citations) and Health Information Management (15 citations). Tony Kam‐Thong has collaborated with scholars based in Switzerland, Germany and Italy. Frequent co-authors include Jitao David Zhang, Lucy Hutchinson, Solveig Badillo, Fabian Birzele, Bernhard Steiert, Iakov I. Davydov, Balázs Bánfai, Juliane Siebourg‐Polster, Chiara Palladino and Philipp Ottis. Their work appears in journals such as Brain, Frontiers in Immunology and Clinical Pharmacology & Therapeutics.

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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