Tom C. Freeman
- Neurology top 0.5%
- Neuroinflammation and Neurodegeneration Mechanisms 9
- Immunology top 1%
- Immune cells in cancer 11
- Immune Response and Inflammation 9
- T-cell and B-cell Immunology 9
- Physiology top 0.5%
- Biological Psychiatry top 2%
- Developmental Neuroscience top 2%
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- Bioinformatics and Genomic Networks 22
- Gene expression and cancer classification 12
- Gene Regulatory Network Analysis 8
- Wnt/β-catenin signaling in development and cancer 7
- Co-authors
- J. Kenneth BaillieDavid HumePeter J. RichardsonKim SummersBarry W. McCollKathleen GrabertD.J.S. SirinathsinghjiAnton J. Enright
- Cited by
- NeurologyImmunologyPhysiology
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Tom C. Freeman
162 papers receiving 9.5k citations
Hit Papers
Peers
Comparison fields: 5 of 173
- Neurology 1.2k
- Immunology 2.3k
- Physiology 473
- Biological Psychiatry 181
- Developmental Neuroscience 274
Countries citing papers authored by Tom C. Freeman
This map shows the geographic impact of Tom C. Freeman'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 Tom C. Freeman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom C. Freeman more than expected).
Fields of papers citing papers by Tom C. Freeman
This network shows the impact of papers produced by Tom C. Freeman. 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 Tom C. Freeman. The network helps show where Tom C. Freeman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tom C. Freeman, 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 | 2025 | 0 | |
| 2 | 2022 | 46 | |
| 3 | 2020 | 13 | |
| 4 | 2019 | 48 | |
| 5 | 2018 | 135 | |
| 6 | 2018 | 55 | |
| 7 | 2017 | 18 | |
| 8 | 2013 | 32 | |
| 9 | Application of graph layout algorithms for the visualization of biological networks in 3D | 2013 | 0 |
| 10 | 2012 | 24 | |
| 11 | 2008 | 64 | |
| 12 | 2006 | 9 | |
| 13 | 2006 | 137 | |
| 14 | 2005 | 178 | |
| 15 | 2002 | 1 | |
| 16 | 2002 | 52 | |
| 17 | Microarray analysis of human placental cytotrophoblast (BeWo cell) syncytialisation induced by forskolin | 2002 | 1 |
| 18 | 1991 | 24 | |
| 19 | 1990 | 37 | |
| 20 | Studie zur chronischen Schizophrenie | 1969 | 1 |
About Tom C. Freeman
Tom C. Freeman is a scholar working on Immunology, Molecular Biology, Neurology, Genetics and Oncology, having authored 169 papers that have together received 9.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (22 papers), Gene expression and cancer classification (12 papers), Immune cells in cancer (11 papers), Immune Response and Inflammation (9 papers), Neuroinflammation and Neurodegeneration Mechanisms (9 papers), T-cell and B-cell Immunology (9 papers), Gene Regulatory Network Analysis (8 papers) and Wnt/β-catenin signaling in development and cancer (7 papers). The work is most often cited by research in Neurology (1.2k citations), Immunology (2.3k citations), Physiology (473 citations), Biological Psychiatry (181 citations) and Developmental Neuroscience (274 citations). Tom C. Freeman has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include J. Kenneth Baillie, David Hume, Peter J. Richardson, Kim Summers, Barry W. McColl, Kathleen Grabert, D.J.S. Sirinathsinghji, Anton J. Enright, Amelie K. Gubitz and Sara Clohisey. Their work appears in journals such as BMC Genomics, PLoS ONE, Scientific Reports, European Journal of Immunology and Genomics.
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.