Tom Jacobs
Impact in
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- Conducting polymers and applications
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- Hepatitis C virus research
Papers in
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- Statistical Methods in Clinical Trials 8
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- Computational Drug Discovery Methods 6
- Co-authors
- H.‐G. Boyen (1 shared paper)Bert Conings (1 shared paper)Jan D’Haen (1 shared paper)Jean Manca (1 shared paper)Linny Baeten (1 shared paper)Leen Vijgen (2 shared papers)Thierry Verbinnen (2 shared papers)Oliver Lenz (2 shared papers)
- Journals
- Journal of Biopharmaceutical Statistics (3 papers)Pharmaceutical Statistics (3 papers)Alzheimer s & Dementia (2 papers)Journal of Alzheimer s Disease (2 papers)Statistics in Biopharmaceutical Research (2 papers)
- Partner nations
- BelgiumUnited StatesUnited Kingdom
In The Last Decade
Tom Jacobs
18 papers receiving 232 citations
Peers
Comparison fields: 5 of 72
- Polymers and Plastics 61
- Hepatology 29
- Neurology 17
- Electrical and Electronic Engineering 107
- Statistics and Probability 15
Countries citing papers authored by Tom Jacobs
This map shows the geographic impact of Tom Jacobs'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 Jacobs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Jacobs more than expected).
Fields of papers citing papers by Tom Jacobs
This network shows the impact of papers produced by Tom Jacobs. 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 Jacobs. The network helps show where Tom Jacobs may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Jacobs, 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 | 2014 | 107 | |
| 2 | 2019 | 24 | |
| 3 | 2016 | 23 | |
| 4 | 2015 | 20 | |
| 5 | 2020 | 11 | |
| 6 | 2012 | 11 | |
| 7 | 2013 | 7 | |
| 8 | 2008 | 6 | |
| 9 | 2012 | 5 | |
| 10 | 2019 | 4 | |
| 11 | 2018 | 4 | |
| 12 | 2010 | 4 | |
| 13 | 2018 | 3 | |
| 14 | 2018 | 3 | |
| 15 | 2008 | 2 | |
| 16 | 2017 | 2 | |
| 17 | 2017 | 1 | |
| 18 | 2020 | 1 |
About Tom Jacobs
Tom Jacobs is a scholar working on Statistics and Probability, Computational Theory and Mathematics, Management Science and Operations Research, Physiology and Infectious Diseases, having authored 18 papers that have together received 238 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (8 papers), Computational Drug Discovery Methods (6 papers), Alzheimer's disease research and treatments (4 papers), Optimal Experimental Design Methods (4 papers), Analytical Chemistry and Chromatography (3 papers), Biosimilars and Bioanalytical Methods (3 papers), HIV/AIDS drug development and treatment (3 papers) and HIV Research and Treatment (2 papers). The work is most often cited by research in Polymers and Plastics (61 citations), Hepatology (29 citations), Neurology (17 citations), Electrical and Electronic Engineering (107 citations) and Statistics and Probability (15 citations). Tom Jacobs has collaborated with scholars based in Belgium, United States and United Kingdom. Frequent co-authors include H.‐G. Boyen, Bert Conings, Jan D’Haen, Jean Manca, Linny Baeten, Leen Vijgen, Thierry Verbinnen, Oliver Lenz, Thomas Jaki and Helena Geys. Their work appears in journals such as Journal of Biopharmaceutical Statistics, Pharmaceutical Statistics, Alzheimer s & Dementia, Journal of Alzheimer s Disease and Statistics in Biopharmaceutical Research.
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.