Thomas Schaffter
Impact in
- Molecular Biology top 10%
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Microbial Metabolic Engineering and Bioproduction
- Single-cell and spatial transcriptomics
- CRISPR and Genetic Engineering
- Viral Infectious Diseases and Gene Expression in Insects
- Biophysics top 10%
Papers in
-
- Cell Image Analysis Techniques 2
- Co-authors
- Dario FloreanoDaniel MarbachClaudio MattiussiGustavo StolovitzkyRobert J. PrillMehmet Eren AhsenRichard BentonPavan P Ramdya
- Journals
- Journal of Philosophical Logic (1 paper)JAMA Network Open (1 paper)Bioinformatics (1 paper)eLife (1 paper)Journal of Computational Biology (1 paper)
- Partner nations
- United StatesSwitzerland
In The Last Decade
Thomas Schaffter
10 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Molecular Biology 1.1k
- Biophysics 47
- Health Informatics 11
- Computational Theory and Mathematics 79
- Artificial Intelligence 158
Countries citing papers authored by Thomas Schaffter
This map shows the geographic impact of Thomas Schaffter'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 Thomas Schaffter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Schaffter more than expected).
Fields of papers citing papers by Thomas Schaffter
This network shows the impact of papers produced by Thomas Schaffter. 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 Thomas Schaffter. The network helps show where Thomas Schaffter may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Thomas Schaffter, 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 | 2022 | 28 | |
| 2 | 2020 | 19 | |
| 3 | 2020 | 4 | |
| 4 | 2014 | 1 | |
| 5 | 2012 | 13 | |
| 6 | 2011 | 360 | |
| 7 | Numerical Integration of SDEs: A Short Tutorial | 2010 | 13 |
| 8 | Revealing strengths and weaknesses of methods for gene network inference Hit paper breakdown → | 2010 | 520 |
| 9 | GeneNetWeaver 3.0: realistic benchmark generation and performance profiling of network inference methods | 2010 | 1 |
| 10 | 2009 | 301 | |
| 11 | 1979 | 1 | |
| 12 | 1975 | 0 |
About Thomas Schaffter
Thomas Schaffter is a scholar working on Health Informatics, Biophysics, Health Information Management, Numerical Analysis and Finance, having authored 12 papers that have together received 1.3k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (5 papers), Bioinformatics and Genomic Networks (5 papers), Gene expression and cancer classification (3 papers), Cell Image Analysis Techniques (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Artificial Intelligence in Healthcare (1 paper), CRISPR and Genetic Engineering (1 paper) and Plant and animal studies (1 paper). The work is most often cited by research in Molecular Biology (1.1k citations), Biophysics (47 citations), Health Informatics (11 citations), Computational Theory and Mathematics (79 citations) and Artificial Intelligence (158 citations). Thomas Schaffter has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Dario Floreano, Daniel Marbach, Claudio Mattiussi, Gustavo Stolovitzky, Robert J. Prill, Mehmet Eren Ahsen, Richard Benton, Pavan P Ramdya, Arash Naeim and Ronald Realubit. Their work appears in journals such as Journal of Philosophical Logic, JAMA Network Open, Bioinformatics, eLife and Journal of Computational Biology.
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.