Markus Heinonen
Impact in
-
- Computational Drug Discovery Methods
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- Metabolomics and Mass Spectrometry Studies
- vaccines and immunoinformatics approaches
- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
Papers in
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- Metabolomics and Mass Spectrometry Studies 3
- Bioinformatics and Genomic Networks 3
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- Gaussian Processes and Bayesian Inference 9
- Co-authors
- Juho Rousu (6 shared papers)Nicola Zamboni (2 shared papers)Huibin Shen (2 shared papers)Harri Lähdesmäki (11 shared papers)Kyle A. Barlow (1 shared paper)Pooja Suresh (1 shared paper)Samuel Thompson (1 shared paper)James E. Lucas (1 shared paper)
- Journals
- Bioinformatics (4 papers)Journal of Cheminformatics (3 papers)Blood (2 papers)Vox Sanguinis (1 paper)Computational Statistics & Data Analysis (1 paper)
- Partner nations
- FinlandUnited StatesSweden
In The Last Decade
Markus Heinonen
31 papers receiving 655 citations
Peers
Comparison fields: 5 of 109
- Computational Theory and Mathematics 140
- Molecular Biology 485
- Spectroscopy 95
- Immunology 87
- Radiology, Nuclear Medicine and Imaging 78
Countries citing papers authored by Markus Heinonen
This map shows the geographic impact of Markus Heinonen'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 Markus Heinonen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Heinonen more than expected).
Fields of papers citing papers by Markus Heinonen
This network shows the impact of papers produced by Markus Heinonen. 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 Markus Heinonen. The network helps show where Markus Heinonen may publish in the future.
Co-authors
The 25 scholars most cited alongside Markus Heinonen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 158 | |
| 2 | 2012 | 139 | |
| 3 | 2021 | 83 | |
| 4 | 2018 | 53 | |
| 5 | 2014 | 28 | |
| 6 | 2013 | 25 | |
| 7 | 2020 | 23 | |
| 8 | 2016 | 18 | |
| 9 | 2017 | 18 | |
| 10 | Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo | 2016 | 16 |
| 11 | ODE2VAE: Deep generative second order ODEs with Bayesian neural networks | 2019 | 14 |
| 12 | 2022 | 14 | |
| 13 | 2022 | 13 | |
| 14 | 2021 | 10 | |
| 15 | 2024 | 7 | |
| 16 | 2012 | 6 | |
| 17 | 2023 | 6 | |
| 18 | 2018 | 5 | |
| 19 | 2022 | 5 | |
| 20 | 2019 | 5 |
About Markus Heinonen
Markus Heinonen is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering and Spectroscopy, having authored 33 papers that have together received 666 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (9 papers), Computational Drug Discovery Methods (6 papers), T-cell and B-cell Immunology (4 papers), Analytical Chemistry and Chromatography (3 papers), Machine Learning in Materials Science (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Immunotherapy and Immune Responses (3 papers) and Bioinformatics and Genomic Networks (3 papers). The work is most often cited by research in Computational Theory and Mathematics (140 citations), Molecular Biology (485 citations), Spectroscopy (95 citations), Immunology (87 citations) and Radiology, Nuclear Medicine and Imaging (78 citations). Markus Heinonen has collaborated with scholars based in Finland, United States and Sweden. Frequent co-authors include Juho Rousu, Nicola Zamboni, Huibin Shen, Harri Lähdesmäki, Kyle A. Barlow, Pooja Suresh, Samuel Thompson, James E. Lucas, Tanja Kortemme and Shane Ó Conchúir. Their work appears in journals such as Bioinformatics, Journal of Cheminformatics, Blood, Vox Sanguinis and Computational Statistics & Data Analysis.
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.