Harri Lähdesmäki
- Molecular Biology top 2%
- Immunology top 2%
- Oncology top 5%
- Cancer Research top 2%
- Genetics top 5%
- Co-authors
- Ilya ShmulevichTarmo ÄijöOlli Yli‐HarjaAnjana RaoRiitta LahesmaaSusan TogherAntti LarjoWilliam A. Pastor
- Topics
- Gene expression and cancer classification (28 papers)Immune Cell Function and Interaction (19 papers)T-cell and B-cell Immunology (19 papers)
- Partner nations
- FinlandUnited StatesUnited Kingdom
In The Last Decade
Harri Lähdesmäki
131 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 183
- Molecular Biology 2.9k
- Immunology 1.5k
- Oncology 798
- Cancer Research 677
- Genetics 632
Countries citing papers authored by Harri Lähdesmäki
This map shows the geographic impact of Harri Lähdesmäki'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 Harri Lähdesmäki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harri Lähdesmäki more than expected).
Fields of papers citing papers by Harri Lähdesmäki
This network shows the impact of papers produced by Harri Lähdesmäki. 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 Harri Lähdesmäki. The network helps show where Harri Lähdesmäki may publish in the future.
Co-authorship network of co-authors of Harri Lähdesmäki
This figure shows the co-authorship network connecting the top 25 collaborators of Harri Lähdesmäki. A scholar is included among the top collaborators of Harri Lähdesmäki 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 Harri Lähdesmäki. Harri Lähdesmäki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 3 | |
| 3 | 60 | |
| 4 | 17 | |
| 5 | 8 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 22 | |
| 10 | 12 | |
| 11 | Latent Gaussian process with composite likelihoods and numerical quadrature | 1 |
| 12 | Continuous-time Model-based Reinforcement Learning | 1 |
| 13 | 1 | |
| 14 | 4 | |
| 15 | ODE2VAE: Deep generative second order ODEs with Bayesian neural networks | 14 |
| 16 | Learning unknown ODE models with Gaussian processes | 3 |
| 17 | 265 | |
| 18 | Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo | 16 |
| 19 | 110 | |
| 20 | 138 |
About Harri Lähdesmäki
Harri Lähdesmäki is a scholar working on Immunology, Molecular Biology and Developmental Biology, having authored 136 papers that have together received 5.3k indexed citations. Recurring topics across this work include Gene expression and cancer classification (28 papers), Immune Cell Function and Interaction (19 papers) and T-cell and B-cell Immunology (19 papers). The work is most often cited by research in Immunology (1.5k citations), Cancer Research (677 citations) and Molecular Biology (2.9k citations). Harri Lähdesmäki has collaborated with scholars based in Finland, United States and United Kingdom. Frequent co-authors include Ilya Shmulevich, Tarmo Äijö, Olli Yli‐Harja, Anjana Rao, Riitta Lahesmaa, Susan Togher, Antti Larjo, William A. Pastor, Patrick G. Hogan and Ageliki Tsagaratou. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids 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.