Research output per year
Research output per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Doctoral degree, Engineering and Technology, University of Helsinki
Award Date: 15 Feb 2013
Fingerprint
Dive into the research topics where Markus Heinonen is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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AbODE: Ab initio antibody design using conjoined ODEs
Verma, Y., Heinonen, M. & Garg, V., Jul 2023, Proceedings of the 40th International Conference on Machine Learning. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). JMLR, p. 35037-35050 14 p. (Proceedings of Machine Learning Research; vol. 202).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Open AccessFile3 Downloads (Pure) -
Chemistry-Based Modeling on Phenotype-Based Drug-Induced Liver Injury Annotation : From Public to Proprietary Data
Moein, M., Heinonen, M., Mesens, N., Chamanza, R., Amuzie, C., Will, Y., Ceulemans, H., Kaski, S. & Herman, D., 21 Aug 2023, In: CHEMICAL RESEARCH IN TOXICOLOGY. 36, 8, p. 1238−1247Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile1 Citation (Scopus)2 Downloads (Pure) -
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach
Raj, V., Cui, T., Heinonen, M. & Marttinen, P., 2023, Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS) 2023. Ruiz, F., Dy, J. & van de Meent, J-W. (eds.). JMLR, p. 6741-6763 (Proceedings of Machine Learning Research; vol. 206).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Open AccessFile3 Downloads (Pure) -
TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifs
Jokinen, E., Dumitrescu, A., Huuhtanen, J., Gligorijevic, V., Mustjoki, S., Bonneau, R., Heinonen, M. & Lähdesmäki, H., 1 Jan 2023, In: Bioinformatics. 39, 1, 8 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile1 Citation (Scopus)27 Downloads (Pure) -
Uncertainty-Aware Natural Language Inference with Stochastic Weight Averaging
Talman, A., Celikkanat, H., Virpioja, S., Heinonen, M. & Tiedemann, J., 2023, Proceedings of the 24th Nordic Conference on Computational Linguistics. University of Tartu Library, p. 358-365Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Open AccessFile3 Downloads (Pure)
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Heinonen Markus/ AT jatko: Deep learning with differential equations
01/09/2023 → 31/08/2025
Project: Academy of Finland: Other research funding
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Heinonen Markus AT-palkka: Deep learning with differential equations
01/09/2020 → 31/08/2025
Project: Academy of Finland: Other research funding
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-: Deep learning with differential equations
Heinonen, M., Rissanen, S. & Keurulainen, O.
01/09/2020 → 31/08/2023
Project: Academy of Finland: Other research funding
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Research and Collaboration Agreement
Kaski, S., Heinonen, M., Qin, X. & Moein, M.
01/10/2018 → 31/12/2020
Project: Corporate foreign
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Next-generation statistical learning for synthetic enzyme engineering
01/09/2016 → 31/08/2019
Project: Academy of Finland: Other research funding
Datasets
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Modeling binding specificities of transcription factor pairs with random forests
Antikainen, A. A. (Creator), Heinonen, M. (Creator) & Lähdesmäki, H. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.c.6031779.v1, https://springernature.figshare.com/collections/Modeling_binding_specificities_of_transcription_factor_pairs_with_random_forests/6031779/1 and 2 more links, https://doi.org/10.6084/m9.figshare.20003418.v1, https://doi.org/10.6084/m9.figshare.20003421.v1 (show fewer)
Dataset
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Genome wide analysis of protein production load in Trichoderma reesei
Pakula, T. M. (Contributor), Nygren, H. (Contributor), Barth, D. (Contributor), Heinonen, M. (Contributor), Castillo, S. (Contributor), Penttilä, M. (Creator) & Arvas, M. (Contributor), figshare, 1 Jan 2016
DOI: 10.6084/m9.figshare.c.3603251.v1, https://figshare.com/collections/Genome_wide_analysis_of_protein_production_load_in_Trichoderma_reesei/3603251/1
Dataset
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Additional file 2 of Modeling binding specificities of transcription factor pairs with random forests
Antikainen, A. A. (Creator), Heinonen, M. (Creator) & Lähdesmäki, H. (Creator), figshare, 6 Jun 2022
DOI: 10.6084/m9.figshare.20003421, https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Modeling_binding_specificities_of_transcription_factor_pairs_with_random_forests/20003421
Dataset
Activities
- 3 Visiting an external academic institution
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University of California San Francisco
Markus Heinonen (Visiting researcher)
9 Jan 2017 → 24 Feb 2017Activity: Visiting an external institution types › Visiting an external academic institution
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University of California San Francisco
Markus Heinonen (Visiting researcher)
31 Jul 2017 → 25 Aug 2017Activity: Visiting an external institution types › Visiting an external academic institution
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Telecom ParisTech
Markus Heinonen (Visiting researcher)
1 Jan 2013 → 30 Dec 2014Activity: Visiting an external institution types › Visiting an external academic institution
Press/Media
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Aalto University Reports Findings in Drug-Induced Liver Injury (Chemistry-Based Modeling on Phenotype-Based Drug-Induced Liver Injury Annotation: From Public to Proprietary Data)
Markus Heinonen & Samuel Kaski
22/08/2023
1 item of Media coverage
Press/Media: Media appearance
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Aalto University Reports Findings in Bioinformatics (TCRconv: Predicting recognition between T cell receptors and epitopes using contextualized motifs)
Harri Lähdesmäki & Markus Heinonen
19/12/2022
1 item of Media coverage
Press/Media: Media appearance
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Strengthening nonparametric Bayesian methods with structured kernels
Markus Heinonen & Samuel Kaski
09/11/2022
1 item of Media coverage
Press/Media: Media appearance
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Differential Equations for Machine Learning
Markus Heinonen & Harri Lähdesmäki
14/01/2022
1 item of Media coverage
Press/Media: Media appearance
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Artificial Intelligence Model Predicts Which Immune System Key Opens the Locks of Coronavirus
Harri Lähdesmäki & Markus Heinonen
30/04/2021
1 item of Media coverage
Press/Media: Media appearance