Author

Markus Heinonen

Aalto UniversityORCID 0000-0002-7741-2279Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1

Frequent Co-Authors

Emmi JokineniD· 2 shared Jani HuuhtaneniD· 2 shared Satu M. MustjokiiD· 2 shared Alexandru DumitrescuiD· 1 shared Harri J LähdesmäkiiD· 1 shared Harri Lähdesmäki· 1 shared Richard BonneauiD· 1 shared Vladimir GligorijevićiD· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 24 mutual co-author links

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2 shared papersBioinformatics

Emmi JokinenORCID

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2 papers

Recent·Most cited

Predicting recognition between T cell receptors and epitopes using contextualized motifs

Emmi Jokinen, Alexandru Dumitrescu, Jani Huuhtanen, Vladimir Gligorijević, Satu M. Mustjoki, Richard Bonneau, Markus Heinonen, Harri J Lähdesmäki

TCRconv predicts T-cell receptor-epitope recognition using a deep learning model and provides insights into T-cell dynamics in COVID-19 patients.

bioRxiv · May 23, 2022 · PreprintBioinformatics

Determining epitope specificity of T cell receptors with TCRGP

Emmi Jokinen, Jani Huuhtanen, Satu M. Mustjoki, Markus Heinonen, Harri Lähdesmäki

The paper introduces TCRGP, a Gaussian process method for predicting TCR epitope specificity, and applies it to scRNA+TCRβ data to identify HBV-epitope specific T cells in hepatocellular carcinoma patients.

bioRxiv · Aug 21, 2019 · PreprintBioinformatics