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Emmi Jokinen

Showing results (1-10 of 13) with videos related to

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Bioinformatics (Oxford, England)|June 29, 2018
mGPfusion: predicting protein stability changes with Gaussian process kernel learning and data fusionEmmi Jokinen, Markus Heinonen, Harri Lähdesmäki
Plos Computational Biology|March 25, 2021
Predicting recognition between T cell receptors and epitopes with TCRGPEmmi Jokinen, Jani Huuhtanen, Satu Mustjoki, et al.
Bioinformatics (Oxford, England)|December 9, 2023
EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddingsDani Korpela, Emmi Jokinen, Alexandru Dumitrescu, et al.
Bioinformatics (Oxford, England)|June 30, 2023
TSignal: a transformer model for signal peptide predictionAlexandru Dumitrescu, Emmi Jokinen, Anja Paatero, et al.
Bioinformatics (Oxford, England)|December 8, 2022
TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifsEmmi Jokinen, Alexandru Dumitrescu, Jani Huuhtanen, et al.
Leukemia|August 23, 2025
Predicting antigen-specific T-cell immunity against Wilms tumor 1 in hematologic cancerBrittany L Ford, Emmi Jokinen, Jani Huuhtanen, et al.
Applied Microbiology and Biotechnology|November 4, 2020
Substrate specificity of 2-deoxy-D-ribose 5-phosphate aldolase (DERA) assessed by different protein engineering and machine learning methodsSanni Voutilainen, Markus Heinonen, Martina Andberg, et al.
Nature Communications|October 11, 2022
Evolution and modulation of antigen-specific T cell responses in melanoma patientsJani Huuhtanen, Liang Chen, Emmi Jokinen, et al.
Blood|January 10, 2025
High-throughput drug screening identifies SMAC mimetics as enhancers of NK-cell cytotoxicity in chronic myeloid leukemiaPetra Nygrén, Jonas Bouhlal, Emmi Jokinen, et al.
The Journal of Clinical Investigation|January 31, 2023
Single-cell characterization of anti-LAG-3 and anti-PD-1 combination treatment in patients with melanomaJani Huuhtanen, Henna Kasanen, Katriina Peltola, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|June 29, 2018
mGPfusion: predicting protein stability changes with Gaussian process kernel learning and data fusionEmmi Jokinen, Markus Heinonen, Harri Lähdesmäki
Plos Computational Biology|March 25, 2021
Predicting recognition between T cell receptors and epitopes with TCRGPEmmi Jokinen, Jani Huuhtanen, Satu Mustjoki, et al.
Bioinformatics (Oxford, England)|December 9, 2023
EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddingsDani Korpela, Emmi Jokinen, Alexandru Dumitrescu, et al.
Bioinformatics (Oxford, England)|June 30, 2023
TSignal: a transformer model for signal peptide predictionAlexandru Dumitrescu, Emmi Jokinen, Anja Paatero, et al.
Bioinformatics (Oxford, England)|December 8, 2022
TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifsEmmi Jokinen, Alexandru Dumitrescu, Jani Huuhtanen, et al.
Leukemia|August 23, 2025
Predicting antigen-specific T-cell immunity against Wilms tumor 1 in hematologic cancerBrittany L Ford, Emmi Jokinen, Jani Huuhtanen, et al.
Applied Microbiology and Biotechnology|November 4, 2020
Substrate specificity of 2-deoxy-D-ribose 5-phosphate aldolase (DERA) assessed by different protein engineering and machine learning methodsSanni Voutilainen, Markus Heinonen, Martina Andberg, et al.
Nature Communications|October 11, 2022
Evolution and modulation of antigen-specific T cell responses in melanoma patientsJani Huuhtanen, Liang Chen, Emmi Jokinen, et al.
Blood|January 10, 2025
High-throughput drug screening identifies SMAC mimetics as enhancers of NK-cell cytotoxicity in chronic myeloid leukemiaPetra Nygrén, Jonas Bouhlal, Emmi Jokinen, et al.
The Journal of Clinical Investigation|January 31, 2023
Single-cell characterization of anti-LAG-3 and anti-PD-1 combination treatment in patients with melanomaJani Huuhtanen, Henna Kasanen, Katriina Peltola, et al.
Pageof 2