About
I am an Immunoinformatics PhD student at the Technical University of Denmark. I am excited about applications of machine learning for design and optimization of antibody therapeutics. My previous work includes constructing algorithms for predicting B-cell epitopes, TCR-p-MHC binding, and protein secondary structure. Since summer 2022, I have worked on developing antibody inverse folding models for therapeutic design, supervised by Charlotte Deane at the Oxford Protein Informatics Group.
Publications
AntiFold: Improved antibody structure design using inverse folding
MH Høie, A Hummer, TH Olsen, M Nielsen, C Deane
NeurIPS 2023 Generative AI and Biology, 2023
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DiscoTope-3.0 - Improved B-cell epitope prediction using AlphaFold2 modeling and inverse folding latent representations
MH Høie, FS Gade, JM Johansen, C Würtzen, O Winther, M Nielsen, P Marcatili
bioRxiv pre-print, 2023
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Widespread amyloidogenicity potential of multiple myeloma patient-derived immunoglobulin light chains
R Sternke-Hoffman, T Pauly, RK Norrild, J Hansen, F Tucholski, MH Høie, P Marcatili, M Dupré, M Duchateau, M Rey, C Malosse, S Metzger, A Boquoi, F Platten, SU Egelhaaf, J Chamot-Rooke, R Fenk, L Nagel-Steger, R Haas, AK Buell
BMC Biology, 2023
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BepiPred-3.0 - Improved B-cell epitope prediction using protein language models
J Clifford, MH Høie, S Deleuran, B Peters, M Nielsen, P Marcatili
Protein Science, 2022
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NetSurfP-3.0 - accurate and fast prediction of protein structural features by protein language models and deep learning
MH Høie, EN Kiehl, B Petersen, M Nielsen, O Winther, H Nielsen, J Hallgren, P Marcatili
Nucleic Acids Research, 2022
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Predicting and interpreting large-scale mutagenesis data using analyses of protein stability and conservation
MH Høie, M Cagiada, AHB Frederiksen, A Stein, K Lindorff-Larsen
Cell Reports, 2022
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Talks
Talks at selected conferences.
AntiFold: Improved antibody structure design using inverse folding
Spotlight, NeurIPS GenBio 2023
Dec 2023
DiscoTope-3.0: Improved B-cell epitope prediction using AlphaFold2 modeling and inverse folding latent representations
Selected talk, ELIXIR Annual Danish Bioinformatics Conference 2023
Sep 2023
Immunological binding prediction using protein language models & inverse folding
SDC Annual Life Science Engineering and Informatics PhD Symposium 2023
June 2023
Supervising
Below are listed titles of the M.Sc. Thesis' and independent research projects I have co-supervised during my time at the Technical University of Denmark.
Development of improved prediction methods for B cell epitopes prediction
Carlos de Santiago León
2023
Structure-based prediction of TCR-pMHC interaction using Graph Neural Networks
Julie Maria Johansen,
Charlotte Würtzen
2022
Using deep learning for improving TCR homology modeling and its application to immunogenicity prediction
Ida Meitil
2021
Community
To build a community in Denmark for sharing experience on working with machine-learning and data-science methods handling biological data, I organized events together with Paolo Marcatili, Tobias Hegelund Olsen and Andreas Fønss Møller. This led to 4 events with 200+ academic and industry professional participants, attending from Novo Nordisk, NovoZymes, Lundbeck, DTU and KU.
Biodatascience101
Organized 4 events teaching biological data-science to academics and industry professionals
2019-2021
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Copenhagen Bioinformatics Hackathon 2021
Hosted TCR-p-MHC prediction challenge, with 7 competing teams
2021
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Teaching
Below you can find a list over courses I have taught in.
DTU course 22117 Protein structure and computational biology
Teaching assistant
Spring, 2022
DTU course 22111 Introduction to Bioinformatics
Teaching assistant
Spring, 2022
DTU course 22110 Python and Unix for Bioinformaticians
Teaching assistant
Fall 2021