Victor Greiff

• Kanduri, Chakravarthi; Pavlović, Milena; Scheffer, Lonneke; Motwani, Keshav; Chernigovskaya, Maria & Greiff, Victor [Show all 7 contributors for this article] (2022). Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification. GigaScience. ISSN 2047-217X. 11(05). doi: 10.1093/gigascience/giac046. Full text in Research Archive
• Akbar, Rahmad; Robert, Philippe Paul Auguste; Weber, Cédric R.; Widrich, Michael; Frank, Robert & Pavlovic, Milena [Show all 19 contributors for this article] (2022). In silico proof of principle of machine learning-based antibody design at unconstrained scale. mAbs. ISSN 1942-0862. 14:e2031482(1), p. 1–18. doi: 10.1080/19420862.2022.2031482.
• Grevys, Algirdas; Frick, Rahel; Mester, Simone; Flem-Karlsen, Karine; Nilsen, Jeannette & Foss, Stian [Show all 13 contributors for this article] (2022). Antibody variable sequences have a pronounced effect on cellular transport and plasma half-life. iScience. ISSN 2589-0042. 25(2). doi: 10.1016/j.isci.2022.103746.
• Akbar, Rahmad; Bashour, Habib; Rawat, Puneet; Robert, Philippe Paul Auguste; Smorodina, Eva & Cotet, Tudor-Stefan [Show all 15 contributors for this article] (2022). Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies. mAbs. ISSN 1942-0862. 14(1). doi: 10.1080/19420862.2021.2008790.
• Dahal-Koirala, Shiva; Balaban, Gabriel; Neumann, Ralf Stefan; Scheffer, Lonneke; Lundin, Knut & Greiff, Victor [Show all 9 contributors for this article] (2022). TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences. Briefings in Bioinformatics. ISSN 1467-5463. doi: 10.1093/bib/bbab566.
• Mathew, Nimitha R.; Kalathilparambil Jayanthan, Jayalal; Smirnov, Ilya V.; Robinson, Jonathan L.; Axelsson, Hannes & Nakka, Sravya S. [Show all 20 contributors for this article] (2021). Single-cell BCR and transcriptome analysis after influenza infection reveals spatiotemporal dynamics of antigen-specific B cells. Cell reports. ISSN 2211-1247. 35:109286(12), p. 1–25. doi: 10.1016/j.celrep.2021.109286. Full text in Research Archive
• Mikocziova, Ivana; Peres, Ayelet; Gidoni, Moriah; Greiff, Victor; Yaari, Gur & Sollid, Ludvig Magne (2021). Germline polymorphisms and alternative splicing of human immunoglobulin light chain genes. iScience. ISSN 2589-0042. 24:103192(10), p. 1–19. doi: 10.1016/j.isci.2021.103192. Full text in Research Archive
• Mikocziova, Ivana; Greiff, Victor & Sollid, Ludvig Magne (2021). Immunoglobulin germline gene variation and its impact on human disease. Genes and Immunity. ISSN 1466-4879. 22(4), p. 205–217. doi: 10.1038/s41435-021-00145-5. Full text in Research Archive
• Amoriello, Roberta; Chernigovskaia, Mariia; Greiff, Victor; Carnasciali, Alberto; Massacesi, Luca & Barilaro, Alessandro [Show all 13 contributors for this article] (2021). TCR repertoire diversity in Multiple Sclerosis: High-dimensional bioinformatics analysis of sequences from brain, cerebrospinal fluid and peripheral blood. EBioMedicine. ISSN 2352-3964. 68:103429, p. 1–13. doi: 10.1016/j.ebiom.2021.103429. Full text in Research Archive
• Robert, Philippe Paul Auguste; Kunze-Schumacher, Heike; Greiff, Victor & Krueger, Andreas (2021). Modeling the dynamics of T-cell development in the thymus. Entropy. ISSN 1099-4300. 23:437(4). doi: 10.3390/e23040437. Full text in Research Archive
• Slabodkin, Andrei; Chernigovskaia, Maria; Mikocziova, Ivana; Akbar, Rahmad; Scheffer, Lonneke & Pavlović, Milena [Show all 16 contributors for this article] (2021). Individualized VDJ recombination predisposes the available Ig sequence space. Genome Research. ISSN 1088-9051. p. 2209–2224. doi: 10.1101/gr.275373.121. Full text in Research Archive
• Pavlović, Milena; Scheffer, Lonneke; Motwani, Keshav; Kanduri, Chakravarthi; Kompova, Radmila & Vazov, Nikolay Aleksandrov [Show all 41 contributors for this article] (2021). The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nature Machine Intelligence. 3(11), p. 936–944. doi: 10.1038/s42256-021-00413-z.
• Neumeier, Daniel; Pedrioli, Alessandro; Genovese, Alessandro; Sandu, Ioana; Ehling, Roy & Hong, Kai-Lin [Show all 19 contributors for this article] (2021). Profiling the specificity of clonally expanded plasma cells during chronic viral infection by single-cell analysis. European Journal of Immunology. ISSN 0014-2980. 52(2), p. 297–311. doi: 10.1002/eji.202149331. Full text in Research Archive
• Snapkov, Igor; Chernigovskaia, Maria; Sinitcyn, Pavel; Le, Quy Khang; Nyman, Tuula Anneli & Greiff, Victor (2021). Progress and challenges in mass spectrometry-based analysis of antibody repertoires. Trends in Biotechnology. ISSN 0167-7799. 00, p. 1–19. doi: 10.1016/j.tibtech.2021.08.006. Full text in Research Archive
• Mester, Simone; Evers, Mitchell; Meyer, Saskia; Nilsen, Jeannette; Greiff, Victor & Sandlie, Inger [Show all 8 contributors for this article] (2021). Extended plasma half-life of albumin-binding domain fused human IgA upon pH-dependent albumin engagement of human FcRn in vitro and in vivo. mAbs. ISSN 1942-0862. 13:1893888(1), p. 1–14. doi: 10.1080/19420862.2021.1893888. Full text in Research Archive
• Øjlert, Åsa Kristina; Nebdal, Daniel J.H.; Snapkov, Igor; Olsen, Vibeke; Kidman, Joel & Greiff, Victor [Show all 8 contributors for this article] (2021). Dynamic changes in the T cell receptor repertoire during treatment with radiotherapy combined with an immune checkpoint inhibitor. Molecular Oncology. ISSN 1574-7891. p. 1–11. doi: 10.1002/1878-0261.13082. Full text in Research Archive
• Arnaout, Ramy A.; Luning Prak, Eline T.; Schwab, Nicholas; Rubelt, Florian; Greiff, Victor & Pavlović, Milena [Show all 32 contributors for this article] (2021). The Future of Blood Testing Is the Immunome. Frontiers in Immunology. ISSN 1664-3224. 12:626793, p. 1–6. doi: 10.3389/fimmu.2021.626793. Full text in Research Archive
• Greiff, Victor & Sandve, Geir Kjetil Ferkingstad (2021). Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification . BioRxiv. ISSN 0362-4331.
• Greiff, Victor & Sandve, Geir Kjetil Ferkingstad (2021). immuneML: an ecosystem for machine learning analysis of adaptive immune receptor repertoires. BioRxiv. ISSN 0362-4331.
• Greiff, Victor & Sandve, Geir Kjetil Ferkingstad (2021). In silico proof of principle of machine learning-based antibody design at unconstrained scale . BioRxiv. ISSN 0362-4331.
• Greiff, Victor & Sandve, Geir Kjetil Ferkingstad (2021). One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction . BioRxiv. ISSN 0362-4331. doi: 10.1101/2021.07.06.451258.
• Akbar, Rahmad; Robert, Philippe Paul Auguste; Pavlović, Milena; Jeliazkov, Jeliazko R.; Snapkov, Igor & Slabodkin, Andrei [Show all 15 contributors for this article] (2021). A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding. Cell reports. ISSN 2211-1247. 34:108856(11), p. 1–21. doi: 10.1016/j.celrep.2021.108856. Full text in Research Archive
• Laustsen, Andreas H.; Greiff, Victor; Karatt-Vellatt, Aneesh; Muyldermans, Serge & Jenkins, Timothy P. (2021). Animal Immunization, in Vitro Display Technologies, and Machine Learning for Antibody Discovery. Trends in Biotechnology. ISSN 0167-7799. 39(12), p. 1263–1273. doi: 10.1016/j.tibtech.2021.03.003. Full text in Research Archive
• Riedel, René; Addo, Richard; Ferreira-Gomes, Marta; Heinz, Gitta Anne; Heinrich, Frederik & Kummer, Jannis [Show all 33 contributors for this article] (2020). Discrete populations of isotype-switched memory B lymphocytes are maintained in murine spleen and bone marrow. Nature Communications. ISSN 2041-1723. 11(1). doi: 10.1038/s41467-020-16464-6.
• Fallet, Bénédict; Hao, Yi; Florova, Marianna; Cornille, Karen; de los Aires, Alba Verge & Girelli Zubani, Giulia [Show all 15 contributors for this article] (2020). Chronic viral infection promotes efficient germinal center B cell responses. Cell reports. ISSN 2211-1247. 30(4), p. 1013–1026. doi: 10.1016/j.celrep.2019.12.023. Full text in Research Archive
• Kräutler, Nike Julia; Yermanos, Alexander; Pedrioli, Alessandro; Welten, Suzanne P.M.; Lorgé, Dominique & Greczmiel, Ute [Show all 16 contributors for this article] (2020). Quantitative and Qualitative Analysis of Humoral Immunity Reveals Continued and Personalized Evolution in Chronic Viral Infection. Cell reports. ISSN 2211-1247. 30(4), p. 997–1012. doi: 10.1016/j.celrep.2019.12.088. Full text in Research Archive
• Yermanos, Alexander; Kräutler, Nike Julia; Pedrioli, Alessandro; Menzel, Ulrike; Greiff, Victor & Stadler, Tanja [Show all 8 contributors for this article] (2020). IgM Antibody Repertoire Fingerprints in Mice Are Personalized but Robust to Viral Infection Status. Frontiers in Cellular and Infection Microbiology. ISSN 2235-2988. 10:254, p. 1–13. doi: 10.3389/fcimb.2020.00254. Full text in Research Archive
• Yermanos, Alexander; Dounas, Andreas; Greiff, Victor; Stadler, Tanja; Oxenius, Annette & Reddy, Sai T. (2020). Inter- and intraspecies comparison of phylogenetic fingerprints and sequence diversity of immunoglobulin variable genes. Immunogenetics. ISSN 0093-7711. 72(5), p. 279–294. doi: 10.1007/s00251-020-01164-8. Full text in Research Archive
• Amoriello, Roberta; Greiff, Victor; Aldinucci, Alessandra; Bonechi, Elena; Carnasciali, Alberto & Peruzzi, Benedetta [Show all 12 contributors for this article] (2020). The TCR Repertoire Reconstitution in Multiple Sclerosis: Comparing One-Shot and Continuous Immunosuppressive Therapies. Frontiers in Immunology. ISSN 1664-3224. 11:559, p. 1–19. doi: 10.3389/fimmu.2020.00559. Full text in Research Archive
• Li, Hai; Limenitakis, Julien P.; Greiff, Victor; Yilmaz, Bahtiyar; Schären, Olivier & Urbaniak, Camilla [Show all 15 contributors for this article] (2020). Mucosal or systemic microbiota exposures shape the B cell repertoire. Nature. ISSN 0028-0836. 584(7820), p. 274–278. doi: 10.1038/s41586-020-2564-6. Full text in Research Archive
• Greiff, Victor; Yaari, Gur & Cowell, Lindsay G. (2020). Mining adaptive immune receptor repertoires for biological and clinical information using machine learning. Current Opinion in Systems Biology. ISSN 2452-3100. 24, p. 109–119. doi: 10.1016/j.coisb.2020.10.010.
• Smakaj, Erand; Babrak, Lmar; Ohlin, Mats; Shugay, Mikhail; Briney, Bryan & Tosoni, Deniz [Show all 16 contributors for this article] (2020). Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences. Bioinformatics. ISSN 1367-4803. 36(6), p. 1731–1739. doi: 10.1093/bioinformatics/btz845. Full text in Research Archive
• Weber, Cédric R.; Akbar, Rahmad; Yermanos, Alexander; Pavlovic, Milena; Snapkov, Igor & Sandve, Geir Kjetil [Show all 8 contributors for this article] (2020). immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking. Bioinformatics. ISSN 1367-4803. 36(11), p. 3594–3596. doi: 10.1093/bioinformatics/btaa158. Full text in Research Archive
• Bartolomé Casado, Raquel; Landsverk, Ole J. B.; Chauhan, Sudhir Kumar; Richter, Lisa Maria; Phung, Danh & Greiff, Victor [Show all 18 contributors for this article] (2019). Resident memory CD8 T cells persist for years in human small intestine. Journal of Experimental Medicine (JEM). ISSN 0022-1007. 216(10), p. 2412–2426. doi: 10.1084/jem.20190414. Full text in Research Archive
• Miho, Enkelejda; Roskar, Rok; Greiff, Victor & Reddy, Sai T. (2019). Large-scale network analysis reveals the sequence space architecture of antibody repertoires. Nature Communications. ISSN 2041-1723. 10(1). doi: 10.1038/s41467-019-09278-8. Full text in Research Archive
• Tomescu-Baciu, Alina; Johansen, Jorunn; Holmøy, Trygve; Greiff, Victor; Stensland, Maria & De Souza, Gustavo Antonio [Show all 8 contributors for this article] (2019). Persistence of intrathecal oligoclonal B cells and IgG in multiple sclerosis. Journal of Neuroimmunology. ISSN 0165-5728. 333:576966, p. 1–7. doi: 10.1016/j.jneuroim.2019.576966. Full text in Research Archive
• Brown, Alex; Snapkov, Igor; Akbar, Rahmad; Pavlovic, Milena; Miho, Enkelejda & Sandve, Geir Kjetil [Show all 7 contributors for this article] (2019). Augmenting adaptive immunity: progress and challenges in the quantitative engineering and analysis of adaptive immune receptor repertoires. Molecular Systems Design & Engineering. ISSN 2058-9689. 4(4), p. 701–736. doi: 10.1039/c9me00071b.
• Ohlin, Mats; Scheepers, Cathrine; Corcoran, Martin; Lees, William D.; Busse, Christian E. & Bagnara, Davide [Show all 25 contributors for this article] (2019). Inferred allelic variants of immunoglobulin receptor genes: A system for their evaluation, documentation, and naming. Frontiers in Immunology. ISSN 1664-3224. 10:435, p. 1–13. doi: 10.3389/fimmu.2019.00435. Full text in Research Archive
• Mason, Derek M; Weber, Cédric R.; Parola, Cristina; Meng, Simon M; Greiff, Victor & Kelton, William [Show all 7 contributors for this article] (2018). High-throughput antibody engineering in mammalian cells by CRISPR/Cas9-mediated homology-directed mutagenesis. Nucleic Acids Research (NAR). ISSN 0305-1048. 46(14), p. 7436–7449. doi: 10.1093/nar/gky550.
• Miho, Enkelejda; Yermanos, Alexander; Weber, Cédric R.; Berger, Christoph T; Reddy, Sai T. & Greiff, Victor (2018). Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires. Frontiers in Immunology. ISSN 1664-3224. 9: 224, p. 1–15. doi: 10.3389/fimmu.2018.00224. Full text in Research Archive
• Yermanos, Alexander; Greiff, Victor; Krautler, Nike Julia; Menzel, Ulrike; Dounas, Andreas & Miho, Enkelejda [Show all 9 contributors for this article] (2017). Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim) . Bioinformatics. ISSN 1367-4803. doi: 10.1093/bioinformatics/btx533.

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• Huang, Yu-Ning; Peng, Kerui; Popejoy, Alice B.; Hu, Jieting; Nowicki, Theodore Scott & Gold, Stefan M. [Show all 13 contributors for this article] (2021). Ancestral diversity is limited in published T cell receptor sequencing studies. Immunity. ISSN 1074-7613. 54(10), p. 2177–2179. doi: 10.1016/j.immuni.2021.09.015.
• Greiff, Victor (2021). Development of Machine Learning Methods for the Analysis, Prediction and Generation of Antibody Repertoires.
• Greiff, Victor (2021). Machine-learning-based design of antibody therapeutics.
• Greiff, Victor (2021). Latest techniques in validation of computational drug discovery.
• Greiff, Victor (2021). Computational and machine learning approaches for identifying antigen-specific information in adaptive immune receptor repertoires.
• Greiff, Victor (2021). Quantifying the specificity of adaptive immunity.
• Greiff, Victor (2021). Introduction to computational adaptive immune receptor repertoire (AIRR) immunogenomics.
• Greiff, Victor (2021). Future perspectives: from protein structure to function.
• Greiff, Victor (2021). Steps in data processing and analysis of adaptive immune receptor repertoires: best practices, pitfalls, and future directions.
• Greiff, Victor (2021). Mining the rules of adaptive immune repertoires in health and disease.
• Greiff, Victor (2021). Quantifying the specificity of adaptive immunity.
• Greiff, Victor (2021). Quantifying the specificity of adaptive immunity.
• Widrich, Michael; Schäfl, Bernhard; Pavlović, Milena; Ramsauer, Hubert; Gruber, Lukas & Holzleitner, Markus [Show all 11 contributors for this article] (2020). Modern Hopfield Networks and Attention for Immune Repertoire Classification. Show summary

  A central mechanism in machine learning is to identify, store, and recognize patterns. How to learn, access, and retrieve such patterns is crucial in Hopfield networks and the more recent transformer architectures. We show that the attention mechanism of transformer architectures is actually the update rule of modern Hopfield networks that can store exponentially many patterns. We exploit this high storage capacity of modern Hopfield networks to solve a challenging multiple instance learning (MIL) problem in computational biology: immune repertoire classification. In immune repertoire classification, a vast number of immune receptors are used to predict the immune status of an individual. This constitutes a MIL problem with an unprecedentedly massive number of instances, two orders of magnitude larger than currently considered problems, and with an extremely low witness rate. Accurate and interpretable machine learning methods solving this problem could pave the way towards new vaccines and therapies, which is currently a very relevant research topic intensified by the COVID-19 crisis. In this work, we present our novel method DeepRC that integrates transformer-like attention, or equivalently modern Hopfield networks, into deep learning architectures for massive MIL such as immune repertoire classification. We demonstrate that DeepRC outperforms all other methods with respect to predictive performance on large-scale experiments including simulated and real-world virus infection data and enables the extraction of sequence motifs that are connected to a given disease class. Source code and datasets: https://github.com/ml-jku/DeepRC.

• Greiff, Victor (2020). Systems immunology of adaptive immune receptor repertoires:  Deciphering immunological variation and specificity.
• Greiff, Victor (2020). Deep-learning based prediction of antibody-antigen interaction.
• Greiff, Victor (2020). Machine learning on sequence and structural adaptive immune receptor repertoire (AIRR) data .
• Greiff, Victor (2020). Quantifying the specificity of the adaptive immune response on the repertoire and sequence level.
• Greiff, Victor (2020). Systems immunology of immune receptor repertoires: Deciphering immunological specificity.
• Greiff, Victor (2020). Methods for mining the adaptive immune repertoire for SARS-CoV-2 diagnostics and therapeutics.
• Chain, Benny; Greiff, Victor; Textor, Johannes & Yaari, Gur (2019). Editorial: Methods and Applications of Computational Immunology. Frontiers in Immunology. ISSN 1664-3224. 10. doi: 10.3389/fimmu.2019.02818.

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