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Claudio Mirabello

Principal Research Engineer, Docent

Publications

2024

Claudio Mirabello, Björn Wallner (2024) DockQ v2: improved automatic quality measure for protein multimers, nucleic acids, and small molecules Bioinformatics, Vol. 40, Article btae586 (Article in journal) Continue to DOI
Inga Petersen, Ana Godec, Farahnaz Ranjbarian, Anders Hofer, Claudio Mirabello, Greta Hultqvist (2024) A charged tail on anti-a-Synuclein antibodies does not enhance their affinity to a-Synuclein fibrils PLOS ONE, Vol. 19, Article e0308521 (Article in journal) Continue to DOI
Johan Wallerstein, Xiao Han, Maria Levkovets, Dmitry Lesovoy, Daniel Malmodin, Claudio Mirabello, Bjoern Wallner, Renhua Sun, Tatyana Sandalova, Peter Agback, Goran Karlsson, Adnane Achour, Tatiana Agback, Vladislav Orekhov (2024) Insights into mechanisms of MALT1 allostery from NMR and AlphaFold dynamic analyses Communications Biology, Vol. 7, Article 868 (Article in journal) Continue to DOI
Nora Bergfeldt, Emrah Kirdok, Nikolay Oskolkov, Claudio Mirabello, Per Unneberg, Helena Malmstrom, Magdalena Fraser, Federico Sanchez-Quinto, Roger Jorgensen, Birgitte Skar, Kerstin Liden, Mattias Jakobsson, Jan Stora, Anders Goetherstrom (2024) Identification of microbial pathogens in Neolithic Scandinavian humans Scientific Reports, Vol. 14, Article 5630 (Article in journal) Continue to DOI

2023

Tina Sarén, Mohanraj Ramachandran, Gustav Gammelgård, Tanja Lövgren, Claudio Mirabello, Åsa K. Björklund, Kristina Wikström, Jamileh Hashemi, Eva Freyhult, Håkan Ahlström, Rose-Marie Amini, Hans Hagberg, Angelica Loskog, Gunilla Enblad, Magnus Essand (2023) Single-Cell RNA Analysis Reveals Cell-Intrinsic Functions of CAR T Cells Correlating with Response in a Phase II Study of Lymphoma Patients Clinical Cancer Research, Vol. 29, p. 4139-4152 (Article in journal) Continue to DOI

News

Two men in white lab coats with a computer in a lab.

Improving Alphafold to predict very large proteins

The AI tool Alphafold has been improved so that it can now predict the shape of very large and complex protein structures. Linköping University researchers have also succeeded in integrating experimental data into the tool.

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