1. PortPred: exploiting deep learning embeddings of amino acid sequences for the identification of transporter proteins and their substrates
Marco Anteghini, Vitor AP Martins dos Santos, Edoardo Saccenti
[DOI: 10.1002/jcb.30490](https://doi.org/10.1002/jcb.30490)
2. Insights Into the Peroxisomal Protein Inventory of Zebrafish
Maki Kamoshita, Rechal Kumar, Marco Anteghini, Markus Kunze, Markus Islinger, Vítor Martins dos Santos, Michael Schrader
[DOI: 10.3389/fphys.2022.822509](https://doi.org/10.3389/fphys.2022.822509)
3. Easy sematification of bioassays
Marco Anteghini, Jennifer D'Souza, Vitor Martins dos Santos, Soeren Auer
[DOI: 10.1007/978-3-031-08421-8_14](https://link.springer.com/chapter/10.1007/978-3-031-08421-8_14)
4. SciBERT-based Semantification of Bioassays in the Open Research Knowledge Graph
Marco Anteghini, Jennifer D'Souza, Vitor Martins dos Santos, Soeren Auer
[arXiv: 2009.08801](https://arxiv.org/abs/2009.08801?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%253A+arxiv%252FQSXk+%2528ExcitingAds%2521+cs+updates+on+arXiv.org%2529)
5. In-Pero: Exploiting deep learning embeddings of protein sequences to predict the localisation of peroxisomal proteins
Marco Anteghini, Vitor Martins dos Santos, Edoardo Saccenti
[DOI: 10.1101/2021.01.18.427146v1](https://www.biorxiv.org/content/10.1101/2021.01.18.427146v1)
6. Thermodynamics and kinetics of the amyloid-β peptide revealed by Markov state models based on MD data in agreement with experiment
Arghadwip Paul, Suman Samantray, Marco Anteghini, Birgit Strodel
[DOI: 10.1101/2020.07.27.223487](https://doi.org/10.1101/2020.07.27.223487)
