Lys Sanz Moreta

Lys Sanz Moreta

PhD Student, Postdoc, Guest Researcher

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    ORCID: 0000-0003-1580-539X

    Publication year:
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    1. Published

      A Probabilistic Programming Approach to Protein Structure Superposition

      Sanz Moreta, Lys, Al-Sibahi, A. S., Theobald, D., Bullock, W., Rommes, B. N., Manoukian, A. & Hamelryck, Thomas Wim, 2019, 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2019. Baruzzo, G., Daberdaku, S., Di Camillo, B., Furini, S., Giordano, E. D. & Nicosia, G. (eds.). IEEE, 5 p. 8791469

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    2. Published

      Link Your Sites (LYS) Scripts: Automated Search of Protein Structures and Mapping of Sites Under Positive Selection Detected by PAML

      Sanz Moreta, Lys & Rodrigues da Fonseca, Rute Andreia, 2020, In: Evolutionary Biology. 47, 3, p. 240-245 6 p.

      Research output: Contribution to journal › Journal article › Research › peer-review

    3. Published

      Bayesian protein superposition using Hamiltonian Monte Carlo

      Sanz Moreta, Lys, Al-Sibahi, A. S. & Hamelryck, Thomas Wim, Oct 2020, Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020. IEEE, p. 1-11 9288019

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    4. Published

      Deep Probabilistic Programming Applied Protein Superposition: Protein Structure Prediction and Ancestral Sequence Resurrection

      Sanz Moreta, Lys, 2022, Department of Computer Science, Faculty of Science, University of Copenhagen. 138 p.

      Research output: Book/Report › Ph.D. thesis › Research

    5. Published

      Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model

      Thygesen, Christian Bahne, Al-Sibahi, A. S., Steenmanns, C. S., Sanz Moreta, Lys, Sørensen, A. B. & Hamelryck, Thomas Wim, 2021, International Conference on Machine Learning, 18-24 July 2021, Virtual. PMLR, p. 10258-10267 (Proceedings of Machine Learning Research, Vol. 139).

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    ID: 195752153