Search Results - "Quadrini, Michela"

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  1. 1

    Structural relation matching: an algorithm to identify structural patterns into RNAs and their interactions by Quadrini, Michela

    Published in Journal of integrative bioinformatics (31-05-2021)
    “…RNA molecules play crucial roles in various biological processes. Their three-dimensional configurations determine the functions and, in turn, influences the…”
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    Journal Article
  2. 2

    Automatic generation of pseudoknotted RNAs taxonomy by Quadrini, Michela, Tesei, Luca, Merelli, Emanuela

    Published in BMC bioinformatics (15-06-2023)
    “…The ability to compare RNA secondary structures is important in understanding their biological function and for grouping similar organisms into families by…”
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    Journal Article
  3. 3

    Hierarchical representation for PPI sites prediction by Quadrini, Michela, Daberdaku, Sebastian, Ferrari, Carlo

    Published in BMC bioinformatics (20-03-2022)
    “…Protein-protein interactions have pivotal roles in life processes, and aberrant interactions are associated with various disorders. Interaction site…”
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  4. 4

    An algebraic language for RNA pseudoknots comparison by Quadrini, Michela, Tesei, Luca, Merelli, Emanuela

    Published in BMC bioinformatics (18-04-2019)
    “…RNA secondary structure comparison is a fundamental task for several studies, among which are RNA structure prediction and evolution. The comparison can…”
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  5. 5

    A Spatial Logic for Simplicial Models by Loreti, Michele, Quadrini, Michela

    Published in Logical methods in computer science (01-01-2023)
    “…Collective Adaptive Systems often consist of many heterogeneous components typically organised in groups. These entities interact with each other by adapting…”
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    Journal Article
  6. 6

    Exploiting the Role of Features for Antigens-Antibodies Interaction Site Prediction by Quadrini, Michela, Ferrari, Carlo

    “…Antibodies are a class of proteins that recognize and neutralize pathogens by binding to their antigens. They are the most significant category of…”
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  7. 7

    ASPRAlign: a tool for the alignment of RNA secondary structures with arbitrary pseudoknots by Quadrini, Michela, Tesei, Luca, Merelli, Emanuela

    Published in Bioinformatics (01-06-2020)
    “…Abstract Summary Current methods for comparing RNA secondary structures are based on tree representations and exploit edit distance or alignment algorithms…”
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  8. 8

    libmg: A Python library for programming graph neural networks in μG by Belenchia, Matteo, Corradini, Flavio, Quadrini, Michela, Loreti, Michele

    Published in Science of computer programming (01-12-2024)
    “…Graph neural networks have proven their effectiveness across a wide spectrum of graph-based tasks. Despite their successes, they share the same limitations as…”
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  9. 9

    Stress detection with encoding physiological signals and convolutional neural network by Quadrini, Michela, Capuccio, Antonino, Falcone, Denise, Daberdaku, Sebastian, Blanda, Alessandro, Bellanova, Luca, Gerard, Gianluca

    Published in Machine learning (01-08-2024)
    “…Stress is a significant and growing phenomenon in the modern world that leads to numerous health problems. Robust and non-invasive method developments for…”
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  10. 10

    Sibilla: A tool for reasoning about collective systems by Del Giudice, Nicola, Matteucci, Lorenzo, Quadrini, Michela, Rehman, Aniqa, Loreti, Michele

    Published in Science of computer programming (01-07-2024)
    “…Formal approaches and tools have been defined, implemented and successfully applied to support the design and development of Collective Adaptive Systems. These…”
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    Journal Article
  11. 11

    A Spatial Logic for Simplicial Models by Loreti, Michele, Quadrini, Michela

    Published 25-07-2023
    “…Logical Methods in Computer Science, Volume 19, Issue 3 (July 26, 2023) lmcs:8576 Collective Adaptive Systems often consist of many heterogeneous components…”
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    Journal Article
  12. 12

    The $\mu\mathcal{G}$ Language for Programming Graph Neural Networks by Belenchia, Matteo, Corradini, Flavio, Quadrini, Michela, Loreti, Michele

    Published 12-07-2024
    “…Graph neural networks form a class of deep learning architectures specifically designed to work with graph-structured data. As such, they share the inherent…”
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