Author

Anna Canaccini

University of Siena

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetic & Genomic Medicine· 3

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:whole-exome sequencing· 3 Research Focus:differential expression· 2 Approach:machine learning (classical)· 2 Research Focus:GWAS / association mapping· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Agnese Verzuri· 3 shared Agostino OgnibeneiD· 3 shared Agostino RivaiD· 3 shared Alessandra VergoriiD· 3 shared Alice Donati· 3 shared Andrea AntinoriiD· 3 shared Andrea CossarizzaiD· 3 shared Andrea Tommasi· 3 shared

Activity by Year

2020-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersGenetic & Genomic Medicine

Agnese Verzuri

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3 papers

Recent·Most cited

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity.

Chiara Fallerini, Nicola Picchiotti, Margherita Baldassarri, Kristina Zguro, Sergio Daga, Francesca Fava, Elisa Benetti, Sara Amitrano, Mirella Bruttini, Maria Palmieri, Susanna Croci, Mirjam Lista, Giada Beligni, Floriana Valentino, Ilaria Meloni, , Pier Giorgio Scotton

The paper develops a machine learning model to predict COVID-19 severity using exonic variants from whole exome sequencing data, finding that variants across all frequency categories contribute to severity.

Human Genetics · Dec 10, 2021Peer-reviewedGenetic & Genomic Medicine

Shorter androgen receptor polyQ alleles protect against life-threatening COVID-19 disease in males.

Margherita Baldassarri, Nicola Picchiotti, Francesca Fava, Chiara Fallerini, Elisa Benetti, Sergio Daga, Floriana Valentino, Gabriella Doddato, Simone Furini, Annarita Giliberti, Rossella Tita, Sara Amitrano, Mirella Bruttini, Susanna Croci, Ilaria Meloni, , Francesca Andretta

The paper identifies shorter androgen receptor polyQ alleles as protective against severe COVID-19 in males using machine learning on whole-exome sequencing data from the GEN-COVID cohort.

EBioMedicine · Feb 26, 2021Peer-reviewedGenetic & Genomic Medicine

ACE2 gene variants may underlie interindividual variability and susceptibility to COVID-19 in the Italian population

Elisa Benetti, Rossella Tita, Ottavia Spiga, Andrea Ciolfi, Giovanni Birolo, Alessandro Bruselles, Gabriella Doddato, Annarita Giliberti, Caterina Marconi, Francesco Musacchia, Tommaso Pippucci, Annalaura Torella, Alfonso Trezza, Floriana Valentino, Margherita Baldassarri, , Carmelo Piscopo

The paper identifies ACE2 gene variants associated with interindividual variability in COVID-19 susceptibility in the Italian population using whole-exome-sequencing data.

European Journal of Human Genetics · Jul 17, 2020Peer-reviewedGenetic & Genomic Medicine