Author

Lucia Guidugli

Rady Children's Institute for Genomic Medicine

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· 2

Signature Assays, Organisms & Methods

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Research Focus:variant calling· 2 Assay:whole-exome sequencing· 2 Assay:whole-genome sequencing· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Stephen Francis KingsmoreiD· 2 shared Alan H. BeggsiD· 1 shared Amanda Thomas‐WilsoniD· 1 shared Ana S.A. CoheniD· 1 shared André FrankeiD· 1 shared Anna SzutoiD· 1 shared Barry MooreiD· 1 shared Braden E. Boone· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Stephen Francis KingsmoreORCID

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2 papers

Recent·Most cited

The landscape of reported VUS in multi-gene panel and genomic testing: Time for a change

Heidi L. Rehm, Joseph T. Alaimo, Swaroop Aradhya, Pınar Bayrak‐Toydemir, Hunter D. Best, Rhonda C. Brandon, Jillian G. Buchan, Elizabeth Chao, Elaine Y. Chen, Jacob Clifford, Ana S.A. Cohen, Laura Kathleen Conlin, Soma Das, Kyle Davis, Daniela del Gaudio, , Stephen Francis Kingsmore

The paper analyzes VUS rates in genetic testing and finds lower rates in exome/genome sequencing compared to multi-gene panels, suggesting improvements in variant reporting practices.

Genetics in Medicine · Jul 30, 2023Peer-reviewedGenetic & Genomic Medicine

Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases

Francisco M. De La Vega, Shimul Chowdhury, Barry Moore, Erwin Frise, Jeanette J. McCarthy, Edgar Javier Hernandez, Terence C. Wong, Kiely N. James, Lucia Guidugli, Pankaj B. Agrawal, Casie A. Genetti, Catherine A. Brownstein, Alan H. Beggs, Britt-Sabina Löscher, André Franke, , Stephen Francis Kingsmore

GEM, an AI-based tool, ranks causal genes highly for rare genetic diseases, improving diagnostic efficiency and reducing manual effort.

Genome Medicine · Oct 13, 2021Peer-reviewedGenetic & Genomic Medicine