Federica De Paoli

ORCID: 0000-0002-8027-5666
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Genomics and Rare Diseases
  • Genomic variations and chromosomal abnormalities
  • Biomedical Text Mining and Ontologies
  • Epilepsy research and treatment
  • Genomics and Phylogenetic Studies
  • Diet and metabolism studies
  • Cancer Genomics and Diagnostics
  • Pneumocystis jirovecii pneumonia detection and treatment
  • Bioinformatics and Genomic Networks
  • Genetic Associations and Epidemiology
  • Neuroscience and Neuropharmacology Research
  • Anesthesia and Neurotoxicity Research
  • Blood disorders and treatments
  • CRISPR and Genetic Engineering
  • Immunodeficiency and Autoimmune Disorders
  • Neurological disorders and treatments
  • Ubiquitin and proteasome pathways
  • Cancer, Stress, Anesthesia, and Immune Response
  • Cancer-related Molecular Pathways
  • Pharmacological Effects and Toxicity Studies

Abstract Background A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing genome-wide. To aid the interpretation prioritization of vast number detected, computational methods proliferating. Knowing which tools most effective remains unclear. evaluate performance methods, to encourage innovation method development, we designed Critical...

10.1186/s40246-024-00604-w article EN cc-by Human Genomics 2024-04-29

Abstract The digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately interpreting and prioritizing combinations variants based on proband’s phenotypes family information can provide valuable assistance during process. We developed diVas, a hypothesis-driven machine learning approach that interprets genomic across different gene pairs. DiVas demonstrates strong performance both classifying causative within...

10.1093/nargab/lqaf029 article EN cc-by-nc NAR Genomics and Bioinformatics 2025-03-29

Abstract Motivation In the modern era of genomic research, scientific community is witnessing an explosive growth in volume published findings. While this abundance data offers invaluable insights, it also places a pressing responsibility on genetic professionals and researchers to stay informed about latest findings their clinical significance. Genomic variant interpretation currently facing challenge identifying most up-to-date relevant papers, while extracting meaningful information...

10.1093/bioinformatics/btae183 article EN cc-by Bioinformatics 2024-03-29

A major obstacle faced by rare disease families is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years, and causal variants are identified in under 50%. Rare Genomes Project (RGP) direct-to-participant research study on the utility of genome sequencing (GS) for diagnosis gene discovery. Families consented sharing sequence phenotype data with researchers, allowing development Critical Assessment Genome Interpretation (CAGI) community challenge, placing...

10.1101/2023.08.02.23293212 preprint EN cc-by-nc-nd medRxiv (Cold Spring Harbor Laboratory) 2023-08-04

Introduction. Shwachman-Diamond Syndrome (SDS) is an autosomal-recessive disorder characterized by neutropenia, pancreatic exocrine insufficiency, skeletal dysplasia, and increased risk for leukemic transformation. Biallelic mutations in the SBDS gene have been found about 90% of patients. The clinical spectrum SDS patients wide, variability has noticed between different patients, siblings, even within same patient over time. Herein, we present two siblings (UPN42 UPN43) carrying showing...

10.3390/genes13081314 article EN Genes 2022-07-23

Abstract Motivation The digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately interpreting and prioritizing combinations based on proband’s phenotypic profiles familial information can provide valuable assistance clinicians during process. Results We have developed diVas, a hypothesis-driven machine learning approach that effectively interpret genomic variants across different gene pairs. DiVas...

10.1101/2023.10.02.560464 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2023-10-03

The present clinical study was approved by the Review Board for Animals Care of University Parma prot N. 03/CESA /2023, which provided a consent to study: regulation (EU) no. 536/2014. (22A01712) (GU General Series n.65 18-03-2022); European Law (O.J. E.C. L 358/1 12/18/1986), and USA Laws (Animal Welfare Assurance No A5594-01, Department Health Human Services, USA). owners signed voluntary informed form prior dogs’ enrollment in study. Twenty female dogs, aged 1±1.5 months, weighing 16± 0.5...

10.20944/preprints202304.1270.v1 preprint EN 2023-04-30

Abstract Background Sudden death is the leading cause of mortality in medically refractory cases epilepsy. Younger persons with epilepsy (PWE), particularly those <40 years, have higher all-cause than without. However, data are conflicting about and burden cardiovascular disease (CVD) middle-aged PWE. Objective Determine sudden death-specific CVD PWE a population. Methods Using UK Biobank, we identified 7,786 (1.6%) participants diagnosis epilepsy; 566 individuals prior history stroke...

10.1101/2023.07.26.23293226 preprint EN cc-by-nc-nd medRxiv (Cold Spring Harbor Laboratory) 2023-07-28

In the modern era of genomic research, scientific community is witnessing an explosive growth in volume published findings. While this abundance data offers invaluable insights, it also places a pressing responsibility on genetic professionals and researchers to stay informed about latest findings their clinical significance. Genomic variant interpretation currently facing challenge identifying most up-to-date relevant papers, while extracting meaningful information accelerate process from...

10.20944/preprints202311.1130.v1 preprint EN 2023-11-17
Coming Soon ...