3 results match your criteria: "Genuity AI Research Institute[Affiliation]"
ATM-deficiency-induced microglial activation promotes neurodegeneration in ataxia-telangiectasia.
Cell Rep
January 2024
Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, MA 02115, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Electronic address:
While ATM loss of function has long been identified as the genetic cause of ataxia-telangiectasia (A-T), how it leads to selective and progressive degeneration of cerebellar Purkinje and granule neurons remains unclear. ATM expression is enriched in microglia throughout cerebellar development and adulthood. Here, we find evidence of microglial inflammation in the cerebellum of patients with A-T using single-nucleus RNA sequencing.
View Article and Find Full Text PDFIdentification of driver genes for critical forms of COVID-19 in a deeply phenotyped young patient cohort.
Sci Transl Med
January 2022
Laboratoire d'ImmunoRhumatologie Moléculaire, plateforme GENOMAX, INSERM (Institut de la Santé et de la Recherche Médicale) UMR_S 1109, Faculté de Médecine, Institut Thématique Interdisciplinaire (ITI) de Médecine de Précision de Strasbourg, Transplantex NG, Université de Strasbourg, 67085 Strasbourg, France.
Article Synopsis
- The study explores the unknown factors driving severe COVID-19 by examining a young patient cohort without major comorbidities, comparing critical and non-critical cases.
- Researchers used advanced techniques like whole-genome sequencing and artificial intelligence to analyze biological samples and found significant inflammatory responses and immune system alterations in critical patients.
- A specific gene signature was identified that distinguished critical cases and indicated that inhibiting the ADAM9 gene could reduce SARS-CoV-2 infection and replication, suggesting potential therapeutic options.
Quantum processor-inspired machine learning in the biomedical sciences.
Patterns (N Y)
June 2021
Computational Statistics and Bioinformatics Group, Genuity AI Research Institute, Genuity Science, 90 Canal Street, Suite 120, Boston, MA 02114, USA.
Recent advances in high-throughput genomic technologies coupled with exponential increases in computer processing and memory have allowed us to interrogate the complex molecular underpinnings of human disease from a genome-wide perspective. While the deluge of genomic information is expected to increase, a bottleneck in conventional high-performance computing is rapidly approaching. Inspired by recent advances in physical quantum processors, we evaluated several unconventional machine-learning (ML) strategies on actual human tumor data, namely "Ising-type" methods, whose objective function is formulated identical to simulated annealing and quantum annealing.
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