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Beverly L. Davidson

Researcher at Children's Hospital of Philadelphia

Publications -  410
Citations -  35019

Beverly L. Davidson is an academic researcher from Children's Hospital of Philadelphia. The author has contributed to research in topics: Gene silencing & RNA interference. The author has an hindex of 94, co-authored 391 publications receiving 33041 citations. Previous affiliations of Beverly L. Davidson include United States Department of Veterans Affairs & University of California, Los Angeles.

Papers
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Targeted Gene Silencing to Induce Permanent Sterility

TL;DR: This article discusses the subject of non-surgical method to induce sterility and provides a succinct account of previous experience with molecular reagents able to disrupt reproductive cyclicity when delivered to regions of the brain involved in the control of reproduction and molecular reagent able to ameliorate neuronal disease when delivered systemically using a novel approach of gene therapy.
Patent

Methods for producing and using in vivo pseudotyped retroviruses using envelope glycoproteins from lymphocytic choriomeningitis virus (LCMV)

TL;DR: In this paper, a pseudotyped retroviral vector that can transduce human and other cells is presented. But this vector does not express novel envelope glycoproteins.
Journal ArticleDOI

Author Correction: Lysosomal storage diseases.

TL;DR: In the version of the article originally published, in Figure 2 and the accompanying legend, LIMP 2 was incorrectly referred to as LIMP 1 and the article has now been corrected.
Journal ArticleDOI

Sonic Hedgehog Controls the Phenotypic Fate and Therapeutic Efficacy of Grafted Neural Precursor Cells in a Model of Nigrostriatal Neurodegeneration

TL;DR: These studies reveal core mechanisms fundamental to grafted NPC-based therapeutic effects, and delineate the particular contributions of two graft-expressed molecules, SHH and GDNF, in mediating midbrain dopamine neuron protection, and host plasticity after NPC transplantation.
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DeepRepeat: direct quantification of short tandem repeats on signal data from nanopore sequencing

TL;DR: DeepRepeat as mentioned in this paper converts ionic current signals into red-green-blue channels, thus transforming the repeat detection problem into an image recognition problem, and achieves higher accuracy in quantifying repeats in long-tandem repeats than competing methods.