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Daniel G. Anderson

Researcher at Massachusetts Institute of Technology

Publications -  563
Citations -  71844

Daniel G. Anderson is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Medicine & Gene delivery. The author has an hindex of 121, co-authored 520 publications receiving 59724 citations. Previous affiliations of Daniel G. Anderson include Emory University & Harvard University.

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Knocking down barriers: advances in siRNA delivery

TL;DR: An update on the progress of RNAi therapeutics is provided and novel synthetic materials for the encapsulation and intracellular delivery of nucleic acids are highlighted.
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Non-viral vectors for gene-based therapy

TL;DR: The biological barriers to gene delivery in vivo are introduced and recent advances in material sciences, nanotechnology and nucleic acid chemistry that have yielded promising non-viral delivery systems are discussed, some of which are currently undergoing testing in clinical trials.
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Physical and mechanical properties of PLA, and their functions in widespread applications - A comprehensive review.

TL;DR: The main purpose of this review is to elaborate the mechanical and physical properties that affect PLA stability, processability, degradation, PLA-other polymers immiscibility, aging and recyclability, and therefore its potential suitability to fulfill specific application requirements.
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Delivery materials for siRNA therapeutics

TL;DR: An introduction to the biological challenges that siRNA delivery materials aim to overcome is provided, as well as a discussion of the way that the most effective and clinically advanced classes of si RNA delivery systems are designed to surmount these challenges.
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CRISPR-Cas9 Knockin Mice for Genome Editing and Cancer Modeling

TL;DR: In vivo as well as ex vivo genome editing using adeno-associated virus, lentivirus, or particle-mediated delivery of guide RNA in neurons, immune cells, and endothelial cells is demonstrated, suggesting that Cas9 mice empower a wide range of biological and disease modeling applications.