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Ron Weiss

Researcher at Massachusetts Institute of Technology

Publications -  301
Citations -  110805

Ron Weiss is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Synthetic biology & Speech synthesis. The author has an hindex of 82, co-authored 292 publications receiving 89189 citations. Previous affiliations of Ron Weiss include French Institute for Research in Computer Science and Automation & Google.

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Artificial cell-cell communication in yeast Saccharomyces cerevisiae using signaling elements from Arabidopsis thaliana.

TL;DR: Two artificial cell-cell communication systems in yeast were developed and analyzed and integrated Arabidopsis thaliana signal synthesis and receptor components with yeast endogenous protein phosphorylation elements and new response promoters resulted in population density–dependent gene expression and quorum sensing.
Posted ContentDOI

Highly-efficient Cas9-mediated transcriptional programming

TL;DR: The development of an improved transcriptional regulator through the rational design of a tripartite activator, VP64-p65-Rta (VPR), fused to Cas9 is described and its utility in activating expression of endogenous coding and non-coding genes, targeting several genes simultaneously and stimulating neuronal differentiation of induced pluripotent stem cells (iPSCs).
Posted Content

VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking.

TL;DR: In this paper, a speaker recognition network that produces speaker-discriminative embeddings and a spectrogram masking network that takes both noisy spectrogram and speaker embedding as input, and produces a mask.
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CRISPR transcriptional repression devices and layered circuits in mammalian cells

TL;DR: In this paper, a modular transcriptional repression architecture based on clustered regularly interspaced palindromic repeats (CRISPR) system was presented for regulated expression of guide RNAs in human cells.
Posted Content

Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model.

TL;DR: This paper presents Tacotron, an end- to-end generative text-to-speech model that synthesizes speech directly from characters, and presents several key techniques to make the sequence-tosequence framework perform well for this challenging task.