Biomedical Engineering

Sharon Aviran

sharon aviran Assistant Professor

Office: 2319 GBSF

Phone: (530) 752-6978

Email: saviran@ucdavis.edu

Personal Education

Postdoctoral Fellowship in Computational Biology, UC Berkeley, 2013
Ph.D. in Electrical Engineering, UCSD, 2006

Affiliations

Biomedical Engineering Graduate Group
Applied Mathematics Graduate Group
Integrative Genetics and Genomics Graduate Group

Research Interests

Computational RNA Biology and Biomolecular Engineering

Recent advances in genomics, chemistry, and biotechnology have opened up new possibilities for studying RNA structure and dynamics at the genome scale and at unprecedented resolution and throughput. Our group develops computational and statistical methods for robust and efficient analysis of the information generated by such novel and emerging technologies and for utilizing it to better infer RNA dynamics and structure-function relationships. Another goal of our group is to develop tools that will assist the engineering of novel RNAs for a range of synthetic biology and therapeutic applications. Our work is at the interface between applied math, statistics, and biochemistry, and draws on tools from machine learning, probabilistic modeling, and optimization.

Selected Recent Publications

Aviran S and Pachter L (2014) Rational experiment design for sequencing-based RNA structure mapping. submitted.

Mortimer SA, Trapnell C*, Aviran S*, Pachter L, and Lucks JB (2012) SHAPE-Seq: high throughput RNA structure analysis. Current Protocols in Chemical Biology, 4, 275-299. (* Equal contribution)

Aviran S, Trapnell C, Lucks JB, Mortimer SA, Luo S, Schroth GP, Doudna JA, Arkin AP, and Pachter L (2011) Modeling and automation of sequencing-based characterization of RNA structure. Proc. of the National Academy of Sciences (PNAS), 108, 11069-11074.

Lucks JB, Mortimer SA, Trapnell C, Luo S, Aviran S, Schroth GP, Pachter L, Doudna JA, and Arkin AP (2011) Multiplexed RNA structure characterization with selective 2′-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq). Proc. of the National Academy of Sciences (PNAS), 108, 11063-11068.

Aviran S, Shah PS, Schaffer DV, and Arkin AP (2010) Computational models of HIV-1 resistance to gene therapy elucidate therapy design principles. PLoS Computational Biology, 6, e1000883.

Major Research Interests

Computational Biology, RNA Genomics, Synthetic Biology, RNA Structural Biology, Statistical Inference and Algorithms.

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