Microfluidic tools for connecting single-cell optical and gene expression phenotype

مرکز و کتابخانه مطالعات اسلامی به زبان های اروپایی

منو

" Microfluidic tools for connecting single-cell optical and gene expression phenotype "
Zhang, Jesse Qiuxu Abate, Adam

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	898116
Doc. No	:	TL0dk6p88m
Main Entry	:	Serrano Careaga, Jesus Antonio
Title & Author	:	Microfluidic tools for connecting single-cell optical and gene expression phenotype\ Zhang, Jesse QiuxuAbate, Adam
Date	:	2020
student score	:	2020
Abstract	:	The single cell is the fundamental unit of biology. Understanding how the identity of individual cells in multicellular organisms contribute to their function remains a key question in Biology. Traditionally, most observations of cells were made through imaging-based techniques. Today, advances in Next Generation Sequencing have led to the widespread adoption of sequencing-based techniques for investigating the genotype and phenotype at single-cell resolution. Microfluidics, including droplet-based microfluidics, have been instrumental in the most successful commercial single-cell genomics platforms. Integrating sequencing and imaging techniques will provide additional information than either of the techniques alone. Both single-cell imaging and genomics techniques measure orthogonal targets, and when combined reveal additional insights into cellular function. However, when performing sequential single-cell assays, there currently exists a tradeoff between throughput and information content. This dissertation will describe progress made towards reducing that gap. I will describe novel microfluidic platforms and techniques and applications involving integrating single-cell sequencing and optical measurements at high throughput. The microfluidics tools that will be discussed in this Dissertation aim to be a platform for performing single-cell multi-parameter and multi-omics techniques that will help further our understanding of cellular identity and how genotype informs phenotype at the single-cell level.
Added Entry	:	Zhang, Jesse Qiuxu
Added Entry	:	UCSF