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Perturbing the Genome: From Bench to Biophysics


Chari, Tara Varada (2024) Perturbing the Genome: From Bench to Biophysics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/5drv-ma07.


In single-cell genomics, we can simultaneously assay hundreds of thousands of cells, their molecular contents, and how they respond to perturbation, from genetic knockouts to environmental changes. This thesis focuses on how to merge experimental and computational techniques to generate and analyze large-scale perturbation data for high-resolution systems biology. Beginning at the bench, we demonstrate how combining large-scale cell atlas surveys with multi-condition experimentation can illuminate the diversity of cell types across whole organisms and cellular strategies in response to environmental changes and perturbations. We then investigate the limitations of current practice in exploratory analysis, and strategies for determining preservation or distortion of biological insight by these data transformation and dimensionality reduction techniques. To address these limitations, we demonstrate how stochastic biophysical models can rewrite the way we interpret complex perturbation data, taking greater advantage of the diverse molecular measurements to develop biological hypotheses about DNA and RNA regulation in cellular function, development, and disease.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Computational Biology; Single-cell Genomics; Biophysics; Perturbation; Dimensionality Reduction
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Bioengineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Pachter, Lior S.
Thesis Committee:
  • Qian, Lulu (chair)
  • Murray, Richard M.
  • Anderson, David J.
  • Pachter, Lior S.
Defense Date:20 May 2024
Non-Caltech Author Email:tarachari3 (AT)
Funding AgencyGrant Number
Record Number:CaltechTHESIS:05292024-221741183
Persistent URL:
Related URLs:
URLURL TypeDescription adapted for ch. 5 adapated for ch. 3 adapted for ch. 6 paper: Spectral neural approximations for models of transcriptional dynamics paper: Biophysical modeling with variational autoencoders for bimodal, single-cell RNA sequencing data article: RNA velocity unraveled
Chari, Tara Varada0000-0002-6953-4313
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:16438
Deposited By: Tara Chari
Deposited On:31 May 2024 23:43
Last Modified:17 Jun 2024 16:37

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