The analysis of cellular states
Abstract/Contents
- Abstract
- Cellular state is an old concept. However, scientists have only recently begun the systematic manipulation of cells to characterize and understand the functions of myriad states. As biotechnology advances enable innovative and large-scale measurements on cellular components, new biostatistical tools are required to make sense of the increased data size and complexity, which in turn augment our knowledge of cellular states. In this dissertation, I discuss my contributions to the study of cellular states from the theory and computation angles: 1) modeling and inference of regulatory gene networks with systems of nonlinear deterministic and stochastic differential equations; 2) partition-assisted clustering analysis of high-dimensional single-cell mass cytometry data; and 3) the alignment of subpopulations of cells across cytometry samples by similarity in the associated network structures. These contributions cement a platform that furthers the discussion of cellular states by framing it in both mechanistic and quantitative terms. This platform adds layers of biostatistical knowledge to Biosciences and enhances the discovery of cellular state properties.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2017 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Li, Ye Henry |
|---|---|
| Associated with | Stanford University, Department of Structural Biology. |
| Primary advisor | Levitt, Michael, 1947- |
| Primary advisor | Wong, Wing Hung |
| Thesis advisor | Levitt, Michael, 1947- |
| Thesis advisor | Wong, Wing Hung |
| Thesis advisor | Nolan, Garry P |
| Thesis advisor | Sabatti, Chiara |
| Advisor | Nolan, Garry P |
| Advisor | Sabatti, Chiara |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Ye Henry Li. |
|---|---|
| Note | Submitted to the Department of Structural Biology. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Ye Li
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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