Tools for large and detailed experiments in genomics and tissue development

In this dissertation I present algorithmic and data representation advances in genomics as well as tools for a new bioinformatic approach to mammalian cell culture experiments which I call highly instrumented cell culture. The first section deals with fast variants of the forward algorithm for the L...

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Main Author: Rosen, Yohei Maurice
Other Authors: Haussler, David
Format: Other/Unknown Material
Language:English
Published: eScholarship, University of California 2022
Subjects:
Online Access:https://escholarship.org/uc/item/7wj3w73z
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spelling ftcdlib:oai:escholarship.org:ark:/13030/qt7wj3w73z 2023-05-15T15:52:59+02:00 Tools for large and detailed experiments in genomics and tissue development Rosen, Yohei Maurice Haussler, David 2022-01-01 https://escholarship.org/uc/item/7wj3w73z en eng eScholarship, University of California qt7wj3w73z https://escholarship.org/uc/item/7wj3w73z CC-BY-NC-ND CC-BY-NC-ND Bioinformatics etd 2022 ftcdlib 2022-10-31T18:33:32Z In this dissertation I present algorithmic and data representation advances in genomics as well as tools for a new bioinformatic approach to mammalian cell culture experiments which I call highly instrumented cell culture. The first section deals with fast variants of the forward algorithm for the Li and Stephens copying model of haplotypes derived from a population. I introduce a direct optimization of the Li and Stephens model forward algorithm which performs the identical calculation, without any approximations, but achieves this in average case sublinear time. This is an improvement over the classical algorithm which is at best linear time. I achieve this by using a sparse representation of the population haplotypes and by introducing an efficient lazy evaluation scheme. I also introduce a generalization of the recombination modeling component of the Li and Stephens model which operates on haplotypes and populations encoded in variation graphs. The second section deals with algebraic representations of genetic sites in variation graphs. I introduce the concept of the bundle, a motif in bidirected graphs which leads to a well defined concept of adjacency of sets of nodes. This allows a granular decomposition of the graph into sites which extends prior work on ultrabubbles and snarls previously reported by Paten et al. Lastly, I introduce the concept of highly instrumented cell culture and some technologies to enable it. I demonstrate a low-cost, robust, arbitrarily scalable microscope array for simultaneous parallel continuous time-series microscopy. I demonstrate new approaches to rapid prototyping of labware and fluidic actuators. I also demonstrate principles and implementation of incubator-free cell culture, which is my approach to cell culture in media containing carbonic acid-carbonate-bicarbonate buffer systems without using any carbon dioxide rich gas chamber. I finally describe how these technologies integrate together to enable the creation of highly instrumented, automated, data rich biology ... Other/Unknown Material Carbonic acid University of California: eScholarship
institution Open Polar
collection University of California: eScholarship
op_collection_id ftcdlib
language English
topic Bioinformatics
spellingShingle Bioinformatics
Rosen, Yohei Maurice
Tools for large and detailed experiments in genomics and tissue development
topic_facet Bioinformatics
description In this dissertation I present algorithmic and data representation advances in genomics as well as tools for a new bioinformatic approach to mammalian cell culture experiments which I call highly instrumented cell culture. The first section deals with fast variants of the forward algorithm for the Li and Stephens copying model of haplotypes derived from a population. I introduce a direct optimization of the Li and Stephens model forward algorithm which performs the identical calculation, without any approximations, but achieves this in average case sublinear time. This is an improvement over the classical algorithm which is at best linear time. I achieve this by using a sparse representation of the population haplotypes and by introducing an efficient lazy evaluation scheme. I also introduce a generalization of the recombination modeling component of the Li and Stephens model which operates on haplotypes and populations encoded in variation graphs. The second section deals with algebraic representations of genetic sites in variation graphs. I introduce the concept of the bundle, a motif in bidirected graphs which leads to a well defined concept of adjacency of sets of nodes. This allows a granular decomposition of the graph into sites which extends prior work on ultrabubbles and snarls previously reported by Paten et al. Lastly, I introduce the concept of highly instrumented cell culture and some technologies to enable it. I demonstrate a low-cost, robust, arbitrarily scalable microscope array for simultaneous parallel continuous time-series microscopy. I demonstrate new approaches to rapid prototyping of labware and fluidic actuators. I also demonstrate principles and implementation of incubator-free cell culture, which is my approach to cell culture in media containing carbonic acid-carbonate-bicarbonate buffer systems without using any carbon dioxide rich gas chamber. I finally describe how these technologies integrate together to enable the creation of highly instrumented, automated, data rich biology ...
author2 Haussler, David
format Other/Unknown Material
author Rosen, Yohei Maurice
author_facet Rosen, Yohei Maurice
author_sort Rosen, Yohei Maurice
title Tools for large and detailed experiments in genomics and tissue development
title_short Tools for large and detailed experiments in genomics and tissue development
title_full Tools for large and detailed experiments in genomics and tissue development
title_fullStr Tools for large and detailed experiments in genomics and tissue development
title_full_unstemmed Tools for large and detailed experiments in genomics and tissue development
title_sort tools for large and detailed experiments in genomics and tissue development
publisher eScholarship, University of California
publishDate 2022
url https://escholarship.org/uc/item/7wj3w73z
genre Carbonic acid
genre_facet Carbonic acid
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op_rights CC-BY-NC-ND
op_rightsnorm CC-BY-NC-ND
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