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Stochastic Modeling Of Heterogeneous Low Input Gene Expression Linking Single Cell Probability Distributions To Transcription Mechanisms
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Book Synopsis Stochastic Modeling of Heterogeneous Low-Input Gene Expression: Linking Single-Cell Probability Distributions to Transcription Mechanisms by : Lisa Amrhein
Download or read book Stochastic Modeling of Heterogeneous Low-Input Gene Expression: Linking Single-Cell Probability Distributions to Transcription Mechanisms written by Lisa Amrhein and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Models of Biological Pattern Formation by : Hans Meinhardt
Download or read book Models of Biological Pattern Formation written by Hans Meinhardt and published by . This book was released on 1982 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Algorithm for the Stochastic Simulation of Gene Expression and Cell Population Dynamics by : Daniel A. Charlebois
Download or read book An Algorithm for the Stochastic Simulation of Gene Expression and Cell Population Dynamics written by Daniel A. Charlebois and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few years, it has been increasingly recognized that stochastic mechanisms play a key role in the dynamics of biological systems. Genetic networks are one example where molecular-level fluctuations are of particular importance. Here stochasticity in the expression of gene products can result in genetically identical cells in the same environment displaying significant variation in biochemical or physical attributes. This variation can influence individual and population-level fitness. In this thesis we first explore the background required to obtain analytical solutions and perform simulations of stochastic models of gene expression. Then we develop an algorithm for the stochastic simulation of gene expression and heterogeneous cell population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte Carlo approach to simulate the statistical characteristics of growing cell populations. This approach permits biologically realistic and computationally feasible simulations of environment and time-dependent cell population dynamics. The algorithm is benchmarked against steady-state and time-dependent analytical solutions of gene expression models, including scenarios when cell growth, division, and DNA replication are incorporated into the modelling framework. Furthermore, using the algorithm we obtain the steady-state cell size distribution of a large cell population, grown from a small initial cell population undergoing stochastic and asymmetric division, to the size distribution of a small representative sample of this population simulated to steady-state. These comparisons demonstrate that the algorithm provides an accurate and efficient approach to modelling the effects of complex biological features on gene expression dynamics. The algorithm is also employed to simulate expression dynamics within 'bet-hedging' cell populations during their adaption to environmental stress. These simulations indicate that the cell population dynamics algorithm provides a framework suitable for simulating and analyzing realistic models of heterogeneous population dynamics combining molecular-level stochastic reaction kinetics, relevant physiological details, and phenotypic variability and fitness.
Book Synopsis Inferring Properties of Transcription from Stochastic Gene Expression by : Marc Samuel Sherman
Download or read book Inferring Properties of Transcription from Stochastic Gene Expression written by Marc Samuel Sherman and published by . This book was released on 2016 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single-cell experiments reveal considerable fluctuations in the expression of both mRNA and protein. Among genetically identical cells, these fluctuations manifest as remarkably broad distributions of expression. What does the nature of stochastic expression intimate about the mechanisms underlying transcriptional regulation? To understand how specific cis-regulatory mechanisms manifest as noise in expression, we tackled two key methodological deficiencies: (1) a lack of assumption-free approaches for fitting mechanistic models to protein distributions, and (2) methods for isolating biochemical noise (intrinsic) from noise due to cellular environment (extrinsic). To fit the standard stochastic protein model without assumptions, we constrained a search algorithm with solutions to the model's higher order moments. The resulting algorithm enables efficient discovery of solution ensembles representing every kinetic scheme consistent with an observed protein distribution. I find that measurement of protein and mRNA degradation rates should permit estimation of the macroscopic rate constants governing gene ON-OFF transitions, transcription and translation from distribution shape alone. I also found that higher-order moments of intrinsic noise separate naturally from their extrinsic counterparts, in principle enabling intrinsic stochasticity to be estimated by comparing expression of strains containing a variable number of identical genes. To test both frameworks, we assembled S. cerevisiae strains expressing one or multiple copies of GFP reporter genes driven by the heat shock responsive promoter SSA1. In contrast to previous studies, we find that stochastic expression from SSA1 resists decomposition into intrinsic and extrinsic components. Degradation rates appear constant across the population, while transcription rates vary extensively with cellular volume, leading us to predict that a large fraction of noise arises from extrinsic mRNA fluctuations. Consistent with this hypothesis, perturbations to transcription rate dramatically impact the balance of protein noise. Together these data argue for models of stochastic expression that explicitly incorporate fluctuating inputs into transcription.
Book Synopsis Copy Number and Gene Expression by : Fang-Han Hsu
Download or read book Copy Number and Gene Expression written by Fang-Han Hsu and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The advances of high-throughput technologies, such as next-generation sequencing and microarrays, have rapidly improved the accessibility of molecular profiles in tumor samples. However, due to the immaturity of relevant theories, analyzing these data and systematically understanding the underlying mechanisms causing diseases, which are essential in the development of therapeutic applications, remain challenging. This dissertation attempts to clarify the effects of DNA copy number alterations (CNAs), which are known to be common mutations in genetic diseases, on steady- state gene expression values, time-course expression activities, and the effectiveness of targeted therapy. Assuming DNA copies operate as independent subsystems producing gene transcripts, queueing theory is applied to model the stochastic processes representing the arrival of transcription factors (TFs) and the departure of mRNA. The copy-number-gene-expression relationships are shown to be generally nonlinear. Based on the mRNA production rates of two transcription models, one corresponding to an unlimited state with prolific production and one corresponding to a restrictive state with limited production, the dynamic effects of CNAs on gene expression are analyzed. Simulations reveal that CNAs can alter the amplitudes of transcriptional bursting and transcriptional oscillation, suggesting the capability of CNAs to interfere with the regulatory signaling mechanism. With this finding, a string-structured Bayesian network that models a signaling pathway and incorporates the interference due to CNAs is proposed. Using mathematical induction, the upstream and downstream CNAs are found to have equal influence on drug effectiveness. Scoring functions for the detection of unfavorable CNAs in targeted therapy are consequently proposed. Rigorous experiments are keys to unraveling the etiology of genetic diseases such as cancer, and the proposed models can be applied to provide theory-supporting hypotheses for experimental design. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/149298
Book Synopsis A Toolset for Linking Phenotype and Gene Expression at the Single-cell Level by : Robert J. Kimmerling
Download or read book A Toolset for Linking Phenotype and Gene Expression at the Single-cell Level written by Robert J. Kimmerling and published by . This book was released on 2017 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of single-cell RNA-sequencing has led to a new degree of resolution in the characterization of complex, heterogeneous biological systems. However, existing methods are often limited in their ability to link these whole-transcriptome profiles with complimentary measurements of single-cell phenotype. In this thesis we present a microfluidic toolset which allows us to link a panel of single-cell phenotypic measurements - including lineage history, cell cycle stage, cell size, and growth rate - with their corresponding transcriptional profiles. Using a microfluidic platform that employs an array of hydrodynamic traps to capture and culture single cells for multiple generations we measured single-cell growth kinetics, lineage hierarchies and cell cycle stage. By subsequently releasing individual cells from this device for downstream scRNA-seq we were able to generate whole-transcriptome profiles of primary, activated murine CD8+ T cell and lymphocytic leukemia cell line lineages. For both cell types we found distinct transcriptional patterns associated with single-cell lineage relationships as well as cell cycle progression. In order to link single-cell size and growth rate measurements with gene expression, we have also developed a system that relies on an array of suspended microchannel resonators (SMR) - high resolution single-cell buoyant mass sensors - in combination with an automated method of isolating single cells to conduct scRNA-seq downstream. Using this platform, we were able to collect linked transcriptional and biophysical measurements for a murine leukemia cell line, primary murine CD8+ T cells, and a patient-derived glioblastoma multiforme (GBM) cell line. For all cell models measured, we found that single-cell buoyant mass showed a strong correlation with the expression of cell cycle genes. Furthermore, we found that single-cell growth rate and buoyant mass measurements can be used to characterize the degree to which GBM cells respond to drug treatment as well as determine transcriptional signatures associated with response and resistance. Taken together, we believe these single-cell phenotypic measurements will offer complementary contextual information to further resolve the heterogeneity of single-cell transcriptional data. As such, we expect these platforms to be broadly useful to fields where heterogeneous populations of cells display distinct clonal trajectories, including immunology, cancer, and developmental biology.
Book Synopsis Stochastic Modeling of Eukaryotic Transcription at the Single Nucleotide Level by : Saurabh Vashishtha
Download or read book Stochastic Modeling of Eukaryotic Transcription at the Single Nucleotide Level written by Saurabh Vashishtha and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Resistance of Pseudomonas Aeruginosa by : Michael Robert Withington Brown
Download or read book Resistance of Pseudomonas Aeruginosa written by Michael Robert Withington Brown and published by John Wiley & Sons. This book was released on 1975 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Encyclopedia of Cell Biology written by and published by Academic Press. This book was released on 2015-08-07 with total page 2972 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Cell Biology, Four Volume Set offers a broad overview of cell biology, offering reputable, foundational content for researchers and students across the biological and medical sciences. This important work includes 285 articles from domain experts covering every aspect of cell biology, with fully annotated figures, abundant illustrations, videos, and references for further reading. Each entry is built with a layered approach to the content, providing basic information for those new to the area and more detailed material for the more experienced researcher. With authored contributions by experts in the field, the Encyclopedia of Cell Biology provides a fully cross-referenced, one-stop resource for students, researchers, and teaching faculty across the biological and medical sciences. Fully annotated color images and videos for full comprehension of concepts, with layered content for readers from different levels of experience Includes information on cytokinesis, cell biology, cell mechanics, cytoskeleton dynamics, stem cells, prokaryotic cell biology, RNA biology, aging, cell growth, cell Injury, and more In-depth linking to Academic Press/Elsevier content and additional links to outside websites and resources for further reading A one-stop resource for students, researchers, and teaching faculty across the biological and medical sciences
Book Synopsis Analytic Solutions for Stochastic Models of Transcription by : Seyed Hossein Hosseini
Download or read book Analytic Solutions for Stochastic Models of Transcription written by Seyed Hossein Hosseini and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The spatio-temporal organization of one RNA polymerase (RNAP) along a DNA strand is explored by studying a kinetic stochastic model for transcription process, the first step in gene expression. An explicit expression for the probability density of one RNAP was found and compared with stochastic simulation results from the corresponding detailed stochastic model. The explicit solution predicts that the movement of RNAP in large genes (genes of a few hundred nucleotides or more) is advective. It provides a justification for the use of delays in gene expression modeling, especially in delay-stochastic models. The kinetic model for the elongation stage of transcription was extended to two bodies, and the related Fokker-Planck equation was developed. This equation describes the evolution of the joint probability density for two RNAPs along the DNA track.
Book Synopsis Stress-Activated Protein Kinases by : Francesc Posas
Download or read book Stress-Activated Protein Kinases written by Francesc Posas and published by Springer Science & Business Media. This book was released on 2008-01-24 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book leading researchers in the field discuss the state-of-the-art of many aspects of SAPK signaling in various systems from yeast to mammals. These include various chapters on regulatory mechanisms as well as the contribution of the SAPK signaling pathways to processes such as gene expression, metabolism, cell cycle regulation, immune responses and tumorigenesis. Written by international experts, the book will appeal to cell biologists and biochemists.
Book Synopsis Analysis of a Simple Gene Expression Model by : Simbarashe Chipindirwi
Download or read book Analysis of a Simple Gene Expression Model written by Simbarashe Chipindirwi and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis MAST: a Flexible Statistical Framework for Assessing Transcriptional Changes and Characterizing Heterogeneity in Single-Cell RNA Sequencing Data by : Odessa Odessa Press
Download or read book MAST: a Flexible Statistical Framework for Assessing Transcriptional Changes and Characterizing Heterogeneity in Single-Cell RNA Sequencing Data written by Odessa Odessa Press and published by . This book was released on 2016-01-29 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at https://github.com/RGLab/MAST.
Book Synopsis Bacterial Persistence by : Jan Michiels
Download or read book Bacterial Persistence written by Jan Michiels and published by Humana. This book was released on 2015-10-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a comprehensive collection of methods that have been instrumental to the current understanding of bacterial persisters. Chapters in the book cover topics ranging from general methods for measuring persister levels in Escherichia coli cultures, protocols for the determination of the persister subpopulation in Candida albicans, quantitative measurements of Type I and Type II persisters using ScanLag, to in vitro and in vivo models for the study of the intracellular activity of antibiotics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Bacterial Persistence: Methods and Protocols brings together the most respected researchers in bacterial persistence whose studies will remain vital to understanding this field for many years to come.
Book Synopsis Statistical Inference of a Single Cell Gene Expression Model for Heterogeneous Tissues by : Graham Heimberg
Download or read book Statistical Inference of a Single Cell Gene Expression Model for Heterogeneous Tissues written by Graham Heimberg and published by . This book was released on 2018 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis we present new statistical analyses for analyzing gene expression distributions within tissue samples and comparing them across tissue samples. These analyses share a common approach, to exploit a natural property of transcriptional systems to reduce the complexity of this data. Through a survey of over 500 datasets, we find that global gene expression profiles can be accurately represented as a linear combination of a relatively small number of gene expression "programs".
Book Synopsis Methods in Yeast Genetics by : David C. Amberg
Download or read book Methods in Yeast Genetics written by David C. Amberg and published by CSHL Press. This book was released on 2005 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Methods in Yeast Genetics" is a course that has been offered annually at Cold Spring Harbor for the last 30 years. This provides a set of teaching experiments along with the protocols and recipes for the standard techniques and reagents used in the study of yeast biology.
Book Synopsis Virus Dynamics : Mathematical Principles of Immunology and Virology by : Martin Nowak
Download or read book Virus Dynamics : Mathematical Principles of Immunology and Virology written by Martin Nowak and published by Oxford University Press, UK. This book was released on 2000-11-23 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This groundbreaking book describes the emerging field of theoretical immunology, in particular the use of mathematical models to describe the spread of infectious diseases within patients. It reveals fascinating insights into the dynamics of viral and other infections, and the interactions between infectious agents and immune responses. Structured around the examples of HIV/AIDS and hepatitis B, Nowak and May show how mathematical models can help researchers to understand the detailed dynamics of infection and the effects of antiviral therapy. Models are developed to describe the dynamics of drug resistance, immune responses, viral evolution and mutation, and to optimise the design of therapy and vaccines. - ;We know, down to the tiniest details, the molecular structure of the human immunodeficiency virus (HIV). Yet despite this tremendous accomplishment, and despite other remarkable advances in our understanding of individual viruses and cells of the immune system, we still have no agreed understanding of the ultimate course and variability of the pathogenesis of AIDS. Gaps in our understanding like these impede our efforts towards developing effective therapies and preventive vaccines. Martin Nowak and Robert M May describe the emerging field of theoretical immunology in this accessible and well- written text. Using mathematical modelling techniques, the authors set out their ideas about how populations of viruses and populations of immune system cells may interact in various circumstances, and how infectious diseases spread within patients. They explain how this approach to understanding infectious diseases can reveal insights into the dynamics of viral and other infections, and the interactions between infectious agents and immune responses. The book is structured around the examples of HIV/AIDS and Hepatitis B virus, although the approaches described will be more widely applicable. The authors use mathematical tools to uncover the detailed dynamics of the infection and the effects of antiviral therapy. Models are developed to describe the emergence of drug resistance, and the dynamics of immune responses, viral evolution, and mutation. The practical implications of this work for optimisation of the design of therapy and vaccines are discussed. The book concludes with a glance towards the future of this fascinating, and potentially highly useful, field of study. - ;... an excellent introduction to a field that has the potential to advance substantially our understanding of the complex interplay between virus and host - Nature
