Analysis and Control of Cellular Ensembles. Exploiting dimensionality reduction in single-cell data and models

Analysis and Control of Cellular Ensembles. Exploiting dimensionality reduction in single-cell data and models PDF Author: Karsten Kuritz
Publisher: Logos Verlag Berlin GmbH
ISBN: 383255209X
Category : Language Arts & Disciplines
Languages : en
Pages : 150

Book Description
An ensemble system is a collection of nearly identical dynamical systems which admit a certain degree of heterogeneity, and which are subject to the restriction that they may only be manipulated or observed as a whole. This thesis presents analysis and control methods for cellular ensembles by considering reduced 1-dimensional dynamics of biological processes in high-dimensional single-cell data and models. To be more specific, we address the quest for real-time analysis of biological processes within single-cell data by introducing the measure-preserving map of pseudotime into real-time, in short MAPiT. MAPiT enables the reconstruction of temporal and spatial dynamics from single-cell snapshot experiments. In addition, we propose a PDE-constrained learning algorithm which allows for efficient inference of changes in cell cycle progression from time series single-cell snapshot data. The second part of this thesis, is devoted to controlling a heterogeneous cell population, in the sense, that we aim at achieving a desired distribution of cellular oscillators on their periodic orbit. A systems theoretic approach to the ensemble control problem provides novel necessary and sufficient conditions for the control of phase distributions in terms of the Fourier coefficients of the phase response curve. This thesis establishes a connection between the previously separate areas of single cell analysis and ensemble control. Our holistic view opens new perspectives for theoretic concepts in basic research and therapeutic strategies in precision medicine.

Computational Methods for Single-Cell Data Analysis

Computational Methods for Single-Cell Data Analysis PDF Author: Guo-Cheng Yuan
Publisher: Humana Press
ISBN: 9781493990566
Category : Science
Languages : en
Pages : 271

Book Description
This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. 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, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.

Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191

Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Probabilistic Boolean Networks

Probabilistic Boolean Networks PDF Author: Ilya Shmulevich
Publisher: SIAM
ISBN: 0898716926
Category : Mathematics
Languages : en
Pages : 276

Book Description
The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.

Introduction to Single Cell Omics

Introduction to Single Cell Omics PDF Author: Xinghua Pan
Publisher: Frontiers Media SA
ISBN: 2889459209
Category :
Languages : en
Pages : 129

Book Description
Single-cell omics is a progressing frontier that stems from the sequencing of the human genome and the development of omics technologies, particularly genomics, transcriptomics, epigenomics and proteomics, but the sensitivity is now improved to single-cell level. The new generation of methodologies, especially the next generation sequencing (NGS) technology, plays a leading role in genomics related fields; however, the conventional techniques of omics require number of cells to be large, usually on the order of millions of cells, which is hardly accessible in some cases. More importantly, harnessing the power of omics technologies and applying those at the single-cell level are crucial since every cell is specific and unique, and almost every cell population in every systems, derived in either vivo or in vitro, is heterogeneous. Deciphering the heterogeneity of the cell population hence becomes critical for recognizing the mechanism and significance of the system. However, without an extensive examination of individual cells, a massive analysis of cell population would only give an average output of the cells, but neglect the differences among cells. Single-cell omics seeks to study a number of individual cells in parallel for their different dimensions of molecular profile on genome-wide scale, providing unprecedented resolution for the interpretation of both the structure and function of an organ, tissue or other system, as well as the interaction (and communication) and dynamics of single cells or subpopulations of cells and their lineages. Importantly single-cell omics enables the identification of a minor subpopulation of cells that may play a critical role in biological process over a dominant subpolulation such as a cancer and a developing organ. It provides an ultra-sensitive tool for us to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. Besides, it also empowers the clinical investigation of patients when facing a very low quantity of cell available for analysis, such as noninvasive cancer screening with circulating tumor cells (CTC), noninvasive prenatal diagnostics (NIPD) and preimplantation genetic test (PGT) for in vitro fertilization. Single-cell omics greatly promotes the understanding of life at a more fundamental level, bring vast applications in medicine. Accordingly, single-cell omics is also called as single-cell analysis or single-cell biology. Within only a couple of years, single-cell omics, especially transcriptomic sequencing (scRNA-seq), whole genome and exome sequencing (scWGS, scWES), has become robust and broadly accessible. Besides the existing technologies, recently, multiplexing barcode design and combinatorial indexing technology, in combination with microfluidic platform exampled by Drop-seq, or even being independent of microfluidic platform but using a regular PCR-plate, enable us a greater capacity of single cell analysis, switching from one single cell to thousands of single cells in a single test. The unique molecular identifiers (UMIs) allow the amplification bias among the original molecules to be corrected faithfully, resulting in a reliable quantitative measurement of omics in single cells. Of late, a variety of single-cell epigenomics analyses are becoming sophisticated, particularly single cell chromatin accessibility (scATAC-seq) and CpG methylation profiling (scBS-seq, scRRBS-seq). High resolution single molecular Fluorescence in situ hybridization (smFISH) and its revolutionary versions (ex. seqFISH, MERFISH, and so on), in addition to the spatial transcriptome sequencing, make the native relationship of the individual cells of a tissue to be in 3D or 4D format visually and quantitatively clarified. On the other hand, CRISPR/cas9 editing-based In vivo lineage tracing methods enable dynamic profile of a whole developmental process to be accurately displayed. Multi-omics analysis facilitates the study of multi-dimensional regulation and relationship of different elements of the central dogma in a single cell, as well as permitting a clear dissection of the complicated omics heterogeneity of a system. Last but not the least, the technology, biological noise, sequence dropout, and batch effect bring a huge challenge to the bioinformatics of single cell omics. While significant progress in the data analysis has been made since then, revolutionary theory and algorithm logics for single cell omics are expected. Indeed, single-cell analysis exert considerable impacts on the fields of biological studies, particularly cancers, neuron and neural system, stem cells, embryo development and immune system; other than that, it also tremendously motivates pharmaceutic RD, clinical diagnosis and monitoring, as well as precision medicine. This book hereby summarizes the recent developments and general considerations of single-cell analysis, with a detailed presentation on selected technologies and applications. Starting with the experimental design on single-cell omics, the book then emphasizes the consideration on heterogeneity of cancer and other systems. It also gives an introduction of the basic methods and key facts for bioinformatics analysis. Secondary, this book provides a summary of two types of popular technologies, the fundamental tools on single-cell isolation, and the developments of single cell multi-omics, followed by descriptions of FISH technologies, though other popular technologies are not covered here due to the fact that they are intensively described here and there recently. Finally, the book illustrates an elastomer-based integrated fluidic circuit that allows a connection between single cell functional studies combining stimulation, response, imaging and measurement, and corresponding single cell sequencing. This is a model system for single cell functional genomics. In addition, it reports a pipeline for single-cell proteomics with an analysis of the early development of Xenopus embryo, a single-cell qRT-PCR application that defined the subpopulations related to cell cycling, and a new method for synergistic assembly of single cell genome with sequencing of amplification product by phi29 DNA polymerase. Due to the tremendous progresses of single-cell omics in recent years, the topics covered here are incomplete, but each individual topic is excellently addressed, significantly interesting and beneficial to scientists working in or affiliated with this field.

Tumor Immunology and Immunotherapy - Cellular Methods Part B

Tumor Immunology and Immunotherapy - Cellular Methods Part B PDF Author:
Publisher: Academic Press
ISBN: 0128186755
Category : Science
Languages : en
Pages : 586

Book Description
Tumor Immunology and Immunotherapy - Cellular Methods Part B, Volume 632, the latest release in the Methods in Enzymology series, continues the legacy of this premier serial with quality chapters authored by leaders in the field. Topics covered include Quantitation of calreticulin exposure associated with immunogenic cell death, Side-by-side comparisons of flow cytometry and immunohistochemistry for detection of calreticulin exposure in the course of immunogenic cell death, Quantitative determination of phagocytosis by bone marrow-derived dendritic cells via imaging flow cytometry, Cytofluorometric assessment of dendritic cell-mediated uptake of cancer cell apoptotic bodies, Methods to assess DC-dependent priming of T cell responses by dying cells, and more.

Computational Stem Cell Biology

Computational Stem Cell Biology PDF Author: Patrick Cahan
Publisher: Humana
ISBN: 9781493992232
Category : Science
Languages : en
Pages : 0

Book Description
This volume details methods and protocols to further the study of stem cells within the computational stem cell biology (CSCB) field. Chapters are divided into four sections covering the theory and practice of modeling of stem cell behavior, analyzing single cell genome-scale measurements, reconstructing gene regulatory networks, and metabolomics. 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, Computational Stem Cell Biology: Methods and Protocols will be an invaluable guide to researchers as they explore stem cells from the perspective of computational biology.

Computational Molecular Evolution

Computational Molecular Evolution PDF Author: Ziheng Yang
Publisher: Oxford University Press, USA
ISBN: 0198566999
Category : Medical
Languages : en
Pages : 374

Book Description
This book describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes.

The Mouse Nervous System

The Mouse Nervous System PDF Author: Charles Watson
Publisher: Academic Press
ISBN: 0123694973
Category : Medical
Languages : en
Pages : 815

Book Description
The Mouse Nervous System provides a comprehensive account of the central nervous system of the mouse. The book is aimed at molecular biologists who need a book that introduces them to the anatomy of the mouse brain and spinal cord, but also takes them into the relevant details of development and organization of the area they have chosen to study. The Mouse Nervous System offers a wealth of new information for experienced anatomists who work on mice. The book serves as a valuable resource for researchers and graduate students in neuroscience. Systematic consideration of the anatomy and connections of all regions of the brain and spinal cord by the authors of the most cited rodent brain atlases A major section (12 chapters) on functional systems related to motor control, sensation, and behavioral and emotional states A detailed analysis of gene expression during development of the forebrain by Luis Puelles, the leading researcher in this area Full coverage of the role of gene expression during development and the new field of genetic neuroanatomy using site-specific recombinases Examples of the use of mouse models in the study of neurological illness

Control Theory and Systems Biology

Control Theory and Systems Biology PDF Author: Pablo A. Iglesias
Publisher: MIT Press
ISBN: 0262013347
Category : Biological control systems
Languages : en
Pages : 359

Book Description
A survey of how engineering techniques from control and systems theory can be used to help biologists understand the behavior of cellular systems.