Data-driven Mechanistic Modeling of 3D Human Genome PDF Download
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Author: Yifeng Qi (Scientist in chemistry)
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This thesis is organized as follows. In the first chapter, we introduce a computational model to simulate chromatin structure and dynamics. The model defines chromatin states by taking one-dimensional genomics and epigenomics data as input and quantitatively learns interacting patterns between these states using experimental contact data. Once learned, the model is able to make de novo predictions of 3D chromatin structures at five-kilo-base resolution across different cell types. The manuscript associated with this study is published in PLoS Computational Biology, 15.6, e1007024 (2019).
Author: Yifeng Qi (Scientist in chemistry)
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This thesis is organized as follows. In the first chapter, we introduce a computational model to simulate chromatin structure and dynamics. The model defines chromatin states by taking one-dimensional genomics and epigenomics data as input and quantitatively learns interacting patterns between these states using experimental contact data. Once learned, the model is able to make de novo predictions of 3D chromatin structures at five-kilo-base resolution across different cell types. The manuscript associated with this study is published in PLoS Computational Biology, 15.6, e1007024 (2019).
Author: Guido Tiana
Publisher: CRC Press
ISBN: 1351387006
Category : Science
Languages : en
Pages : 370
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Book Description
This book provides a timely summary of physical modeling approaches applied to biological datasets that describe conformational properties of chromosomes in the cell nucleus. Chapters explain how to convert raw experimental data into 3D conformations, and how to use models to better understand biophysical mechanisms that control chromosome conformation. The coverage ranges from introductory chapters to modeling aspects related to polymer physics, and data-driven models for genomic domains, the entire human genome, epigenome folding, chromosome structure and dynamics, and predicting 3D genome structure.
Author: G. Tiana
Publisher: CRC Press
ISBN: 9780367780456
Category : Genomics
Languages : en
Pages : 370
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Book Description
This book provides a timely summary of physical modeling approaches applied to biological datasets that describe conformational properties of chromosomes in the cell nucleus. The coverage ranges from introductory chapters to modeling aspects related to polymer physics, and data-driven models for genomic domains, and predicting 3D genome structur
Author: Christophe Lavelle
Publisher: Academic Press
ISBN: 012803503X
Category : Science
Languages : en
Pages : 620
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Book Description
Nuclear Architecture and Dynamics provides a definitive resource for (bio)physicists and molecular and cellular biologists whose research involves an understanding of the organization of the genome and the mechanisms of its proper reading, maintenance, and replication by the cell. This book brings together the biochemical and physical characteristics of genome organization, providing a relevant framework in which to interpret the control of gene expression and cell differentiation. It includes work from a group of international experts, including biologists, physicists, mathematicians, and bioinformaticians who have come together for a comprehensive presentation of the current developments in the nuclear dynamics and architecture field. The book provides the uninitiated with an entry point to a highly dynamic, but complex issue, and the expert with an opportunity to have a fresh look at the viewpoints advocated by researchers from different disciplines. Highlights the link between the (bio)chemistry and the (bio)physics of chromatin Deciphers the complex interplay between numerous biochemical factors at task in the nucleus and the physical state of chromatin Provides a collective view of the field by a large, diverse group of authors with both physics and biology backgrounds
Author: Michael Harris Kramer
Publisher:
ISBN:
Category :
Languages : en
Pages : 128
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Book Description
A holy grail of bioinformatics is the creation of whole-cell models with the ability to enhance human understanding and facilitate discovery. To this end, a successful and widely-used effort is the Gene Ontology (GO), a massive project to manually annotate genes into terms describing molecular functions, biological processes and cellular components and provide relations between terms, e.g. capturing that "small ribosomal subunit" and "large ribosomal subunit" come together to make "ribosome". GO is widely used to understand the function of a gene or group of genes. Unfortunately, GO is limited by the effort required to create and update it by hand. It exists only for well-studied organisms and even then in one, generic form per organism with limited overall genome coverage and bias towards well-studied genes and functions. It is not possible to learn about an uncharacterized gene or discover a new function using GO, and one cannot quickly assemble an ontology model for a new organism, cell-type or disease-state. Here we change this state of affairs by developing and utilizing the concept of purely data-driven gene ontologies. In chapter two, we show that large networks of gene and protein interactions in Saccharomyces cerevisiae can be used to computationally infer a data-driven ontology whose coverage and power are equivalent to those of the manually-curated GO. In chapter three we further develop the algorithmic foundations for data-driven ontologies, laying the groundwork for machine learning to intelligently integrate many types of experimental data into ontology models. In chapter four, we focus on a cellular process (autophagy in Saccharomyces cerevisiae) and develop a framework (Active Interaction Mapping) which guides experimental selection, systematically improves an existing process-specific ontology model and uncovers new autophagy biology. Finally, in chapter five, we illustrate the power of hierarchical whole-cell ontology models for biological modeling by demonstrating an ontology-based framework for translation of genotype to phenotype. Overall, this work provides a roadmap to construct data-driven, hierarchical models of gene function for the whole cell or a specific cellular process and illustrates the power of these models for both discovery of new biology and biological modeling.
Author: Oldenburg Oldenburg Press
Publisher:
ISBN: 9781523764426
Category :
Languages : en
Pages : 40
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Book Description
HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro.
Author: J. Nathan Kutz
Publisher: SIAM
ISBN: 1611974496
Category : Science
Languages : en
Pages : 241
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Book Description
Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
Author: Surajit Pathak
Publisher: Springer Nature
ISBN: 9811938245
Category : Medical
Languages : en
Pages : 1158
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Book Description
This reference book compiles together different animal models in cancer research. It provides knowledge and a better understanding of the advancement of the molecular and cellular mechanisms associated with the progression, formation, and clinical results of various types of cancer from the evidence collected from animal models utilized for cancer research. It discusses animal models for screening anti-cancer drugs and exploration of gene therapy. It presents different methods used to construct cancer animal models and the progress of each animal model in tumor research. The book also highlights the applications of genetic engineering, including CRISP/Cas9, in designing and developing animal models for cancer research. Further, it discusses strategies for modeling animals for investigating growth, metastasis, tumor-associated inflammation and microenvironment, cancer stem cells, tumor heterogeneity, and therapeutic resistance. This book is s a valuable resource for basic and translational cancer researchers, clinicians, and health care.
Author: Issam El Naqa
Publisher: Springer
ISBN: 3319183052
Category : Medical
Languages : en
Pages : 336
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Book Description
This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Author: Zorina S. Galis
Publisher: Academic Press
ISBN: 0128225475
Category : Science
Languages : en
Pages : 528
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Book Description
The Vasculome: From Many, One introduces the fundamental bases of the “unity in diversity of the Vasculome, from the coming together of various cell lineages during development, to its deceptively simple solution for architectural design: the efficient interplay of a few types of building blocks supporting key similar functions throughout the body and their highly specialized functional local variations. Specific examples are included to illustrate how the Vasculome is integral to the function and malfunction of different organs, such as the brain or the kidney. Each section is preceded by an introductory summary that will give a high level unified view of the key concepts illustrated in the various chapters in that section. Zorina Galis' The Vasculome was named a finalist in the Clinical Medicine category of the American Association of Publishers’ 2023 PROSE Awards. 2023 PROSE Awards - Winner: Finalist: Clinical Medicine: Association of American Publishers Brings together leading experts who present the latest biomedical thinking about the vasculature from the integrative perspective of the Vasculome Challenges traditional real and perceived boundaries within vascular research areas and stimulates new fundamental thinking and medical explorations Creates the bases for translating the integrative Vasculome concept into improved fundamental and clinical assessment and management of local and systemic contributions of the vasculature in health and disease
