Improving the Accuracy of 3D Chromosome Structure Inference and Analyzing the Organization of Genome in Early Embryogenesis Using Single Cell Hi-C Data

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Book Synopsis Improving the Accuracy of 3D Chromosome Structure Inference and Analyzing the Organization of Genome in Early Embryogenesis Using Single Cell Hi-C Data by : Tarak Shisode

Download or read book Improving the Accuracy of 3D Chromosome Structure Inference and Analyzing the Organization of Genome in Early Embryogenesis Using Single Cell Hi-C Data written by Tarak Shisode and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation summarizes my graduate work on the structure and organization of mouse genome during preimplantation development. My research is divided into three different areas, which I will discuss in turn. To begin, I will discuss my collaborative work on parental-to-embryo switch of chromosome organization during critical stages of early development. Notably, both paternal and maternal epigenomes undergo significant modifications following fertilization. Recent epigenomic studies have revealed the extraordinary chromatin landscapes found in oocytes, sperm, and early preimplantation embryos, including atypical histone modification patterns and differences in chromosome organization and accessibility. However, these studies reached polar opposite conclusions: the global absence of local topological-associated domains (TADs) in gametes and their appearance in the embryo versus the zygote's pre-existence of TADs and loops. The issues of whether parental structures can be inherited in the newly formed embryo and how these structures may be related to allele-specific gene regulation remain unresolved. To address this question, we use an optimized single cell high-throughput chromosome conformation capture (HiC) protocol to map genomic interactions for each parental genome (including the X chromosome) during mouse preimplantation. We integrate chromosome organization with allelic expression states and chromatin marks and demonstrate that after fertilization, higher-order chromatin structure is associated with an allele specific enrichment of histone H3 lysine 27 methylation. These early parental-specific domains are associated with gene repression and contribute to parentally biased gene expression-including newly described transiently imprinted loci. Additionally, we observe that these domains emerge in a non-parental-specific manner during the second wave of genome assembly. Finally, we discover that these domains are lost as genes are silenced on the paternal X chromosome but persist in regions that are not inactivated by the X chromosome. These findings highlight the complexities of three-dimensional genome organization and gene expression dynamics during early development. Second, I will discuss my work on some common and cell type-specific themes of higher order chromatin arrangements during mouse preimplantation development. Mapping the spatial organization of the genome is critical for comprehending its regulatory function in health, disease, and development. Our findings demonstrate an extraordinary amount of parent-specific chromosome choreography during the concatenation of two genomes. After fertilization, we observe an abrupt emergence of a Rabl-like configuration and a high head-to-head and tail-to-tail alignment of the chromosomes, which are gradually lost by the 64-cell stage. Additionally, the characteristics and marks of active and inactive chromatin exhibit a distinct radial profile across developmental stages and the genome. Finally, in addition to the well-known hallmarks of genome organization, we observe a preferential organization of chromosome territories - which call the "Territome". We were able to distinguish cell types based on the radial and relative positioning of the chromosomes in the 3D reconstructions. This suggest that interchromosomal interactions are just as critical for defining chromatin architecture and cellular identity as intrachromosomal interactions. Our findings establish a novel criterion for classifying cells when other hallmarks are difficult to quantify or when transcriptomics data is unavailable, thus paving a whole new way of looking at cells and learning how they function. Finally, with advances in experimental and theoretical approaches for generating single cell chromatin conformation capture assays, elucidating the genome's structure-function relationship has become a highly active area of research. Numerous computational methods have been developed to infer the genome's three-dimensional organization using Hi-C data from single cells. This is referred to as the three-dimensional genome reconstruction problem in formal terms (3D-GRP). While numerous methods exist for predicting the three-dimensional structure of a single genomic region, chromosome, or genome, the reconstructed models do not satisfy all of the input constraints. To address this, we present CUT & GROW, a method for improving the accuracy of three-dimensional chromosome structure inference using an iterative importance sampling strategy. CUT & GROW refines the structure of a three-dimensional chromosome (or genome) model by regrowing fragments of varying sizes locally, satisfying the majority of input constraints and providing a more precise view of the structure-function relationship

Hi-C Data Analysis

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Publisher : Humana
ISBN 13 : 9781071613924
Total Pages : 0 pages
Book Rating : 4.6/5 (139 download)

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Book Synopsis Hi-C Data Analysis by : Silvio Bicciato

Download or read book Hi-C Data Analysis written by Silvio Bicciato and published by Humana. This book was released on 2022-09-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume details a comprehensive set of methods and tools for Hi-C data processing, analysis, and interpretation. Chapters cover applications of Hi-C to address a variety of biological problems, with a specific focus on state-of-the-art computational procedures adopted for the data analysis. 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, Hi-C Data Analysis: Methods and Protocols aims to help computational and molecular biologists working in the field of chromatin 3D architecture and transcription regulation.

Investigating Chromosome Dynamics Through Hi-C Assembly

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (119 download)

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Book Synopsis Investigating Chromosome Dynamics Through Hi-C Assembly by : Lyam Baudry

Download or read book Investigating Chromosome Dynamics Through Hi-C Assembly written by Lyam Baudry and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent of high-throughput DNA sequencing technologies has set off an expanding trend in genome assembling and scaffolding. Such genome quality is an essential preliminary to understand interactions between and among chromosomes. We built upon a computational and technological framework that let us tackle genome assembly problems of increasing complexity. Our methods are mainly based on chromosome conformation capture technologies such as Hi-C. In a Hi-C experiment, DNA molecules are cross-linked with the surrounding proteins and form a large, static protein-DNA complex. This captures the spatial conformation by trapping together molecules that are physically close to each other. Therefore, Hi-C is very suitable for 3D genome structure analysis, which lets us infer a wealth of information about the genome. It was indeed shown that the tridimensional structure of the genome can be unambiguously linked to its 1D structure thanks to the physical properties of DNA polymers. Moreover, such 3D proximity also gives access to cell compartment information, thus opening the way for an additional approach for metagenomic binning, known as meta3C. In this work, we expand upon these methods and apply them to use cases with more and more complexity. We first improve on tools for genome assembly and demonstrate their validity with the scaffolding of Ectocarpus sp., then unveil rearrangements in joint scaffoldings of Trichoderma reesei and Cataglyphis hispanica. Lastly, we use the same approach with metagenomic binning on live mouse microbiome samples to reconstruct hundreds of genomes.

High-resolution Computational Analysis of Chromatin Architecture and Function

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (122 download)

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Book Synopsis High-resolution Computational Analysis of Chromatin Architecture and Function by : Christopher Cameron

Download or read book High-resolution Computational Analysis of Chromatin Architecture and Function written by Christopher Cameron and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Since sequencing the human genome in the early 2000s, researchers have been determined to define the genetic pathways that regulate cellular activity or lead to disease. With the recent advent of Chromosome Conformation Capture (3C) technologies, the ability to observe chromatin’s three-dimensional (3D) structure became a possibility. It quickly became apparent that the genome is not regulated in one-dimension, but in 3D where chromatin loops are formed between an enhancer(s) and promoter to regulate a gene’s transcription. While 3C technology is quite useful, most protocols are limited in their resolution and availability across cell types and genomes. This limited resolution is a common concern for many technologies that study the regulation of genomes, such as Chromatin Immunoprecipitation (ChIP), and typically results from low-coverage sequencing. The objective of this thesis is to develop computational and biochemical methodologies that provide accurate, high-resolution genomic data for deciphering the organization and regulation of genomes. The first contribution in this thesis is Hi-C Interaction Frequency Inference (HIFI), a collection of density estimation algorithms for High-throughput 3C (Hi-C) data. Hi-C is a particularly useful 3C technology that identifies chromatin contacts genome-wide. HIFI allows Hi-C data to be analyzed at the highest possible resolution (restriction fragments) while providing the most accurate estimation of chromatin contact frequency when compared to other techniques in the field. The higher resolution afforded by HIFI has lead to the discovery of a potential role for active promoters and enhancers at the boundaries of Topologically Associating Domains (TADs). Next, we developed machine learning approaches to predict chromatin interaction frequencies from the reference genome sequence alone. While some machine learning work has been done to predict Hi-C data, all these models rely on biochemical input to make their predictions, which makes them impossible to use in cases where this data is unavailable (e.g., computationally inferred ancestral genomes). By limiting model input to features derived from sequence only, their predictions enable us to identify sequence determinants of 3D genome organization. Finally, we present a targeted and affordable ChIP methodology, called ‘Carbon Copy-ChIP’ (2C-ChIP), that continues our foray into high-resolution chromatin assays. 2C-ChIP provides quantifiable measures of bound protein across the genome at a cost that makes it very attractive for studies involving multiple experimental conditions (e.g., drug design). We also describe a computational tool for processing 2C-ChIP products called the Ligation-mediated Amplified, Multiplexed Paired-end Sequence (LAMPS) analysis pipeline.Taken together, the work in this thesis provides new ways to study genome function and organization affordably and at high resolution"--

HiC-Pro: an Optimized and Flexible Pipeline for Hi-C Data Processing

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ISBN 13 : 9781523764426
Total Pages : 40 pages
Book Rating : 4.7/5 (644 download)

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Book Synopsis HiC-Pro: an Optimized and Flexible Pipeline for Hi-C Data Processing by : Oldenburg Oldenburg Press

Download or read book HiC-Pro: an Optimized and Flexible Pipeline for Hi-C Data Processing written by Oldenburg Oldenburg Press and published by . This book was released on 2016-01-29 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Single Cell Omics

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Publisher : Frontiers Media SA
ISBN 13 : 2889459209
Total Pages : 129 pages
Book Rating : 4.8/5 (894 download)

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Book Synopsis Introduction to Single Cell Omics by : Xinghua Pan

Download or read book Introduction to Single Cell Omics written by Xinghua Pan and published by Frontiers Media SA. This book was released on 2019-09-19 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Inference of 3D Structure of Diploid Chromosomes

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ISBN 13 :
Total Pages : 62 pages
Book Rating : 4.:/5 (17 download)

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Book Synopsis Inference of 3D Structure of Diploid Chromosomes by : Lawrence J. Sun

Download or read book Inference of 3D Structure of Diploid Chromosomes written by Lawrence J. Sun and published by . This book was released on 2018 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: The spatial organization of DNA in the cell nucleus plays an important role for gene regulation, DNA replication, and genomic integrity. Through the development of chromosome capture experiments (such as 3C, 4C, Hi-C) it is now possible to obtain the contact frequencies of the DNA at the whole-genome level. In this thesis, we study the problem of reconstructing the 3D organization of the genome from whole-genome contact frequencies. A standard approach is to transform the contact frequencies into noisy distance measurements and then apply semidefinite programming (SDP) formulations to obtain the 3D configurations. However, neglected in such reconstructions is the fact that most eukaryotes including humans are diploid and therefore contain two (from the available data) indistinguishable copies of each genomic locus. Due to this, the standard approach performs very poorly on diploid organisms. We prove that the 3D organization of the DNA is not identifiable from exclusively chromosome capture data for diploid organisms. In fact, there are infinitely many solutions even in the noise-free setting. We then discuss various additional biologically relevant constraints (including distances between neighboring genomic loci and to the nucleus center or higher-order interactions). Under these conditions we prove there are finitely many solutions and conjecture we in fact have identifiability. Finally, we provide SDP formulations for computing the 3D embedding of the DNA with these additional constraints and show that we can recover the true 3D embedding with high accuracy even under noise.

Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA)

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Publisher : Frontiers Media SA
ISBN 13 : 2832543804
Total Pages : 89 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) by : E. Zhang

Download or read book Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) written by E. Zhang and published by Frontiers Media SA. This book was released on 2024-01-25 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to numerous biomedical information sensing devices, such as Computed Tomography (CT), Magnetic Resonance (MR) Imaging, Ultrasound, Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), to Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy, etc. a large amount of biomedical information was gathered these years. However, identifying how to develop new advanced imaging methods and computational models for efficient data processing, analysis and modelling from the collected data is important for clinical applications and to understand the underlying biological processes. Deep learning approaches have been rapidly developed in recent years, both in terms of methodologies and practical applications. Deep learning techniques provide computational models of multiple processing layers to learn and represent data with multiple levels of abstraction. Deep Learning allows to implicitly capture intricate structures of large-scale data and ideally suited to some of the hardware architectures that are currently available.

Patterns and Processes Driving Chromosome Organization

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Patterns and Processes Driving Chromosome Organization by : Sameer Abraham (Physicist)

Download or read book Patterns and Processes Driving Chromosome Organization written by Sameer Abraham (Physicist) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we focus on different approaches to studying the organization of chromosomes with in the nucleus of cells. We employ both genomic analysis of chromosome interaction maps, and polymer simulations to answer various questions that are relevant to the field. The first two chapters of this thesis are centered around genomic analysis of interaction maps generated from Chromosome Conformation Capture (3C) technologies. We begin by analyzing data generated using a novel Micro-C protocol and assess its performance in comparison to established Hi-C. New computation tools are developed to extract, quantify and compare patterns detected in both techniques. We find that Micro-C can accurately recapitulate the patterns of interactions found in Hi-C. In addition, evidence for nucleosome scale structure is also detected in the data. Following this, the scope of the meta-analysis is expanded. We compared over 70 different human Hi-C and Micro-C libraries that vary in the biochemical parameters used in data generation. We extract trends that relate the protocol parameters to the observed patterns of enrichment found in the data. We find that libraries generated with a high degree of fragmentation are better at capturing fine scale organization, while those with larger fragments excel in capturing larger patterns and structures. In the final chapter, we explore the dynamic changes in chromosome organization through the early stages of cell division. We analyze experimental Hi-C of DT-40 chicken cells and uncover the role of Condensin in disassembling interphase chromatin structure during prophase. We develop a model for prophase condensation and explore different interactions between loop extruding Cohesins and Condensins. We find that non-trivial interactions between these complexes are required to accurately capture the dynamics of the data. Our findings extend the model of loop extrusion and highlight the role of interactions between SMC complexes in organizing chromosomes.

Recent Advances in Learning and Control

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Publisher : Springer Science & Business Media
ISBN 13 : 1848001541
Total Pages : 283 pages
Book Rating : 4.8/5 (48 download)

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Book Synopsis Recent Advances in Learning and Control by : Vincent D. Blondel

Download or read book Recent Advances in Learning and Control written by Vincent D. Blondel and published by Springer Science & Business Media. This book was released on 2008-01-11 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is composed of invited papers on learning and control. The contents form the proceedings of a workshop held in January 2008, in Hyderabad that honored the 60th birthday of Doctor Mathukumalli Vidyasagar. The 14 papers, written by international specialists in the field, cover a variety of interests within the broader field of learning and control. The diversity of the research provides a comprehensive overview of a field of great interest to control and system theorists.

Computational Methods for Analyzing and Modeling Gene Regulation and 3D Genome Organization

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (125 download)

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Book Synopsis Computational Methods for Analyzing and Modeling Gene Regulation and 3D Genome Organization by : Anastasiya Belyaeva

Download or read book Computational Methods for Analyzing and Modeling Gene Regulation and 3D Genome Organization written by Anastasiya Belyaeva and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological processes from differentiation to disease progression are governed by gene regulatory mechanisms. Currently large-scale omics and imaging data sets are being collected to characterize gene regulation at every level. Such data sets present new opportunities and challenges for extracting biological insights and elucidating the gene regulatory logic of cells. In this thesis, I present computational methods for the analysis and integration of various data types used for cell profiling. Specifically, I focus on analyzing and linking gene expression with the 3D organization of the genome. First, I describe methodologies for elucidating gene regulatory mechanisms by considering multiple data modalities. I design a computational framework for identifying colocalized and coregulated chromosome regions by integrating gene expression and epigenetic marks with 3D interactions using network analysis. Then, I provide a general framework for data integration using autoencoders and apply it for the integration and translation between gene expression and chromatin images of naive T-cells. Second, I describe methods for analyzing single modalities such as contact frequency data, which measures the spatial organization of the genome, and gene expression data. Given the important role of the 3D genome organization in gene regulation, I present a methodology for reconstructing the 3D diploid conformation of the genome from contact frequency data. Given the ubiquity of gene expression data and the recent advances in single-cell RNA-sequencing technologies as well as the need for causal modeling of gene regulatory mechanisms, I then describe an algorithm as well as a software tool, difference causal inference (DCI), for learning causal gene regulatory networks from gene expression data. DCI addresses the problem of directly learning differences between causal gene regulatory networks given gene expression data from two related conditions. Finally, I shift my focus from basic biology to drug discovery. Given the current COVID19 pandemic, I present a computational drug repurposing platform that enables the identification of FDA approved compounds for drug repurposing and investigation of potential causal drug mechanisms. This framework relies on identifying drugs that reverse the signature of the infection in the space learned by an autoencoder and then uses causal inference to identify putative drug mechanisms.

RNA-Chromatin Interactions

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Publisher : Humana
ISBN 13 : 9781071606797
Total Pages : 0 pages
Book Rating : 4.6/5 (67 download)

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Book Synopsis RNA-Chromatin Interactions by : Ulf Andersson Vang Ørom

Download or read book RNA-Chromatin Interactions written by Ulf Andersson Vang Ørom and published by Humana. This book was released on 2020-07-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on RNAs interacting with chromatin and their function. Chapters guide readers through transcription, splicing, non-coding RNA function and manipulation of gene expression. 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, RNA-Chromatin Interactions: Methods and Protocols aims to be a starting-point to expand researchers experimental approaches towards the numerous outstanding questions in this new and expanding field.

Understanding Gene Regulation at a Fine-scale

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (111 download)

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Book Synopsis Understanding Gene Regulation at a Fine-scale by : Lin An

Download or read book Understanding Gene Regulation at a Fine-scale written by Lin An and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Mammalian genomes are spatially organized into different levels. The three-dimensional genome organization is essential for gene expression, as it reflects or possibly enables the physical interactions between distal regulatory elements and their target genes. The advances in chromatin conformation capture technologies in the past decade, have both expanded and refined our understanding of the multiple levels of chromatin organization. Among the current technologies, Hi-C technology shows the highest potential with its unbiased genome-wide coverage. It provides exceptional resources as well as challenges in understanding chromatin interactions in detail.Observations from Hi-C suggest that the chromatin forms frequent local interactions in specific regions, which are called as Topologically Associating Domains (TADs). While TADs are often interpreted as the structural units to study regulatory mechanism, previous observation shows that hierarchy is present in TADs, with smaller TADs nested within larger ones. Though several different TAD calling algorithms have been developed, limited research has been done to reliably identify hierarchical TAD structures and understand their roles in gene regulation. The first tool introduced in this thesis is an optimized nested TAD calling method (OnTAD), which can identify different levels of TADs in a biologically meaningful manner. By incorporating epigenetics and transcriptional information, our analyses bring new insights towards understanding the complex system of gene regulation.Investigations on site-to-site interactions (e.g. enhancer-gene pairs) from Hi-C data are often limited by their resolution. As Hi-C measures pair-wise interactions, improving resolution requires quadratic increasing of sequencing depth. Inspired by the super-resolution image technique, the second tool in this thesis is a deep convolutional neural network (HiCPlus) to impute the high-resolution Hi-C results from low-sequence depth Hi-C data. It shows the power to recover biologically and statistically significant chromatin interactions with improved resolution. We also applied HiCPlus to 20 different tissue/cell-types, which only have low-resolution experimental data, to provide the community with a useful resource to investigate chromatin interaction at a fine scale.Besides improving resolution on existing Hi-C data, the third tool in this thesis utilizes one-dimensional epigenetic features to predict three-dimensional chromatin interactions in Hi-C. It can provide support for studies in cell-types with no experimental Hi-C data available. Meanwhile, it also sheds light on understanding driving factors for chromatin interaction formation.In the last part of the thesis, I included our effort on generating comprehensive chromatin segmentation maps for cell populations in the mouse hematopoietic lineage. During this process, we observed an unexpected chromatin state that is enriched with high signal in most of the input features, termed as heterogeneous state. I presented our exploration in finding the cause of such state and solution to improve the final segmentation map.

Principles of Nutrigenetics and Nutrigenomics

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Publisher : Academic Press
ISBN 13 : 0128045876
Total Pages : 586 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Principles of Nutrigenetics and Nutrigenomics by : Raffaele De Caterina

Download or read book Principles of Nutrigenetics and Nutrigenomics written by Raffaele De Caterina and published by Academic Press. This book was released on 2019-09-22 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Nutrigenetics and Nutrigenomics: Fundamentals for Individualized Nutrition is the most comprehensive foundational text on the complex topics of nutrigenetics and nutrigenomics. Edited by three leaders in the field with contributions from the most well-cited researchers conducting groundbreaking research in the field, the book covers how the genetic makeup influences the response to foods and nutrients and how nutrients affect gene expression. Principles of Nutrigenetics and Nutrigenomics: Fundamentals for Individualized Nutrition is broken into four parts providing a valuable overview of genetics, nutrigenetics, and nutrigenomics, and a conclusion that helps to translate research into practice. With an overview of the background, evidence, challenges, and opportunities in the field, readers will come away with a strong understanding of how this new science is the frontier of medical nutrition. Principles of Nutrigenetics and Nutrigenomics: Fundamentals for Individualized Nutrition is a valuable reference for students and researchers studying nutrition, genetics, medicine, and related fields. Uniquely foundational, comprehensive, and systematic approach with full evidence-based coverage of established and emerging topics in nutrigenetics and nutrigenomics Includes a valuable guide to ethics for genetic testing for nutritional advice Chapters include definitions, methods, summaries, figures, and tables to help students, researchers, and faculty grasp key concepts Companion website includes slide decks, images, questions, and other teaching and learning aids designed to facilitate communication and comprehension of the content presented in the book

New Insights Into 3D Chromatin Organization and Function

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)

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Book Synopsis New Insights Into 3D Chromatin Organization and Function by : Lina Zheng

Download or read book New Insights Into 3D Chromatin Organization and Function written by Lina Zheng and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precise and delicate 3D genome organization is fundamental to cellular homeostasis. Big data generated by high-throughput technologies has granted great opportunities to deepen our understanding of chromatin organization and function, particularly for non-coding DNA sequences which have long been considered "junk DNAs". This dissertation aims at illuminating the structural importance of the non-coding DNA sequences and elucidating the modular organization of the 3D genome from histone modifications. First, I performed network analysis on Hi-C 3D contact data to identify non-coding DNA regions forming many spatial contacts with other regions ("hubs") without epigenetic signals that could maintain the global 3D chromatin structure. Furthermore, I employed a small-world network on epigenetic histone modification data to identify a group of active enhancers and promoters harboring many 3D contacts ("hotspots") which can maintain broad 3D chromatin organization beyond enhancer-promoter interactions. Deletion of hubs and hotspots can produce a profound impact on 3D chromatin organization and cell viability. In addition, through investigation of the histone modification across cell types, I identified the regulation associated modules ("RAMs") that can not only reflect the modular organization of the 3D genome but also be better aligned with the chromatin function. These studies provide new insights into 3D genome organization and function, navigating future efforts in the mechanistic investigation of the 3D genome.

Computational Methods for 3D Genome Analysis

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Author :
Publisher : Humana
ISBN 13 : 9781071641354
Total Pages : 0 pages
Book Rating : 4.6/5 (413 download)

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Book Synopsis Computational Methods for 3D Genome Analysis by : Ryuichiro Nakato

Download or read book Computational Methods for 3D Genome Analysis written by Ryuichiro Nakato and published by Humana. This book was released on 2024-10-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers the latest methods and analytical approaches used to study the computational analysis of three-dimensional (3D) genome structure. The chapters in this book are organized into six parts. Part One discusses different NGS assays and the regulatory mechanism of 3D genome folding by SMC complexes. Part Two presents analysis workflows for Hi-C and Micro-C in different species, including human, mouse, medaka, yeast, and prokaryotes. Part Three covers methods for chromatin loop detection, sub-compartment detection, and 3D feature visualization. Part Four explores single-cell Hi-C and the cell-to-cell variability of the dynamic 3D structure. Parts Five talks about the analysis of polymer modelling to simulate the dynamic behavior of the 3D genome structure, and Part Six looks at 3D structure analysis using other omics data, including prediction of 3D genome structure from the epigenome, double-strand break-associated structure, and imaging-based 3D analysis using seqFISH. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and tools, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Computational Methods for 3D Genome Analysis: Methods and Protocols is a valuable resource for researchers interested in using computational methods to further their studies in the nature of 3D genome organization.

Iscn 2020

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Publisher :
ISBN 13 : 9783318067064
Total Pages : 164 pages
Book Rating : 4.0/5 (67 download)

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Book Synopsis Iscn 2020 by : Jean McGowan-Jordan

Download or read book Iscn 2020 written by Jean McGowan-Jordan and published by . This book was released on 2020-12-31 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reprint of 'Cytogenetic and Genome Research' contains contributions discussing the subject in-depth. 'Cytogenetic and Genome Research' is a well-respected, international peer-reviewed journal in genetics.