Download or read book Multiplex Single cell RNA Sequencing for Chemical Genomics and Spatial Transcriptomics written by Sanjay R. Srivatsan and published by . This book was released on 2021 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each of us begins life as a single fertilized cell. Following a seemingly predetermined set of cell divisions, the single cell morphs into a rough mass, then a hollowed tube, and finally becomes a recognizable neonatal form. How the information contained within a single cell si- multaneously specifies an organism’s anatomy, the construction of its organs, and the ability to cogitate on this very question, remains one of biology’s open questions. Although centuries of careful experiments devoted to characterizing development have revealed many important genes and mechanisms, the results of these experiments span different model organisms, developmental stages, cell populations and measurement modalities. Integrating this knowledge base into coher- ent representation requires a cellular scaffold that charts an organism’s development over the axes of time and space. Preliminary unified representations of developing organisms (e.g. C. Elegans, Zebrafish and Mouse) have been created by large-scale single cell RNA sequencing (scRNA-seq) efforts. These efforts have characterized the set of intermediates through which differentiating cells transit and have profiled the large number of cell types present in a developing organism. Although scRNA-seq data have proven powerful in cataloging cellular states, they lack crucial context: i) the experimental context afforded by the comparison of multiple conditions (e.g. wild-type vs. perturbation) and ii) a cell’s spatial context, a crucial factor driving its behavior. To address these knowledge gaps, over the course of my PhD I have developed two scRNA-seq technologies: 1) sci- Plex, a generalizable strategy to label cell populations and 2) sci-Space, a methodology to record acell’s spatial position in conjunction with its single cell transcriptome. (1) First I developed the sci-Plex protocol, an inexpensive and efficient method to label single cells through the chemical fixation of unmodified single stranded oligos to nuclei prior to scRNA- seq library preparation. To demonstrate proof-of-concept of the sci-Plex protocol, I performed a high-throughput, high-content drug screen at single cell resolution in 3 cancer cell lines; effectively conducting 4,500 independent scRNA-seq experiments at once. The resulting dataset enabled characterization of a drug’s potency, class, mechanism of action, and the heterogeneity of cellular responses induced upon drug treatment. For example, our scRNA-seq data showed that histone deacetylase inhibitors likely lead to cell death by trapping valuable acetyl molecules on chromatin. (2) Next, I extended the application of the sci-Plex protocol and developed the sci-Space method to capture spatial information from sectioned tissue. The fast and scalable sci-Space method uses patterned oligonucleotide barcodes in a regular array such that each spot contains a unique set of sequences. Then, to mark each nucleus’ coordinates on the grid, the barcodes are stamped onto a tissue section prior to disaggregation and library preparation. To showcase the power of sci-Space, I collected a dataset comprising over 120,000 cells originating from 14 sections of a single E14 mouse embryo. The resulting data uncovers the genes that drive the devel- oping organism’s body plan and reveals a widespread migration signature within neurons that form the developing brain. These data also provide a quantitative assessment of how cell state relates to spatial position within the developing embryo. Specifically, our estimates indicate that 25% of the variance in gene expression observed is attributable to spatial position. It is my hope that this technology will power the generation of a unified scaffold of development akin to the reference genome. I believe that such a unified representation will be instrumental in amassing data, accel- erating discovery and facilitating translation through the training of machine learning models of cellular state.

Download or read book Single Molecule and Single Cell Sequencing written by Yutaka Suzuki and published by Springer. This book was released on 2019-04-09 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of the recent technologies in single molecule and single cell sequencing. These sequencing technologies are revolutionizing the way of the genomic studies and the understanding of complex biological systems. The PacBio sequencer has enabled extremely long-read sequencing and the MinION sequencer has made the sequencing possible in developing countries. New developments and technologies are constantly emerging, which will further expand sequencing applications. In parallel, single cell sequencing technologies are rapidly becoming a popular platform. This volume presents not only an updated overview of these technologies, but also of the related developments in bioinformatics. Without powerful bioinformatics software, where rapid progress is taking place, these new technologies will not realize their full potential. All the contributors to this volume have been involved in the development of these technologies and software and have also made significant progress on their applications. This book is intended to be of interest to a wide audience ranging from genome researchers to basic molecular biologists and clinicians.

Download or read book Mobile DNA Finding Treasure in Junk written by Haig H. Kazazian and published by FT Press. This book was released on 2011 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation What we now know about mobile DNA--and the substantial roles it plays in humans, animals, and plants. & bull; & bull;Mobile DNA accounts for more than half of our genome: This book explains the important role it plays in shaping evolutionary change. & bull;A rich, thorough, and accessible introduction for all serious students, practitioners, and researchers in human and medical genetics, molecular biology, or evolutionary biology. & bull;By one of the field's leading researchers, Dr. Haig Kazazian. This book thoroughly reviews our current scientific understanding of the significant role that mobile genetic elements play in the evolution and function of genomes and organisms--from plants and animals to humans. Highly regarded geneticist Haig Kazazian offers an accessible intellectual history of the field's research strategies and concerns, explaining how advances opened up new questions, and how new tools and capabilities have encouraged progress in the field. Kazazian introduces the key strategies and approaches taken in leading laboratories (including his own) to gain greater insight into the large proportion of our genome that derives from mobile genetic elements, including viruses, plasmids, and transposons. He also presents intriguing insights into long-term research strategies that may lead to an even deeper understanding.

Download or read book Highly Multiplexed Single Cell in Situ Transcriptomic Analysis written by Lu Xiao (Ph.D.) and published by . This book was released on 2019 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial resolved detection and quantification of ribonucleic acid (RNA) molecules in single cell is crucial for the understanding of inherent biological issues, like mechanism of gene regulation or the development and maintenance of cell fate. Conventional methods for single cell RNA profiling, like single-cell RNA sequencing (scRNA-seq) or single-molecule fluorescent in situ hybridization (smFISH), suffer either from the loss of spatial information or the low detection throughput. In order to advance single-cell analysis, new approaches need to be developed with the ability to perform high-throughput detection while preserving spatial information of the subcellular location of target RNA molecules. Novel approaches for highly multiplexed single cell in situ transcriptomic analysis were developed by our group to enable single-cell comprehensive RNA profiling in their native spatial contexts. Reiterative FISH was demonstrated to be able to detect >100 RNA species in single cell in situ, while more sophisticated approaches, consecutive FISH (C-FISH) and switchable fluorescent oligonucleotide based FISH (SFO-FISH), have the potential for whole transcriptome profiling at the single molecule sensitivity. The introduction of a cleavable fluorescent tyramide even enables sensitive RNA profiling in intact tissues with high throughput. These approaches will have wide applications in studies of systems biology, molecular diagnosis and targeted therapies.

Download or read book Hepatocellular Carcinoma written by Yujin Hoshida and published by Springer. This book was released on 2019-08-05 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the current limitations and unmet needs in Hepatocellular Carcinoma (HCC) diagnosis, treatment, and prevention. It also provides newly emerging concepts, approaches, and technologies to address challenges. Topics covered include changing landscape of HCC etiologies in association with health disparities, framework of clinical management algorithm, new and experimental modalities of HCC diagnosis and prognostication, multidisciplinary treatment options including rapidly evolving molecular targeted therapies and immune therapies, multi-omics molecular characterization, and clinically relevant experimental models. The book is intended to assist collaboration between the diverse disciplines and facilitate forward and reverse translation between basic and clinical research by providing a comprehensive overview of relevant areas, covering epidemiological trend and population-level patient management strategies, new diagnostic and prognostic tools, recent advances in the standard care and novel therapeutic approaches, and new concepts in pathogenesis and experimental approaches and tools, by experts and opinion leaders in their respective fields. By thoroughly and concisely covering whole aspects of HCC care, Hepatocellular Carcinoma serves as a valuable reference for multidisciplinary readers, and promotes the development of personalized precision care strategies that lead to substantial improvement of disease burden and patient prognosis in HCC.

Download or read book The Mouse Nervous System written by Charles Watson and published by Academic Press. This book was released on 2011-11-28 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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.

Download or read book Statistical Simulation and Analysis of Single cell RNA seq Data written by Tianyi Sun and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent development of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies by revealing the genome-wide gene expression levels within individual cells. In contrast to bulk RNA sequencing, scRNA-seq technology captures cell-specific transcriptome landscapes, which can reveal crucial information about cell-to-cell heterogeneity across different tissues, organs, and systems and enable the discovery of novel cell types and new transient cell states. According to search results from PubMed, from 2009-2023, over 5,000 published studies have generated datasets using this technology. Such large volumes of data call for high-quality statistical methods for their analysis. In the three projects of this dissertation, I have explored and developed statistical methods to model the marginal and joint gene expression distributions and determine the latent structure type for scRNA-seq data. In all three projects, synthetic data simulation plays a crucial role. My first project focuses on the exploration of the Beta-Poisson hierarchical model for the marginal gene expression distribution of scRNA-seq data. This model is a simplified mechanistic model with biological interpretations. Through data simulation, I demonstrate three typical behaviors of this model under different parameter combinations, one of which can be interpreted as one source of the sparsity and zero inflation that is often observed in scRNA-seq datasets. Further, I discuss parameter estimation methods of this model and its other applications in the analysis of scRNA-seq data. My second project focuses on the development of a statistical simulator, scDesign2, to generate realistic synthetic scRNA-seq data. Although dozens of simulators have been developed before, they lack the capacity to simultaneously achieve the following three goals: preserving genes, capturing gene correlations, and generating any number of cells with varying sequencing depths. To fill in this gap, scDesign2 is developed as a transparent simulator that achieves all three goals and generates high-fidelity synthetic data for multiple scRNA-seq protocols and other single-cell gene expression count-based technologies. Compared with existing simulators, scDesign2 is advantageous in its transparent use of probabilistic models and is unique in its ability to capture gene correlations via copula. We verify that scDesign2 generates more realistic synthetic data for four scRNA-seq protocols (10x Genomics, CEL-Seq2, Fluidigm C1, and Smart-Seq2) and two single-cell spatial transcriptomics protocols (MERFISH and pciSeq) than existing simulators do. Under two typical computational tasks, cell clustering and rare cell type detection, we demonstrate that scDesign2 provides informative guidance on deciding the optimal sequencing depth and cell number in single-cell RNA-seq experimental design, and that scDesign2 can effectively benchmark computational methods under varying sequencing depths and cell numbers. With these advantages, scDesign2 is a powerful tool for single-cell researchers to design experiments, develop computational methods, and choose appropriate methods for specific data analysis needs. My third project focuses on deciding latent structure types for scRNA-seq datasets. Clustering and trajectory inference are two important data analysis tasks that can be performed for scRNA-seq datasets and will lead to different interpretations. However, as of now, there is no principled way to tell which one of these two types of analysis results is more suitable to describe a given dataset. In this project, we propose two computational approaches that aim to distinguish cluster-type vs. trajectory-type scRNA-seq datasets. The first approach is based on building a classifier using eigenvalue features of the gene expression covariance matrix, drawing inspiration from random matrix theory (RMT). The second approach is based on comparing the similarity of real data and simulated data generated by assuming the cell latent structure as clusters or a trajectory. While both approaches have limitations, we show that the second approach gives more promising results and has room for further improvements.

Download or read book Cancer Evolution written by Charles Swanton and published by Perspectives Cshl. This book was released on 2017 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tumor progression is driven by mutations that confer growth advantages to different subpopulations of cancer cells. As a tumor grows, these subpopulations expand, accumulate new mutations, and are subjected to selective pressures from the environment, including anticancer interventions. This process, termed clonal evolution, can lead to the emergence of therapy-resistant tumors and poses a major challenge for cancer eradication efforts. Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Medicine examines cancer progression as an evolutionary process and explores how this way of looking at cancer may lead to more effective strategies for managing and treating it. The contributors review efforts to characterize the subclonal architecture and dynamics of tumors, understand the roles of chromosomal instability, driver mutations, and mutation order, and determine how cancer cells respond to selective pressures imposed by anticancer agents, immune cells, and other components of the tumor microenvironment. They compare cancer evolution to organismal evolution and describe how ecological theories and mathematical models are being used to understand the complex dynamics between a tumor and its microenvironment during cancer progression. The authors also discuss improved methods to monitor tumor evolution (e.g., liquid biopsies) and the development of more effective strategies for managing and treating cancers (e.g., immunotherapies). This volume will therefore serve as a vital reference for all cancer biologists as well as anyone seeking to improve clinical outcomes for patients with cancer.

Download or read book Bioinformatics in Rice Research written by Manoj Kumar Gupta and published by Springer Nature. This book was released on 2021-09-24 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an up-to-date review of classic and advanced bioinformatics approaches and their utility in rice research. It summarizes databases and tools for analyzing DNA, proteins and gene expression profiles, mapping genetic variations, annotation of protein and RNA molecules, phylogenetic analysis, and pathway enrichment. In addition, it presents high-throughput technologies that are widely used to provide deep insights into the genetic architecture of important traits in the rice genome. The book subsequently discusses techniques for identifying RNA-protein, DNA-protein interactions, and molecular markers, including SNP and microsatellites, in the contexts of rice breeding and genetics. Lastly, it explores various tools that are used to identify and characterize non-coding RNA in rice and their potential role in rice research.

Download or read book Computational Methods for Single Cell Data Analysis written by Guo-Cheng Yuan and published by Humana Press. This book was released on 2019-02-14 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Molecular Neuroanatomy written by Fred W. Leeuwen and published by Elsevier Publishing Company. This book was released on 1988 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: For a thorough study of the dynamics of particular brain compounds it is now possible to use and combine various molecular neuroanatomical methods (e.g. in situ hybridization, receptor localisation and immunocytochemistry) in a quantitative way on whole brain sections maintaining morphological details. Molecular Neuroanatomy deals with the many practical aspects and recent developments in these areas. The theoretical background of many techniques is presented, as well as clear, step-by-step instructions on the preparation and application of all the methods and techniques described in this book. It will be invaluable to all those working in the field of neuroscience. Available in both hardback and paperback, with colour illustrations.

Download or read book RNA Seq Analysis Methods Applications and Challenges written by Filippo Geraci and published by Frontiers Media SA. This book was released on 2020-06-08 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Microfluidic Methods for Molecular Biology written by Chang Lu and published by Springer. This book was released on 2016-05-14 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the state-of-the-art research on molecular biology assays and molecular techniques enabled or enhanced by microfluidic platforms. Topics covered include microfluidic methods for cellular separations and single cell studies, droplet-based approaches to study protein expression and forensics, and microfluidic in situ hybridization for RNA analysis. Key molecular biology studies using model organisms are reviewed in detail. This is an ideal book for students and researchers in the microfluidics and molecular biology fields as well as engineers working in the biotechnology industry. This book also: Reviews exhaustively the latest techniques for single-cell genetic, epigenetic, metabolomic, and proteomic analysis Illustrates microfluidic approaches for inverse metabolic engineering, as well as analysis of circulating exosomes Broadens readers’ understanding of microfluidics convection-based PCR technology, microfluidic RNA-seq, and microfluidics for robust mobile diagnostics

Download or read book Manipulating the Mouse Embryo written by Andras Nagy and published by Cold Spring Harbor, N.Y. : Cold Spring Harbor Laboratory Press. This book was released on 2003 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides background information and detailed protocols for developing a mouse colony and using the animals in transgenic and gene-targeting experiments. The protocols list the animals, equipment, and reagents required and step-by-step procedures. Topics include in vitro culture of preimplantation embryos, surgical procedures, the production of chimeras, and the analysis of genome alterations. The third edition adds protocols for cloning mice, modifying embryonic stem cells, intracytoplasmic sperm injection, and cryopreservation of embryos.

Download or read book Handbook of Maize Its Biology written by Jeff L. Bennetzen and published by Springer Science & Business Media. This book was released on 2008-12-25 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Maize: Its Biology centers on the past, present and future of maize as a model for plant science research and crop improvement. The book includes brief, focused chapters from the foremost maize experts and features a succinct collection of informative images representing the maize germplasm collection.

Download or read book Extracellular Matrix Biology written by Richard O. Hynes and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In most tissues, cells are surrounded by an extracellular matrix (ECM) containing proteins such as collagen, laminin, and fibronectin. The ECM plays an important role in regulating cell function. ECM proteins bind to integrins and other cell surface receptors, activating signaling pathways that regulate cellular morphology, adhesion, cell migration, cell proliferation, and apoptosis. Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Biology covers all aspects of ECM composition and function, as well as alterations in the ECM that occur during development, tumorigenesis, and other disease states. The contributors examine the various ECM proteins and proteoglycans, ECM receptors such as integrins, and the signaling pathways that mediate the effects of the ECM on cells. They also describe ECM functions in specific biological contexts, including angiogenesis, hemostasis, and thrombosis. Covering not only the biochemistry and cell biology of the ECM but also its roles in development, physiology, and pathology, this volume is an indispensable reference for cell biologists and all those interested in exploring the myriad functions of the ECM.