Download or read book Dynamics of Gene Networks in Cancer Research written by Paul Scott and published by . This book was released on 2017 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author's abstract: Cancer prevention treatments are being researched to see if an optimized treatment schedule would decrease the likelihood of a person being diagnosed with cancer. To do this we are looking at genes involved in the cell cycle and how they interact with one another. Through each gene expression during the life of a normal cell we get an understanding of the gene interactions and test these against those of a cancerous cell. First we construct a simplified network model of the normal gene network. Once we have this model we translate it into a transition matrix and force changes on it. Observing the effects of the changes we see the interactions each gene has with other genes within the network. Using the observed interactions we construct a set of differential equations that represent the network dynamics. Using numerical methods and the rough system of equations, we find an approximated system of equations that accurately predicts the dynamics of the normal gene network.
Download or read book Genome Chaos written by Henry H. Heng and published by Academic Press. This book was released on 2019-05-25 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genome Chaos: Rethinking Genetics, Evolution, and Molecular Medicine transports readers from Mendelian Genetics to 4D-genomics, building a case for genes and genomes as distinct biological entities, and positing that the genome, rather than individual genes, defines system inheritance and represents a clear unit of selection for macro-evolution. In authoring this thought-provoking text, Dr. Heng invigorates fresh discussions in genome theory and helps readers reevaluate their current understanding of human genetics, evolution, and new pathways for advancing molecular and precision medicine. Bridges basic research and clinical application and provides a foundation for re-examining the results of large-scale omics studies and advancing molecular medicine Gathers the most pressing questions in genomic and cytogenomic research Offers alternative explanations to timely puzzles in the field Contains eight evidence-based chapters that discuss 4d-genomics, genes and genomes as distinct biological entities, genome chaos and macro-cellular evolution, evolutionary cytogenetics and cancer, chromosomal coding and fuzzy inheritance, and more
Download or read book Structures and Boolean Dynamics in Gene Regulatory Networks written by Anthony Szedlak and published by . This book was released on 2017 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Research on Computational Methodologies in Gene Regulatory Networks written by Das, Sanjoy and published by IGI Global. This book was released on 2009-10-31 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization"--Provided by publisher.
Download or read book Cancer Gene Networks written by Usha Kasid and published by Methods in Molecular Biology. This book was released on 2018-11-17 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a valuable and timely resource for a broad audience with interests in basic and translational cancer biology, cancer drug development, as well as in the practice of personalized oncology. 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, Cancer Gene Networks aims to ensure successful results in the further study of this evolving and vital field. Ultimately these efforts will guide development of transformative strategies for cancer diagnosis and treatment.
Download or read book Probabilistic Boolean Networks written by Ilya Shmulevich and published by SIAM. This book was released on 2010-01-21 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.
Download or read book Gene Network Inference written by Alberto Fuente and published by Springer Science & Business Media. This book was released on 2014-01-03 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.
Download or read book Debating Cancer written by Henry H. Heng and published by World Scientific. This book was released on 2015-10-08 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Cancer research is at a crossroads. Traditionally, cancer has been thought of as a disease of gene mutation, where the stepwise accumulation of cancer gene mutations is the key, and the identification of common gene mutations has been considered to be essential for diagnosis and treatment. Despite extensive research efforts and accumulated knowledge on cancer genes and pathways, the clinical benefits of this traditional approach have been limited. Recently, cancer genome sequencing has revealed an extensive amount of genetic heterogeneity where the long-expected common mutation drivers have been difficult, if not impossible, to identify. These realities ultimately challenge the conceptual framework of current cancer biology. This book introduces a new concept of genome theory of cancer evolution, in an attempt to unify the field. Many important and representative, but often confusing, questions and paradoxes are critically analyzed. By comparing gene- and genome-based theories, the hidden flaws of many popular viewpoints are addressed. This discussion is intended to initiate a much-needed critical re-evaluation of current cancer research."--
Download or read book Systems Immunology and Infection Microbiology written by Bor-Sen Chen and published by Academic Press. This book was released on 2021-03-16 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Immunology and Infection Microbiology provides a large amount of biological system models, diagrams and flowcharts to illustrate development procedures and help users understand the results of systems immunology and infection microbiology. Chapters discuss systems immunology, systems infection microbiology, systematic inflammation and immune responses in restoration and regeneration process, systems' innate and adaptive immunity in infection process, systematic genetic and epigenetic pathogenic/defensive mechanism during bacterial infection on human cells is introduced, and the systematic genetic and epigenetic pathogenic/defensive mechanisms during viral infection on human cells. This book provides new big data-driven and systems-driven systems immunology and infection microbiology to researchers applying systems biology and bioinformatics in their work. It is also invaluable to several members of biomedical field who are interested in learning more about those approaches. Encompasses one applicable example in every chapter to illustrate the solution procedure from big data mining, network modeling, host/pathogen cross-talk detection, drug target identification and systems drug design Presents flowcharts to represent the development procedure of systematic immunology and infection in a very clear format Contains 100 color diagrams to help readers understand the related biological networks, their corresponding mechanisms, and significant network biomarkers for therapeutic drug design
Download or read book Genomic Control Process written by Isabelle S. Peter and published by Academic Press. This book was released on 2015-01-21 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic Control Process explores the biological phenomena around genomic regulatory systems that control and shape animal development processes, and which determine the nature of evolutionary processes that affect body plan. Unifying and simplifying the descriptions of development and evolution by focusing on the causality in these processes, it provides a comprehensive method of considering genomic control across diverse biological processes. This book is essential for graduate researchers in genomics, systems biology and molecular biology seeking to understand deep biological processes which regulate the structure of animals during development. Covers a vast area of current biological research to produce a genome oriented regulatory bioscience of animal life Places gene regulation, embryonic and postembryonic development, and evolution of the body plan in a unified conceptual framework Provides the conceptual keys to interpret a broad developmental and evolutionary landscape with precise experimental illustrations drawn from contemporary literature Includes a range of material, from developmental phenomenology to quantitative and logic models, from phylogenetics to the molecular biology of gene regulation, from animal models of all kinds to evidence of every relevant type Demonstrates the causal power of system-level understanding of genomic control process Conceptually organizes a constellation of complex and diverse biological phenomena Investigates fundamental developmental control system logic in diverse circumstances and expresses these in conceptual models Explores mechanistic evolutionary processes, illuminating the evolutionary consequences of developmental control systems as they are encoded in the genome
Download or read book Gene Regulatory Networks written by Guido Sanguinetti and published by Humana. This book was released on 2018-12-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores recent techniques for the computational inference of gene regulatory networks (GRNs). The chapters in this book cover topics such as methods to infer GRNs from time-varying data; the extraction of causal information from biological data; GRN inference from multiple heterogeneous data sets; non-parametric and hybrid statistical methods; the joint inference of differential networks; and mechanistic models of gene regulation dynamics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, descriptions of recently developed methods for GRN inference, applications of these methods on real and/ or simulated biological data, and step-by-step tutorials on the usage of associated software tools. Cutting-edge and thorough, Gene Regulatory Networks: Methods and Protocols is an essential tool for evaluating the current research needed to further address the common challenges faced by specialists in this field.
Download or read book Network Medicine written by Joseph Loscalzo and published by Harvard University Press. This book was released on 2017-02-01 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. With contributions from leading experts, Network Medicine introduces this rapidly evolving field of research, which promises to revolutionize the diagnosis and treatment of human diseases.
Download or read book Applied Statistics for Network Biology written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2011-04-08 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.
Download or read book Random Dynamical Systems written by Ludwig Arnold and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first systematic presentation of the theory of dynamical systems under the influence of randomness, this book includes products of random mappings as well as random and stochastic differential equations. The basic multiplicative ergodic theorem is presented, providing a random substitute for linear algebra. On its basis, many applications are detailed. Numerous instructive examples are treated analytically or numerically.
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 Mammography and Beyond written by National Research Council and published by National Academies Press. This book was released on 2001-06-04 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: X-ray mammography screening is the current mainstay for early breast cancer detection. It has been proven to detect breast cancer at an earlier stage and to reduce the number of women dying from the disease. However, it has a number of limitations. These current limitations in early breast cancer detection technology are driving a surge of new technological developments, from modifications of x-ray mammography such as computer programs that can indicate suspicious areas, to newer methods of detection such as magnetic resonance imaging (MRI) or biochemical tests on breast fluids. To explore the merits and drawbacks of these new breast cancer detection techniques, the Institute of Medicine of the National Academy of Sciences convened a committee of experts. During its year of operation, the committee examined the peer-reviewed literature, consulted with other experts in the field, and held two public workshops. In addition to identifying promising new technologies for early detection, the committee explored potential barriers that might prevent the development of new detection methods and their common usage. Such barriers could include lack of funding from agencies that support research and lack of investment in the commercial sector; complicated, inconsistent, or unpredictable federal regulations; inadequate insurance reimbursement; and limited access to or unacceptability of breast cancer detection technology for women and their doctors. Based on the findings of their study, the committee prepared a report entitled Mammography and Beyond: Developing Technology for Early Detection of Breast Cancer, which was published in the spring of 2001. This is a non-technical summary of that report.
Download or read book Application of Bioinformatics in Cancers written by Chad Brenner and published by MDPI. This book was released on 2019-11-20 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.
