Bioinformatics of Genome Regulation, Volume I, 2nd Edition

Bioinformatics of Genome Regulation, Volume I, 2nd Edition

Author: Yuriy L. Orlov

Publisher: Frontiers Media SA

Published:

Total Pages: 234

ISBN-13: 2889741427

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Publisher’s note: In this 2nd edition, the following article has been updated: Orlov YL, Tatarinova TV, Oparina NY, Galieva ER and Baranova AV (2021) Editorial: Bioinformatics of Genome Regulation, Volume I. Front. Genet. 12:803273. doi: 10.3389/fgene.2021.803273


Evolution of Translational Omics

Evolution of Translational Omics

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2012-09-13

Total Pages: 354

ISBN-13: 0309224187

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Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.


How Tobacco Smoke Causes Disease

How Tobacco Smoke Causes Disease

Author: United States. Public Health Service. Office of the Surgeon General

Publisher:

Published: 2010

Total Pages: 728

ISBN-13:

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This report considers the biological and behavioral mechanisms that may underlie the pathogenicity of tobacco smoke. Many Surgeon General's reports have considered research findings on mechanisms in assessing the biological plausibility of associations observed in epidemiologic studies. Mechanisms of disease are important because they may provide plausibility, which is one of the guideline criteria for assessing evidence on causation. This report specifically reviews the evidence on the potential mechanisms by which smoking causes diseases and considers whether a mechanism is likely to be operative in the production of human disease by tobacco smoke. This evidence is relevant to understanding how smoking causes disease, to identifying those who may be particularly susceptible, and to assessing the potential risks of tobacco products.


Epigenetic Biomarkers and Diagnostics

Epigenetic Biomarkers and Diagnostics

Author: Jose Luis Garcia-Gimenez

Publisher: Academic Press

Published: 2015-12-07

Total Pages: 698

ISBN-13: 0128019212

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Epigenetic Biomarkers and Diagnostics comprises 31 chapters contributed by leading active researchers in basic and clinical epigenetics. The book begins with the basis of epigenetic mechanisms and descriptions of epigenetic biomarkers that can be used in clinical diagnostics and prognostics. It goes on to discuss classical methods and next generation sequencing-based technologies to discover and analyze epigenetic biomarkers. The book concludes with an account of DNA methylation, post-translational modifications and noncoding RNAs as the most promising biomarkers for cancer (i.e. breast, lung, colon, etc.), metabolic disorders (i.e. diabetes and obesity), autoimmune diseases, infertility, allergy, infectious diseases, and neurological disorders. The book describes the challenging aspects of research in epigenetics, and current findings regarding new epigenetic elements and modifiers, providing guidance for researchers interested in the most advanced technologies and tested biomarkers to be used in the clinical diagnosis or prognosis of disease. - Focuses on recent progress in several areas of epigenetics, general concepts regarding epigenetics, and the future prospects of this discipline in clinical diagnostics and prognostics - Describes the importance of the quality of samples and clinical associated data, and also the ethical issues for epigenetic diagnostics - Discusses the advances in epigenomics technologies, including next-generation sequencing based tools and applications - Expounds on the utility of epigenetic biomarkers for diagnosis and prognosis of several diseases, highlighting the study of these biomarkers in cancer, cardiovascular and metabolic diseases, infertility, and infectious diseases - Includes a special section that discusses the relevance of biobanks in the maintenance of high quality biosamples and clinical-associated data, and the relevance of the ethical aspects in epigenetic studies


Integrative Multi-Omics for Diagnosis, Treatments, and Drug Discovery of Aging-Related Neuronal Diseases

Integrative Multi-Omics for Diagnosis, Treatments, and Drug Discovery of Aging-Related Neuronal Diseases

Author: Min Tang

Publisher: Frontiers Media SA

Published: 2022-11-23

Total Pages: 224

ISBN-13: 2832506674

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As the cost of high-throughput sequencing goes down, huge volumes of biological and medical data have been produced from various sequencing platforms at multiple molecular levels including genome, transcriptome, proteome, epigenome, metabolome, and so on. For a long time, data analysis on single molecular levels has paved the way to answer many important research questions. However, many Aging-Related Neuronal Diseases (ARNDs) and Central Nervous System (CNS) aging involve interactions of molecules from multiple molecular levels, in which conclusions based on single molecular levels are usually incomplete and sometimes misleading. In these scenarios, multi-omics data analysis has unprecedentedly helped capture much more useful information for the diagnosis, treatment, prognosis, and drug discovery of ARNDs. The first step towards a multi-omics analysis is to establish reliable and robust multi-omics datasets. In the past years, a few important ARNDs-associated multi-omics databases like Allen Brain have been constructed, which raised immediate needs like data curation, normalization, interpretation, and visualization for integrative multi-omics explorations. Though there have been several well-established multi-omics databases for ARNDs like Alzheimer’s disease, similar databases for other ARNDs are still in urgent need. After the databases establish, many computational tools and experiential strategies should be developed specifically for them. First, the multi-omics data are usually extremely noisy, complex, heterogeneous and in high dimension, which presents the need for appropriate denoising and dimension reduction methods. Second, since the multi-omics and non-omics data like pathological and clinical data are usually in different data spaces, a useful algorithm to mapping them into the same data space and integrate them is nontrivial. In the multi-omics era, there are numerous data-centric tools for the integration of multi-omics datasets, which could be generally divided into three categories: unsupervised, supervised, and semi-supervised methods. Commonly used algorithms include but not limited to Bayesian-based methods, Network-based methods, multi-step analysis methods, and multiple kernel learning methods. Third, methods are needed in studying and verifying the association between two or more levels of multi-omics data and non-omics data. For example, expression quantitative trait loci (eQTL) analysis is widely used to infer the association between a single nucleotide polymorphism (SNP) and the expression of a gene. Recently, the association between omics data and more complex data like pathological and clinical imaging data has been a hot research topic. The outcomes may reveal the underlying molecular mechanism and promote de novo drug design as well as drug repurposing for ARNDs. Here, we welcome investigators to share their Original Research, Review, Mini Review, Hypothesis and Theory, Perspective, Conceptual Analysis, Data Report, Brief Research Report, Code related to multi-omics studies of ARNDs, which can be applied for better diagnosis, treatment, prognosis and drug discovery of human diseases in the future era of precision medicine. Potential contents include but are not limited to the following: ▪ Methods for integrating, interpreting, or visualizing two or more omics data. ▪ Methods for identifying interactions between different data modalities. ▪ Methods for disease subtyping, biomarker prediction. ▪ Machine learning or deep learning methods on dimensional reduction and feature selection for big noisy data. ▪ Methods for studying the association among different omics data or between omics and non-omics data like clinical, pathological, and imaging data. ▪ Review of multi-omics resource about ARNDs and/or CNS aging. ▪ Experimental validation of biomarkers identified from multi-omics data analysis. ▪ Disease diagnosis and prognosis prediction from imaging and non-imaging data analysis, or both. ▪ Clinical applications or validations of findings from multi-omics data analysis.


Understanding convergent evasion mechanisms in cancer and chronic infection: Implications for immunotherapy

Understanding convergent evasion mechanisms in cancer and chronic infection: Implications for immunotherapy

Author: Matthias Theobald

Publisher: Frontiers Media SA

Published: 2024-06-04

Total Pages: 247

ISBN-13: 2832550010

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The complex interactions between the innate and adaptive immune systems function to recognize and clear pathogens or transformed cells, but inefficient interactions between these two systems can result in harmful immunologic responses including chronic infections and the development of cancer. Several hallmarks of dysfunctional adaptive immune responses often detected in tumors share specific features with ineffective immunity in chronic infections. The members of the micromilieu actively participate in the process of tumorigenesis or chronification of infection by modulating innate and adaptive immune system interactions leading e.g. to insufficient T cell responses. The best example is given by the acquisition of an “exhausted” state of cytotoxic CD8+ T cells (CTLs) responding to chronic infections or tumors that are associated with elevated expression of inhibitory receptors and impaired cytokine response. Targeting these major inhibitory pathways by immune checkpoint blockers represents a prime example of successful clinical translation of tumor-specific immunotherapies. Understanding the mechanisms behind (mal)adaptations of the immune system is crucial for achieving therapeutic benefits. The establishment and co-evolution of a dynamic microenvironment niche constituted by the recruitment of numerous cell types dampen immune responses and thus contribute to the development of neoplastic transformation as well as infection. Although there are examples of successful immunotherapeutic approaches (CAR-T cells, immune checkpoint inhibitors, or mRNA vaccination), a large percentage of patients with cancer or chronic infections still do not benefit from these therapies or develop severe immune-related adverse events. The reasons for these failures are not well understood. A possible explanation might be that current immunotherapies target predominantly the effector arm of the immune system by trying to reactivate dysfunctional T cells, but do not sufficiently address the influence of the innate immune system and the contributions of the tumor microenvironment (TME) niche. The main problem we would like to address in this special issue is how inappropriate function of the innate immune system affects adaptive immunity and contributes to inefficient anti-cancer immunity and chronification of infections. The central goal is to provide a more precise understanding of the various (common and novel) immune evasion mechanisms in cancers and in chronic infections to obtain a detailed map of common and disease-specific immune escape checkpoints. To that aim, we want to compile a wide array of interdisciplinary studies exploring a comparative and multi-layered analysis of mechanisms responsible for inefficient immune responses, including novel approaches i.e. multi-omics or epigenetic signaling. We would also like to combine studies from different fields, including basic and clinical immunology, oncology, and virology/microbiology. We welcome the submission of Original Research, Review, Mini-Review, Methods, Case report, and Perspective articles that cover, but are not limited to the following topics: • Convergent mechanisms supporting immune escape in preclinical models (tumors and chronic infections) • Convergent evasion mechanisms mediated by tumor-infiltrating suppressive cells (Treg, MDSC, macro-phages, soluble mediators, signaling, metabolism, ...) • Convergent immune evasion mechanisms mediated by chronic infection (viral or parasite) • Novel strategies to modulate the TME by direct or indirect targeting of immune suppressor cells. • Approaches to enhance persistence and resilience of anticancer T cells • Combinatorial therapeutic strategies (mRNA, antibodies, immune checkpoint blockers …) that target convergent immune evasion mechanisms Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this topic.


Molecular Epidemiology

Molecular Epidemiology

Author: Paul A. Schulte

Publisher: Academic Press

Published: 2012-12-02

Total Pages: 609

ISBN-13: 0323138578

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This book will serve as a primer for both laboratory and field scientists who are shaping the emerging field of molecular epidemiology. Molecular epidemiology utilizes the same paradigm as traditional epidemiology but uses biological markers to identify exposure, disease or susceptibility. Schulte and Perera present the epidemiologic methods pertinent to biological markers. The book is also designed to enumerate the considerations necessary for valid field research and provide a resource on the salient and subtle features of biological indicators.