Multi Omics For The Understanding Of Brain Diseases
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Multi Omics For The Understanding Of Brain Diseases
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Author :
language : en
Publisher:
Release Date : 2021-12-13
Multi Omics For The Understanding Of Brain Diseases written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-13 with Science categories.
Integrative Multi Omics For Diagnosis Treatments And Drug Discovery Of Aging Related Neuronal Diseases
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Author : Min Tang
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-23
Integrative Multi Omics For Diagnosis Treatments And Drug Discovery Of Aging Related Neuronal Diseases written by Min Tang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-23 with Science categories.
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.
Identifying The Key Pathogenic Factors Of Neurological Disorders By Integrating Multi Omics Data
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Author : Andrea Legati
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-30
Identifying The Key Pathogenic Factors Of Neurological Disorders By Integrating Multi Omics Data written by Andrea Legati and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Science categories.
Multi Omics Epigenomics And Computational Analysis Of Neurodegenerative Disorders
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Author : Manoj Kumar Jaiswal
language : en
Publisher: Frontiers Media SA
Release Date : 2022-08-03
Multi Omics Epigenomics And Computational Analysis Of Neurodegenerative Disorders written by Manoj Kumar Jaiswal and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-03 with Science categories.
Integrative Multi Omics In Biomedical Research
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Author :
language : en
Publisher:
Release Date : 2021-12-13
Integrative Multi Omics In Biomedical Research written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-13 with Science categories.
Biologically Interpretable Machine Learning Methods To Understand Gene Regulation For Disease Phenotypes
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Author : Ting Jin
language : en
Publisher:
Release Date : 2023
Biologically Interpretable Machine Learning Methods To Understand Gene Regulation For Disease Phenotypes written by Ting Jin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Gene expression and regulation is a key molecular mechanism driving the development of human diseases, particularly at the cell type level, but it remains elusive. For example in many brain diseases, such as Alzheimer's disease (AD), understanding how cell-type gene expression and regulation change across multiple stages of AD progression is still challenging. Moreover, interindividual variability of gene expression and regulation is a known characteristic of the human brain and brain diseases. However, it is still unclear how interindividual variability affects personalized gene regulation in brain diseases including AD, thereby contributing to their heterogeneity. Recent technological advances have enabled the detection of gene regulation activities through multi-omics (i.e., genomics, transcriptomics, epigenomics, proteomics). In particular, emerging single-cell sequencing technologies (e.g., scRNA-seq, scATAC-seq) allow us to study functional genomics and gene regulation at the cell-type level. Moreover, these multi-omics data of populations (e.g., human individuals) provide a unique opportunity to study the underlying regulatory mechanisms occurring in brain disease progression and clinical phenotypes. For instance, PsychAD is a large project generating single-cell multi-omics data including many neuronal and glial cell types, aiming to understand the molecular mechanisms of neuropsychiatric symptoms of multiple brain diseases (e.g., AD, SCZ, ASD, Bipolar) from over 1,000 individuals. However, analyzing and integrating large-scale multi-omics data at the population level, as well as understanding the mechanisms of gene regulation, also remains a challenge. Machine learning is a powerful and emerging tool to decode the unique complexities and heterogeneity of human diseases. For instance, Beebe-Wang, Nicosia, et al. developed MD-AD, a multi-task neural network model to predict various disease phenotypes in AD patients using RNA-seq. Additionally, with advancements in graph neural networks, which possess enhanced capabilities to represent sophisticated gene network structures like gene regulation networks that control gene expression. Efforts have also been made to capture the gene regulation heterogeneity of brain diseases. For instance, Kim SY has applied graph convolutional networks to offer personalized diagnostic insights through population graphs that correspond with disease progression. However, many existing machine learning methods are often limited to constructing accurate models for disease phenotype prediction and frequently lack biological interpretability or personalized insights, especially in gene regulation. Therefore, to address these challenges, my Ph.D. works have developed three machine-learning methods designed to decode the gene regulation mechanisms of human diseases. First, in this dissertation, I will present scGRNom, a computational pipeline that integrates multi-omic data to construct cell-type gene regulatory networks (GRNs) linking non-coding regulatory elements. Next, I will introduce i-BrainMap an interpretable knowledge-guided graph neural network model to prioritize personalized cell type disease genes, regulatory linkages, and modules. Thirdly, I introduce ECMaker, a semi-restricted Boltzmann machine (semi-RBM) method for identifying gene networks to predict diseases and clinical phenotypes. Overall, all our interpretable machine learning models improve phenotype prediction, prioritize key genes and networks associated with disease phenotypes, and are further aimed at enhancing our understanding of gene regulatory mechanisms driving disease progression and clinical phenotypes.
Calcific Aortic Valve Disease
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Author : Elena Aikawa
language : en
Publisher: BoD – Books on Demand
Release Date : 2013-06-12
Calcific Aortic Valve Disease written by Elena Aikawa and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-12 with Medical categories.
Due to population aging, calcific aortic valve disease (CAVD) has become the most common heart valve disease in Western countries. No therapies exist to slow this disease progression, and surgical valve replacement is the only effective treatment. Calcific Aortic Valve Disease covers the contemporary understanding of basic valve biology and the mechanisms of CAVD, provides novel insights into the genetics, proteomics, and metabolomics of CAVD, depicts new strategies in heart valve tissue engineering and regenerative medicine, and explores current treatment approaches. As we are on the verge of understanding the mechanisms of CAVD, we hope that this book will enable readers to comprehend our current knowledge and focus on the possibility of preventing disease progression in the future.
Heterogeneity Of Alzheimer S Disease
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Author : Francois Boller
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-08
Heterogeneity Of Alzheimer S Disease written by Francois Boller and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-08 with Medical categories.
The term "Alzheimer's disease" is currently used to refer to senile and also presenile dementia, but the heterogeneity of this disorder is demonstrated in many of its aspects. This is of great theoretical interest, and with the appearance of new therapeutic interventions, it may well also start to have very significant practical importance. To shed some light on the debate, the Fondation Ipsen organized an international symposium which took place on April 6, 1992. This volume contains the proceedings of this meeting, which was attended by researchers in epidemiology, clinical neurology and geriatrics, neuropsychology, neuropathology, molecular biology, and genetics.
The Neuronal Ceroid Lipofuscinoses Batten Disease
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Author : Sara Mole
language : en
Publisher: OUP Oxford
Release Date : 2011-03-10
The Neuronal Ceroid Lipofuscinoses Batten Disease written by Sara Mole and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-10 with Medical categories.
The neuronal ceroid lipofuscinoses are an extremely rare group of inherited neurodegenerative diseases that primarily affect children. Core symptoms of these conditions typically include epilepsy, cognitive decline and visual failure. These diseases are so rare that professionals who come into contact with them need a consultative reference work that enables them to become expert, or identify who to contact for more details. Fully updated and revised, this second edition continues to be the definitive volume on this devastating group of disorders. Written by an international collection of authorities in the field, it provides invaluable advice on their diagnosis, patient care, and new treatments that are available. This new edition of the definitive reference text on the neuronal ceroid lipofuscinoses will prove useful for clinicians, family physicians, research scientists, diagnostic laboratories, families affected by the disease as well as by workers in industry planning translational research.
Multi Omics Approaches To Study Signaling Pathways
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Author : Jyoti Sharma
language : en
Publisher: Frontiers Media SA
Release Date : 2020-11-18
Multi Omics Approaches To Study Signaling Pathways written by Jyoti Sharma and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-18 with Science categories.
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.