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  • 1
    UID:
    edochu_18452_29233
    Format: 1 Online-Ressource (24 Seiten)
    Content: Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.
    Content: Peer Reviewed
    In: Lausanne : Frontiers Media, 14
    Language: English
    URL: Volltext  (kostenfrei)
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  • 2
    UID:
    almahu_9949383739202882
    Format: 1 online resource (xviii, 167 pages)
    Edition: First edition.
    ISBN: 9780429330179 , 0429330170 , 9781000682564 , 1000682560 , 9781000682748 , 1000682749 , 9781000682922 , 1000682927
    Series Statement: Chapman & Hall/CRC Mathematical and Computational Biology
    Content: Praise for Computational Systems BiologyApproaches in Cancer Research: "Complex concepts are written clearly and with informative illustrations and useful links. The book is enjoyable to read yet provides sufficient depth to serve as a valuable resource for both students and faculty."--Trey Ideker, Professor of Medicine, UC Xan Diego, School of Medicine "This volume is attractive because it addresses important and timely topics for research and teaching on computational methods in cancer research. It covers a broad variety of approaches, exposes recent innovations in computational methods, and provides acces to source code and to dedicated interactive web sites." -- Yves Moreau, Department of Electrical Engineering, SysBioSys Centre for Computational Systems Biology, University of Leuven With the availability of massive amounts of data in biology, the need for advanced computational tools and techniques is becoming increasingly important and key in understanding biology in disease and healthy states. This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. The book provides an important reference and teaching material in the field of computational biology in general and cancer systems biology in particular. The book presents a list of modern approaches in systems biology with application to cancer research and beyond. It is structured in a didactic form such that the idea of each approach can easily be grasped from the short text and self-explanatory figures. The coverage of topics is diverse: from pathway resources, through methods for data analysis and single data analysis to drug response predictors, classifiers and image analysis using machine learning and artificial intelligence approaches. Features Up to date using a wide range of approaches Applicationexample in each chapter Online resources with useful applications'
    Note: Chapter 1. Pathway Databases and Network Resources in Cancer Chapter 2. Tumor Microenvironment Studies in Immuno-oncology Research Chapter 3. Multi-level Data Analysis: Tools and Approaches Chapter 4. Mathematical Modelling of Signalling Networks in Cancer Chapter 5. Single Cell Analysis in Cancer Chapter 6. Patient Stratification and Treatment Response Prediction
    Additional Edition: Print version: Computational Systems Biology Approaches in Cancer Research. Boca Raton : CRC Press, 2019 ISBN 0367344211
    Additional Edition: ISBN 9780367344214
    Language: English
    Keywords: Electronic books. ; Electronic books.
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