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Advances in Molecular Pathology 1st Edition at Meripustak

Advances in Molecular Pathology 1st Edition by Tsongalis, Gregory , Elsevier

Books from same Author: Tsongalis, Gregory

Books from same Publisher: Elsevier

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  • General Information  
    Author(s)Tsongalis, Gregory
    PublisherElsevier
    Edition1st Edition
    ISBN9780323940399
    Pages240
    LanguageEnglish
    Publish YearNovember 2022

    Description

    Elsevier Advances in Molecular Pathology 1st Edition by Tsongalis, Gregory

    Advances in Molecular Pathology reviews the year's most important findings and updates within the field in order to provide molecular pathologists with the current clinical information they need to improve patient outcomes. A distinguished editorial board, led by Dr. Gregory Tsongalis, identifies key areas of major progress and controversy and invites preeminent specialists to contribute original articles devoted to these topics. These insightful overviews in molecular pathology inform and enhance clinical practice by bringing concepts to a clinical level and exploring their everyday impact on patient care.Provides in-depth, clinical reviews in molecular pathology, providing actionable insights for clinical practice. Presents the latest information in the field under the leadership of an experienced editorial team. Authors synthesize and distill the latest research and practice guidelines to create these timely topic-based reviews. Polygenic Risk Scores in Clinical CareHereditary Cancer and Cancer Predisposition SyndromesExpanding the Molecular Landscape of Cutaneous T-Cell LymphomaHigh-Grade B-cell LymphomasMolecular Advances in Nodal Peripheral T-Cell LymphomaPrevalence and Clinical Disease Severity of Respiratory Coinfections During the Coronavirus Disease 2019 PandemicMultiple MyelomaApplications of Long-Read Sequencing Technology in Clinical GenomicsSLCO1B1 Pharmacogenetics in PediatricsImplementation of a Clinical Pharmacogenomics Service in a Large Freestanding Pediatric Health SystemArtificial Intelligence/Machine Learning and Mechanistic Modeling Approaches as Translational Tools to Advance Personalized Medicine DecisionsAdvances in Cell-Free DNA



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