Mathematical and computational oncol...
ISMCO (Symposium) (2020 :)

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  • Mathematical and computational oncology = second International Symposium, ISMCO 2020, San Diego, CA, USA, October 8-10, 2020 : proceedings /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Mathematical and computational oncology/ edited by George Bebis ... [et al.].
    Reminder of title: second International Symposium, ISMCO 2020, San Diego, CA, USA, October 8-10, 2020 : proceedings /
    remainder title: ISMCO 2020
    other author: Bebis, George.
    corporate name: ISMCO (Symposium)
    Published: Cham :Springer International Publishing : : 2020.,
    Description: xxii, 119 p. :ill. (some col.), digital ;24 cm.
    [NT 15003449]: Invited -- Plasticity in cancer cell populations: biology, mathematics and philosophy of cancer -- Statistical and Machine Learning Methods for Cancer Research -- CHIMERA: Combining Mechanistic Models and Machine Learning for Personalized Chemotherapy and Surgery Sequencing in Breast Cancer -- Fine-Tuning Deep Learning Architectures for Early Detection of Oral Cancer -- Discriminative Localized Sparse Representations for Breast Cancer Screening -- Activation vs. Organization: Prognostic Implications of T and B cell Features of the PDAC Microenvironment -- On the use of neural networks with censored time-to-event data -- Mathematical Modeling for Cancer Research -- tugHall: a tool to reproduce Darwinian evolution of cancer cells for simulation-based personalized medicine -- General Cancer Computational Biology -- The potential of single cell RNA-sequencing data for the prediction of gastric cancer serum biomarkers -- Poster -- Theoretical Foundation of the Performance of Phylogeny-Based Somatic Variant Detection -- Detecting subclones from spatially resolved RNA-seq data -- Novel driver synonymous mutations in the coding regions of GCB lymphoma patients improve the transcription levels of BCL2.
    Contained By: Springer Nature eBook
    Subject: Oncology - Congresses. - Mathematical models -
    Online resource: https://doi.org/10.1007/978-3-030-64511-3
    ISBN: 9783030645113
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