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Record Nr. |
UNISA996418213803316 |
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Titolo |
Mathematical and computational oncology : second International Symposium, ISMCO 2020, San Diego, CA, USA, October 8-10, 2020, proceedings / / George Bebis [and four others] editors |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2020] |
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©2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XXII, 119 p. 34 illus., 25 illus. in color.) |
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Collana |
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Lecture Notes in Bioinformatics ; ; 12508 |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the Second International Symposium on Mathematical and Computational Oncology, ISMCO 2020, which was supposed to be held in San Diego, |
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CA, USA, in October 2020, but was instead held virtually due to the COVID-19 pandemic. The 6 full papers and 4 short papers presented together with 1 invited talk were carefully reviewed and selected from 28 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; general cancer computational biology; and posters. |
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