000 04355nam a22005535i 4500
001 978-3-031-05164-7
003 DE-He213
005 20220530132237.0
007 cr nn 008mamaa
008 220508s2022 sz | s |||| 0|eng d
020 _a9783031051647
_9978-3-031-05164-7
024 7 _a10.1007/978-3-031-05164-7
_2doi
072 7 _aPBKS
_2bicssc
072 7 _aCOM014000
_2bisacsh
072 7 _aPBKS
_2thema
082 0 4 _a003.3
_223
245 1 0 _aComputational Physiology
_h[electronic resource] :
_bSimula Summer School 2021 − Student Reports /
_cedited by Kimberly J. McCabe.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXI, 109 páginas47 ilustraciones, 45 ilustraciones in color.
_bonline resource.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aReports on Computational Physiology,
_x2730-7743 ;
_v12
505 0 _aA Pipeline for Automated Coordinate Assignment in Anatomically Accurate Biventricular Models 3D Simulations of Fetal and Maternal Ventricular Excitation for Investigating the Abdominal ECG -- Ordinary Differential Equation-based Modeling of Cells in Human Cartilage -- Conduction Velocity in Cardiac Tissue as Function of Ion Channel Conductance and Distribution -- Computational Prediction of Cardiac Electropharmacology - How Much Does the Model Matter? -- A Computational Study of Flow Instabilities in Aneurysms -- Investigating the Multiscale Impact of Deoxyadenosine Triphosphate (dATP) on Pulmonary Arterial Hypertension (PAH) Induced Heart Failure -- Identifying Ionic Channel Block in a Virtual Cardiomyocyte Population Using Machine Learning Classifiers.
506 0 _aOpen Access
520 _aThis open access volume compiles student reports from the 2021 Simula Summer School in Computational Physiology. Interested readers will find herein a number of modern approaches to modeling excitable tissue. This should provide a framework for tools available to model subcellular and tissue-level physiology across scales and scientific questions. In June through August of 2021, Simula held the seventh annual Summer School in Computational Physiology in collaboration with the University of Oslo (UiO) and the University of California, San Diego (UCSD). The course focuses on modeling excitable tissues, with a special interest in cardiac physiology and neuroscience. The majority of the school consists of group research projects conducted by Masters and PhD students from around the world, and advised by scientists at Simula, UiO and UCSD. Each group then produced a report that addreses a specific problem of importance in physiology and presents a succinct summary of the findings. Reports may not necessarily represent new scientific results; rather, they can reproduce or supplement earlier computational studies or experimental findings. Reports from eight of the summer projects are included as separate chapters. The fields represented include cardiac geometry definition (Chapter 1), electrophysiology and pharmacology (Chapters 2-5), fluid mechanics in blood vessels (Chapter 6), cardiac calcium handling and mechanics (Chapter 7), and machine learning in cardiac electrophysiology (Chapter 8).
650 0 _aMathematics-Data processing.
650 0 _aBiomathematics.
650 0 _aBiomedical engineering.
650 1 4 _aComputational Science and Engineering.
650 2 4 _aMathematical and Computational Biology.
650 2 4 _aBiomedical Engineering and Bioengineering.
650 2 4 _aComputational Mathematics and Numerical Analysis.
700 1 _aMcCabe, Kimberly J.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031051630
776 0 8 _iPrinted edition:
_z9783031051654
830 0 _aReports on Computational Physiology,
_x2730-7743 ;
_v12
856 4 0 _uhttps://doi.org/10.1007/978-3-031-05164-7
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
912 _aZDB-2-SOB
999 _c154502
_d154502