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Computational Methods in Cell Biology
 
 

Computational Methods in Cell Biology, 1st Edition

 
Computational Methods in Cell Biology, 1st Edition,Anand R. Asthagiri,Adam Arkin,ISBN9780123884039
 
 
 

Methods in Cell Biology

Asthagiri   &   Arkin   

Academic Press

9780123884039

9780123884213

370

235 X 191

Computational methods are playing an ever-increasing role in cell biology, and this volume of Methods in Cell Biology focuses on the intimate and necessary connection with interpreting experimental data and proposing the next hypothesis and experiment.

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Key Features

  • Focuses on computational methods in cell biology
  • Split into 2 parts--data extraction and analysis to distill models and mechanisms, and developing and simulating models to make predictions and testable hypotheses
  • Emphasizes the intimate and necessary connection with interpreting experimental data and proposing the next hypothesis and experiment

Description

Computational methods are playing an ever increasing role in cell biology.  This volume of Methods in Cell Biology focuses on Computational Methods in Cell Biology and consists of two parts: (1) data extraction and analysis to distill models and mechanisms, and (2) developing and simulating models to make predictions and testable hypotheses. 

Readership

Researchers and students in cell, molecular and developmental biology

Anand R. Asthagiri

Adam Arkin

Computational Methods in Cell Biology, 1st Edition

  1. Principles of model building: an experimentation-aided approach to development of models for signaling networks
  2. Ambhighainath Ganesan and Andre Levchenko

  3. Integrated Inference and Analysis of Regulatory Networks From Multi-Level Measurements
  4. Christopher S. Poultney, Alex Greenfield, and Richard Bonneau

  5. Swimming upstream: identifying proteomic signals that drive transcriptional changes using the interactome and multiple "-omics" datasets
  6. Shao-shan Carol Huang and Ernest Fraenkel

  7. A framework for modeling the relationship between cellular steady-state and stimulus-responsiveness
  8. Paul Loriaux and Alexander Hoffmann

  9. Stochastic Modeling of Cellular Networks
  10. Jacob Stewart-Ornstein and Hana El-Samad

  11. Quantifying Traction Stresses in Adherent Cells
  12. Casey M. Kraning-Rush, Shawn P. Carey, Joseph P. Califano, and Cynthia A. Reinhart-King

  13. CellOrganizer: Image-derived Models of Subcellular Organization and Protein Distribution
  14. Robert F. Murphy

  15. Spatial Modeling of Cell Signaling Networks
  16. Ann E. Cowan, Ion I. Moraru, James C. Schaff, Boris M. Slepchenko, and Leslie M. Loew

  17. Stochastic models of cell protrusion arising from spatiotemporal signaling and adhesion dynamics
  18. Erik S. Welf and Jason M. Haugh

  19. Nonparametric Variable Selection and Modeling for Spatial and Temporal Regulatory Networks
  20. Anil Aswani, Mark D. Biggin, Peter Bickel and Claire Tomlin

  21. Quantitative Models of the Mechanisms that Control Genome-Wide Patterns of Animal Transcription Factor Binding
  22. Tommy Kaplan and Mark D. Biggin

  23. Computational Analysis of Live Cell Images of the Arabidopsis thaliana Plant
  24. Alexandre Cunha, Paul T. Tarr, Adrienne H. K. Roeder, Alphan Altinok, Eric Mjolsness, and Elliot M. Meyerowitz

  25. Multi-scale modeling of tissues using CompuCell3D
  26. Maciej H. Swat, Gilberto L. Thomas, Julio M. Belmonte, Abbas Shirinifard, Mitja Hmeljak, and James A. Glazier

  27. Multiscale Model of Fibrin Accumulation on the Blood Clot Surface and Platelet Dynamics

Zhiliang Xu, Scott Christley, Joshua Lioi, Cameron Harvey, Wenzhao Sun, Elliot D. Rosen, and Mark Alber

 
 

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