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- Principles of model building: an experimentation-aided approach to development of models for signaling networks
- Integrated Inference and Analysis of Regulatory Networks From Multi-Level Measurements
- Swimming upstream: identifying proteomic signals that drive transcriptional changes using the interactome and multiple "-omics" datasets
- A framework for modeling the relationship between cellular steady-state and stimulus-responsiveness
- Stochastic Modeling of Cellular Networks
- Quantifying Traction Stresses in Adherent Cells
- CellOrganizer: Image-derived Models of Subcellular Organization and Protein Distribution
- Spatial Modeling of Cell Signaling Networks
- Stochastic models of cell protrusion arising from spatiotemporal signaling and adhesion dynamics
- Nonparametric Variable Selection and Modeling for Spatial and Temporal Regulatory Networks
- Quantitative Models of the Mechanisms that Control Genome-Wide Patterns of Animal Transcription Factor Binding
- Computational Analysis of Live Cell Images of the Arabidopsis thaliana Plant
- Multi-scale modeling of tissues using CompuCell3D
- Multiscale Model of Fibrin Accumulation on the Blood Clot Surface and Platelet Dynamics
Ambhighainath Ganesan and Andre Levchenko
Christopher S. Poultney, Alex Greenfield, and Richard Bonneau
Shao-shan Carol Huang and Ernest Fraenkel
Paul Loriaux and Alexander Hoffmann
Jacob Stewart-Ornstein and Hana El-Samad
Casey M. Kraning-Rush, Shawn P. Carey, Joseph P. Califano, and Cynthia A. Reinhart-King
Robert F. Murphy
Ann E. Cowan, Ion I. Moraru, James C. Schaff, Boris M. Slepchenko, and Leslie M. Loew
Erik S. Welf and Jason M. Haugh
Anil Aswani, Mark D. Biggin, Peter Bickel and Claire Tomlin
Tommy Kaplan and Mark D. Biggin
Alexandre Cunha, Paul T. Tarr, Adrienne H. K. Roeder, Alphan Altinok, Eric Mjolsness, and Elliot M. Meyerowitz
Maciej H. Swat, Gilberto L. Thomas, Julio M. Belmonte, Abbas Shirinifard, Mitja Hmeljak, and James A. Glazier
Zhiliang Xu, Scott Christley, Joshua Lioi, Cameron Harvey, Wenzhao Sun, Elliot D. Rosen, and Mark Alber
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.
- 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
Researchers and students in cell, molecular and developmental biology
- No. of pages:
- © Academic Press 2012
- 13th April 2012
- Academic Press
- Hardcover ISBN:
- eBook ISBN:
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