Computational Methods in Cell Biology, Volume 110

1. Principles of model building: an experimentation-aided approach to development of models for signaling networks

Ambhighainath Ganesan and Andre Levchenko

2. Integrated Inference and Analysis of Regulatory Networks From Multi-Level Measurements

Christopher S. Poultney, Alex Greenfield, and Richard Bonneau

3. Swimming upstream: identifying proteomic signals that drive transcriptional changes using the interactome and multiple "-omics" datasets

Shao-shan Carol Huang and Ernest Fraenkel

4. A framework for modeling the relationship between cellular steady-state and stimulus-responsiveness

Paul Loriaux and Alexander Hoffmann

5. Stochastic Modeling of Cellular Networks

Jacob Stewart-Ornstein and Hana El-Samad

6. Quantifying Traction Stresses in Adherent Cells

Casey M. Kraning-Rush, Shawn P. Carey, Joseph P. Califano, and Cynthia A. Reinhart-King

7. CellOrganizer: Image-derived Models of Subcellular Organization and Protein Distribution

Robert F. Murphy

8. Spatial Modeling of Cell Signaling Networks

Ann E. Cowan, Ion I. Moraru, James C. Schaff, Boris M. Slepchenko, and Leslie M. Loew

9. Stochastic models of cell protrusion arising from spatiotemporal signaling and adhesion dynamics

Erik S. Welf and Jason M. Haugh

10. Nonparametric Variable Selection and Modeling for Spatial and Temporal Regulatory Networks

Anil Aswani, Mark D. Biggin, Peter Bickel and Claire Tomlin

11. Quantitative Models of the Mechanisms that Control Genome-Wide Patterns of Animal Transcription Factor Binding

Tommy Kaplan and Mark D. Biggin

12. Computational Analysis of Live Cell Images of the Arabidopsis thaliana Plant

Alexandre Cunha, Paul T. Tarr, Adrienne H. K. Roeder, Alphan Altinok, Eric Mjolsness, and Elliot M. Meyerowitz

13. Multi-scale modeling of tissues using CompuCell3D

Maciej H. Swat, Gilberto L. Thomas, Julio M. Belmonte, Abbas Shirinifard, Mitja Hmeljak, and James A. Glazier

14. 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

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