Computational Methods in Cell Biology

<ol> <li>Principles of model building: an experimentation-aided approach to development of models for signaling networks<br></li> <li>Integrated Inference and Analysis of Regulatory Networks From Multi-Level Measurements<br></li> <li>Swimming upstream: identifying proteomic signals that drive transcriptional changes using the interactome and multiple "-omics" datasets<br></li> <li>A framework for modeling the relationship between cellular steady-state and stimulus-responsiveness<br></li> <li>Stochastic Modeling of Cellular Networks<br></li> <li>Quantifying Traction Stresses in Adherent Cells<br></li> <li>CellOrganizer: Image-derived Models of Subcellular Organization and Protein Distribution<br></li> <li>Spatial Modeling of Cell Signaling Networks<br></li> <li>Stochastic models of cell protrusion arising from spatiotemporal signaling and adhesion dynamics<br></li> <li>Nonparametric Variable Selection and Modeling for Spatial and Temporal Regulatory Networks<br></li> <li>Quantitative Models of the Mechanisms that Control Genome-Wide Patterns of Animal Transcription Factor Binding<br></li> <li>Computational Analysis of Live Cell Images of the Arabidopsis thaliana Plant<br></li> <li>Multi-scale modeling of tissues using CompuCell3D<br></li> <li>Multiscale Model of Fibrin Accumulation on the Blood Clot Surface and Platelet Dynamics</li></ol>