Computational Cell Biology

Rule-based Models and Applications in Biology.- Optimized Protein-protein Interaction Network usage with Context Filtering.- SignaLink: Multi-layered Regulatory Networks.- Interplay between Long Non-coding RNAs and microRNAs in Cancer.- Methods and Tools in Genome-wide Association Studies.- Identifying Differentially Expressed Genes using Fluorescence-Activated Cell Sorting (FACS) and RNA Sequencing from Low Input Samples.- Computational and Experimental Approaches to Predict Host-parasite Protein-protein Interactions.- An Integrative Approach to Virus-host Protein-protein Interactions.- The SQUAD Method for the Qualitative Modeling of Regulatory Networks.- miRNet - functional Analysis and Visual Exploration of miRNA-target Interactions in a Network Context.- Systems Biology Analysis to Understand Regulatory miRNA Networks in Lung Cancer.- Spatial Analysis of Functional Enrichment (SAFE) in Large Biological Networks.- Toward Large Scale Computational Prediction of Protein Complexes.- Computational Models of Cell Cycle Transitions.- Simultaneous Profiling of DNA Accessibility and Gene Expression Dynamics with ATAC.- Computational Network Analysis for Drug Toxicity Prediction.- Modeling the Epigenetic Landscape in Plant Development.- Developing Network Models of Multi-scale Host Responses Involved in Infections and Diseases.- Exploring Dynamics and Noise in Gonadotropin-Releasing Hormone (GnRH) Signaling. 

"The book recommends itself as an optimal starting point for understanding the current state of the art of data driven analyses, applied on high throughput datasets ... . The layout of the chapters makes them accessible to a wide variety of audiences from undergraduates, graduates and established researchers from a wide spectrum of fields from mathematics, computer science to biology and medicine. ... this book is a must have for the current research in this field." (Irina Ioana Mohorianu, zbMATH 1417.92006, 2019)