Computational Cell Biology, 1st ed. 2018 Methods and Protocols Methods in Molecular Biology Series, Vol. 1819
Coordonnateurs : von Stechow Louise, Santos Delgado Alberto
This volume details computational techniques for analyses of a wide range of biological contexts, providing an overview of the most up-to-date techniques used in the field. Chapters guide the reader through available data resources and analysis methods and easy-to-follow protocols that allow the researcher to apply various computational tools to an array of different data types. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory and computational protocols, and tips on troubleshooting and avoiding known pitfalls.
Authoritative and cutting-edge, Computational Cell Biology: Method and Protocols aims to ensure successful results in the further study of this vital field.
Part I: Big Data- and its Implications in Cell Biology
1. Rule-based Models and Applications in Biology
Álvaro Bustos, Ignacio Fuenzalida1, Rodrigo Santibáñez, Tomás Pérez-Acle, and
Alberto J.M. Martin
2. Optimized Protein-protein Interaction Network usage with Context Filtering
Natalia Pietrosemolia and Maria Pamela Dobay
Part II: Data-driven Analyses of High-throughput Datasets
3. SignaLink: Multi-layered Regulatory Networks
Luca Csabai1, Márton Ölbei, Aidan Budd, Tamás Korcsmáros, and Dávid Fazekas
4. Interplay between Long Non-coding RNAs and microRNAs in Cancer
Francesco Russo, Giulia Fiscon, Federica Conte, Milena Rizzo, Paola Paci, and Marco Pellegrini
5. Methods and Tools in Genome-wide Association Studies
Anja C. Gumpinger, Damian Roqueiro, Dominik G. Grimm, and Karsten M. Borgwardt
Part III: Network-based Modeling of Cellular Phenotypes
6. Identifying Differentially Expressed Genes using Fluorescence-Activated Cell Sorting (FACS) and RNA Sequencing from Low Input Samples
Natalie M Clark, Adam P Fisher, and Rosangela Sozzani
7. Computational and Experimental Approaches to Predict Host-parasite Protein-protein Interactions
Yesid Cuesta-Astroz and Guilherme Oliveira
8. An Integrative Approach to Virus-host Protein-protein Interactions
Helen V Cook1 and Lars Juhl Jensen
9. The SQUAD Method for the Qualitative Modeling of Regulatory Networks
Akram M´endez , Carlos Ram´ırez, Mauricio P´erez Mart´ınez, and Luis Mendoza
10. miRNet - functional Analysis and Visual Exploration of miRNA-target Interactions in a Network Context
Yannan Fan and Jianguo Xia
11. Systems Biology Analysis to Understand Regulatory miRNA Networks in Lung Cancer
Meik Kunz, Andreas Pittroff, and Thomas Dandekar
12. Spatial Analysis of Functional Enrichment (SAFE) in Large Biological Networks Anastasia BaryshnikovaPart IV: Mathematical Modeling of Cellular Phenotypes
13. Toward Large Scale Computational Prediction of Protein Complexes Simone Rizzetto and Attila Csikász-Nagy
14. Computational Models of Cell Cycle Transitions
Hernansaiz-Ballesteros, Rosa, Jenkins, Kirsten, and Csikász-Nagy, Attila
15. Simultaneous Profiling of DNA Accessibility and Gene Expression Dynamics with ATAC-Seq and RNA-Seq
David G. Hendrickson, Ilya Soifer, Bernd Wranik, David Botstein, R. Scott McIsaac
16. Computational Network Analysis for Drug Toxicity Prediction
Hardt C, Bauer C, Schuchhardt J, and Herwig R
17. Modeling the Epigenetic Landscape in Plant Development
Davila-Velderrain, Jose, Caldu-Primo, Jose Luis, Martinez-Garcia, Juan Carlos, and Alvarez-Buylla, Elena R.
18. Developing Network Models of Multi-scale Host Responses Involved in Infections and Diseases
Rohith Palli and Juilee Thakar
PART V: Computational Analyses of Heterogenous Cell Populations and Organisms
19. Exploring Dynamics and Noise in Gonadotropin-Releasing Hormone (GnRH) SignalingMargaritis Voliotisa, Kathryn L. Garnerc, Hussah Alobaidc, Krasimira Tsaneva-Atanasovaa, and Craig A. McArdlec
Includes cutting-edge methods and protocols
Provides step-by-step detail essential for reproducible results
Contains key notes and implementation advice from the experts
Ouvrage de 436 p.
17.8x25.4 cm
Mots-clés :
high-throughput; PLS regression; datasets; gene-set enrichment; network inference