This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Zielgruppe
Illustrationen
11
71 farbige Abbildungen, 11 s/w Abbildungen
X, 377 p. 82 illus., 71 illus. in color.
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 21 mm
Gewicht
ISBN-13
978-3-030-51864-6 (9783030518646)
DOI
10.1007/978-3-030-51862-2
Schweitzer Klassifikation
Dr. Fabrício Alves Barbosa da Silva is a Public Health Researcher in the Scientific Computing Program (PROCC) at the Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, Brazil. His other publications include the Springer title Theoretical and Applied Aspects of Systems Biology (with Dr. Carels).
Dr. Nicolas Carels is a Titular Researcher in the Centre for Technological Development in Health (CDTS) at FIOCRUZ.
Dr. Marcelo Trindade dos Santos is a Full Technologist at the Department of Computational Modeling, National Laboratory of Scientific Computing (LNCC), Petrópolis, Brazil.
Dr. Francisco José Pereira Lopes is an Associate Professor in the Graduate Program in Nanobiosystems at the Federal University of Rio de Janeiro (UFRJ), Duque de Caxias, Brazil.
1. Network Medicine: Methods and Applications.- 2. Computational Tools to Compare Biological Networks.- 3. Functional Gene Networks and their Applications.- 4. A Review of Artificial Neural Networks for the Prediction of Essential Proteins.- 5. Transcriptograms: A Genome Wide Gene Expression Analysis Method.- 6. A Tutorial on Sobols' Global Sensitivity Analysis Applied to Biological Models.- 7. Reaction Network Models as a Tool to Study Gene Regulation and Cell Signaling in Development and Diseases.- 8. Challenges for the Optimization of Drug Therapy in the Treatment of Cancer.- 9. Opportunities and Challenges Provided by Boolean Modelling of Cancer Signalling Pathways.- 10. Integrating Omics Data to Prioritize Target Genes in Pathogenic Bacteria.- 11. Modelling Oxidative Stress Pathways.- 12. Computational Modeling in Virus Infections and Virtual Screening, Docking and Molecular Dynamics in Drug Design.- 13. Cellular Regulatory Network Modeling Applied to Breast Cancer.
