Download computational systems biology of cancer in pdf or read computational systems biology of cancer in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get computational systems biology of cancer in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.



Computational Systems Biology Of Cancer

Author: Emmanuel Barillot
Publisher: CRC Press
ISBN: 1439831440
Size: 24.66 MB
Format: PDF, Mobi
View: 3812
Download and Read
The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.

Computational Systems Biology

Author: Andres Kriete
Publisher: Elsevier
ISBN: 9780080459349
Size: 42.33 MB
Format: PDF, Kindle
View: 4230
Download and Read
Systems Biology is concerned with the quantitative study of complex biosystems at the molecular, cellular, tissue, and systems scales. Its focus is on the function of the system as a whole, rather than on individual parts. This exciting new arena applies mathematical modeling and engineering methods to the study of biological systems. This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches. The work covers new concepts, methods for information storage, mining and knowledge extraction, reverse engineering of gene and metabolic networks, as well as modelling and simulation of multi-cellular systems. Central themes include strategies for predicting biological properties and methods for elucidating structure-function relationships.

Computational Systems Biology

Author: Stefan M. Kallenberger
Publisher: Elsevier Inc. Chapters
ISBN: 012807020X
Size: 41.33 MB
Format: PDF, Docs
View: 6965
Download and Read
Apoptosis is a form of cellular suicide central to various aspects in biology including tissue homeostasis and embryonic development. It is typically dysregulated in cancer. Understanding the apoptotic signal transduction network is thus a central goal of cancer research. Quantitative modeling approaches provided valuable insights into determinants of cell fate decisions, and promise to become a valuable tool to optimize therapeutic strategies. In this chapter, we summarize modeling approaches used in systems biology of apoptosis. In addition, we give an overview of apoptosis-related research questions that can be addressed by modeling. Moreover, we review top-down and bottom-up modeling approaches applied to apoptosis, and particularly focus on ordinary differential equation (ODE) modeling. We describe bistability, temporal switching, crosstalk between death and survival, and discuss approaches to model cell-to-cell variability.

Cancer Systems Biology

Author: Edwin Wang
Publisher: CRC Press
ISBN: 9781439811863
Size: 57.69 MB
Format: PDF
View: 2942
Download and Read
The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation methods to glean meaningful information in systems-level biology. Applying this approach to the underlying molecular mechanisms of tumorigenesis, cancer researchers can uncover a series of new discoveries and biological insights. The First Cancer Systems Biology Book Designed for Computational and Experimental Biologists Unusual in its dualistic approach, Cancer Systems Biology discusses the recent progress in the understanding of cancer systems biology at a time when more and more researchers and pharmaceutical companies are looking into a systems biology approach to find drugs that can effectively be used to treat cancer patients. Includes Contributions from more than 30 International Experts Part I introduces basic concepts and theories of systems biology and their applications in cancer research, including case studies of current efforts in cancer systems biology. Part II discusses basic cancer biology and cutting-edge topics of cancer research for computational biologists. In contains an overview of genomics, cell signaling, and tumorigenesis, in addition to hot topics like molecular mechanisms of cancer metastasis and the molecular relationships between solid tumors, their microenvironments, and tumor blood vessels. Rounding out the book’s solid coverage, Part III explores a variety of computational tools and public data resources that are useful for studying cancer problems at a systems level. Cancer systems biology is still in its infancy as a field of study, but it is fast becoming indispensable in the battle to defeat cancer and develop successful new treatments. Cancer Systems Biology marks an important step toward reaching that goal.

A Practical Guide To Cancer Systems Biology

Author: Juan Hsueh-fen
Publisher: World Scientific
ISBN: 9813229160
Size: 21.28 MB
Format: PDF, ePub, Docs
View: 2070
Download and Read
Systems biology combines computational and experimental approaches to analyze complex biological systems and focuses on understanding functional activities from a systems-wide perspective. It provides an iterative process of experimental measurements, data analysis, and computational simulation to model biological behavior. This book provides explained protocols for high-throughput experiments and computational analysis procedures central to cancer systems biology research and education. Readers will learn how to generate and analyze high-throughput data, therapeutic target protein structure modeling and docking simulation for drug discovery. This is the first practical guide for students and scientists who wish to become systems biologists or utilize the approach for cancer research. Contents: Introduction to Cancer Systems Biology (Hsueh-Fen Juan and Hsuan-Cheng Huang)Transcriptome Analysis: Library Construction (Hsin-Yi Chang and Hsueh-Fen Juan)Quantitative Proteome: The Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) (Yi-Hsuan Wu and Hsueh-Fen Juan)Phosphoproteome: Sample Preparation (Chia-Wei Hu and Hsueh-Fen Juan)Transcriptomic Data Analysis: RNA-Seq Analysis Using Galaxy (Chia-Lang Hsu and Chantal Hoi Yin Cheung)Proteomic Data Analysis: Functional Enrichment (Hsin-Yi Chang and Hsueh-Fen Juan)Phosphorylation Data Analysis (Chia-Lang Hsu and Wei-Hsuan Wang)Pathway and Network Analysis (Chen-Tsung Huang and Hsueh-Fen Juan)Dynamic Modeling (Yu-Chao Wang)Protein Structure Modeling (Chia-Hsien Lee and Hsueh-Fen Juan)Docking Simulation (Chia-Hsien Lee and Hsueh-Fen Juan) Readership: Graduate students and researchers entering the cancer systems biology field. Keywords: Systems Biology;Transcriptomics;Proteomics;Network Biology;Dynamic Modeling;Protein Structure Modeling;Docking Simulation;BioinformaticsReview: Key Features: Written by two active researchers in the fieldCovers both experimental and computational areas in cancer systems biologyStep-by-step instructions help beginners who are interested in creating biological data and analyzing the data by themselvesReaders will gain the skills to generate and analyze omics data and discover potential therapeutic targets and drug candidates

Systemic Approaches In Bioinformatics And Computational Systems Biology Recent Advances

Author: Lecca, Paola
Publisher: IGI Global
ISBN: 1613504365
Size: 48.59 MB
Format: PDF, ePub
View: 1828
Download and Read
The convergence of biology and computer science was initially motivated by the need to organize and process a growing number of biological observations resulting from rapid advances in experimental techniques. Today, however, close collaboration between biologists, biochemists, medical researchers, and computer scientists has also generated remarkable benefits for the field of computer science. Systemic Approaches in Bioinformatics and Computational Systems Biology: Recent Advances presents new techniques that have resulted from the application of computer science methods to the organization and interpretation of biological data. The book covers three subject areas: bioinformatics, computational biology, and computational systems biology. It focuses on recent, systemic approaches in computer science and mathematics that have been used to model, simulate, and more generally, experiment with biological phenomena at any scale.

Computational Systems Biology

Author: Hang Chang
Publisher: Elsevier Inc. Chapters
ISBN: 0128070196
Size: 53.99 MB
Format: PDF, ePub
View: 3419
Download and Read
Integrated analysis of tissue histology with the genome-wide array and clinical data has the potential to generate hypotheses as well as be prognostic. However, due to the inherent technical and biological variations, automated analysis of whole mount tissue sections is impeded in very large datasets, such as The Cancer Genome Atlas (TCGA), where tissue sections are collected from different laboratories. We aim to characterize tumor architecture from hematoxylin and eosin (H&E) stained tissue sections, through the delineation of nuclear regions on a cell-by-cell basis. Such a representation can then be utilized to derive intrinsic morphometric subtypes across a large cohort for prediction and molecular association. Our approach has been validated on manually annotated samples, and then applied to a Glioblastoma Multiforme (GBM) cohort of 377 whole slide images from 146 patients. Further bioinformatics analysis, based on the multidimensional representation of the nuclear features and their organization, has identified (i) statistically significant morphometric sub types; (ii) whether each subtype can be predictive or not; and (iii) that the molecular correlates of predictive subtypes are consistent with the literature. The net result is the realization of the concept of pathway pathology through analysis of a large cohort of whole slide images.

Computational Systems Biology

Author: Paola Lecca
Publisher: Woodhead Publishing
ISBN: 0081001150
Size: 26.90 MB
Format: PDF, Mobi
View: 2616
Download and Read
Computational Systems Biology: Inference and Modelling provides an introduction to, and overview of, network analysis inference approaches which form the backbone of the model of the complex behavior of biological systems. This book addresses the challenge to integrate highly diverse quantitative approaches into a unified framework by highlighting the relationships existing among network analysis, inference, and modeling. The chapters are light in jargon and technical detail so as to make them accessible to the non-specialist reader. The book is addressed at the heterogeneous public of modelers, biologists, and computer scientists. Provides a unified presentation of network inference, analysis, and modeling Explores the connection between math and systems biology, providing a framework to learn to analyze, infer, simulate, and modulate the behavior of complex biological systems Includes chapters in modular format for learning the basics quickly and in the context of questions posed by systems biology Offers a direct style and flexible formalism all through the exposition of mathematical concepts and biological applications

Systems Biology In Cancer Research And Drug Discovery

Author: Asfar S Azmi
Publisher: Springer Science & Business Media
ISBN: 9400748183
Size: 66.81 MB
Format: PDF, Docs
View: 4022
Download and Read
Systems Biology in Cancer Research and Drug Discovery provides a unique collection of chapters, by world-class researchers, describing the use of integrated systems biology and network modeling in the cancer field where traditional tools have failed to deliver expected promise. This book touches four applications/aspects of systems biology (i) in understanding aberrant signaling in cancer (ii) in identifying biomarkers and prognostic markers especially focused on angiogenesis pathways (iii) in unwinding microRNAs complexity and (iv) in anticancer drug discovery and in clinical trial design. This book reviews the state-of-the-art knowledge and touches upon cutting edge newer and improved applications especially in the area of network modeling. It is aimed at an audience ranging from students, academics, basic researcher and clinicians in cancer research. This book is expected to benefit the field of translational cancer medicine by bridging the gap between basic researchers, computational biologists and clinicians who have one ultimate goal and that is to defeat cancer.

Transactions On Computational Systems Biology V

Author: Tony Hu
Publisher: Springer Science & Business Media
ISBN: 3540360484
Size: 68.11 MB
Format: PDF, Docs
View: 1602
Download and Read
The 5th Transactions on Computational Systems Biology collects carefully chosen and enhanced contributions initially presented at the 2005 IEEE International Conference on Granular Computing held in Beijing, China, in July 2005. The 9 papers in this special issue cover various aspects of computational methods, algorithms and techniques in bioinformatics such as gene expression analysis, biomedical literature mining and natural language processing, protein structure prediction, biological database management and biomedical information retrieval.