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Author: David (Wei) Dai
Publisher:
ISBN:
Category :
Languages : en
Pages : 233
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Book Description
Cancer is an umbrella term that encompasses a collection of related diseases. In all types of cancer, as cells become unregulated, they begin to divide uncontrollably and spread into surrounding tissues. From early to late stages of disease progression, there are many alterations that occur and many criteria that must be met for cancer to proliferate uncontrollable, resist cell death, avoid the immune system, and metastasize. Targeted therapy have been developed for a wide range of dysregulated cancer pathways using different modalities and mechanism of actions. However, due to the diversity of cancer, the same treatment that may be effective for one type of cancer may not be responsive on another. Furthermore, patients may carry resistance forms of the disease. To alleviate this, new strategies have been developed to target specific mutations of known dysregulated proteins and to use combination therapies that target multiple pathways. However, both methods require vast amount of knowledge on the biological interactions and mechanism of actions that takes place within the cell. To address this knowledge gap, we believe that the metabolism can be used as a tool to better understand the dysregulations of signaling and gene expression. There is a great opportunity to study the system as a whole to gain key insights for combination therapies that target different regulatory pathways, such as the metabolism and signaling. In this work, we leveraged our current understanding of signaling transduction, transcription factor, and metabolic networks to develop an integrated systems biology approach to quantitatively unravel the mechanisms that regulate cancer. Ultimately, we were able to establish a computational model that incorporated mechanistic understanding of multiple layers of cellular decision making. We believe this work will be useful in the development and evaluation of new combination therapy across all form of cancers.
Author: David (Wei) Dai
Publisher:
ISBN:
Category :
Languages : en
Pages : 233
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Book Description
Cancer is an umbrella term that encompasses a collection of related diseases. In all types of cancer, as cells become unregulated, they begin to divide uncontrollably and spread into surrounding tissues. From early to late stages of disease progression, there are many alterations that occur and many criteria that must be met for cancer to proliferate uncontrollable, resist cell death, avoid the immune system, and metastasize. Targeted therapy have been developed for a wide range of dysregulated cancer pathways using different modalities and mechanism of actions. However, due to the diversity of cancer, the same treatment that may be effective for one type of cancer may not be responsive on another. Furthermore, patients may carry resistance forms of the disease. To alleviate this, new strategies have been developed to target specific mutations of known dysregulated proteins and to use combination therapies that target multiple pathways. However, both methods require vast amount of knowledge on the biological interactions and mechanism of actions that takes place within the cell. To address this knowledge gap, we believe that the metabolism can be used as a tool to better understand the dysregulations of signaling and gene expression. There is a great opportunity to study the system as a whole to gain key insights for combination therapies that target different regulatory pathways, such as the metabolism and signaling. In this work, we leveraged our current understanding of signaling transduction, transcription factor, and metabolic networks to develop an integrated systems biology approach to quantitatively unravel the mechanisms that regulate cancer. Ultimately, we were able to establish a computational model that incorporated mechanistic understanding of multiple layers of cellular decision making. We believe this work will be useful in the development and evaluation of new combination therapy across all form of cancers.
Author: Inna Kuperstein
Publisher: CRC Press
ISBN: 1000682927
Category : Computers
Languages : en
Pages : 167
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Book Description
Praise for Computational Systems BiologyApproaches in Cancer Research: "Complex concepts are written clearly and with informative illustrations and useful links. The book is enjoyable to read yet provides sufficient depth to serve as a valuable resource for both students and faculty." — Trey Ideker, Professor of Medicine, UC Xan Diego, School of Medicine "This volume is attractive because it addresses important and timely topics for research and teaching on computational methods in cancer research. It covers a broad variety of approaches, exposes recent innovations in computational methods, and provides acces to source code and to dedicated interactive web sites." — Yves Moreau, Department of Electrical Engineering, SysBioSys Centre for Computational Systems Biology, University of Leuven With the availability of massive amounts of data in biology, the need for advanced computational tools and techniques is becoming increasingly important and key in understanding biology in disease and healthy states. This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. The book provides an important reference and teaching material in the field of computational biology in general and cancer systems biology in particular. The book presents a list of modern approaches in systems biology with application to cancer research and beyond. It is structured in a didactic form such that the idea of each approach can easily be grasped from the short text and self-explanatory figures. The coverage of topics is diverse: from pathway resources, through methods for data analysis and single data analysis to drug response predictors, classifiers and image analysis using machine learning and artificial intelligence approaches. Features Up to date using a wide range of approaches Applicationexample in each chapter Online resources with useful applications’
Author: Hsueh-fen Juan
Publisher: World Scientific
ISBN: 981446290X
Category : Medical
Languages : en
Pages : 339
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Book Description
This volume presents an overview of recent developments in systems biology and their applications in cancer-related research. The ongoing advances in our understanding of genomics and proteomics, coupled with the development of new and more robust tools, have led to an emphasis on analyzing biological systems at multiple levels. Thus, there is a need to integrate different types of data into a comprehensive “systems” view.Written by active researchers in the emerging areas, this book gives senior undergraduate students, graduate students and new researchers an idea of where the frontiers of systems biology are and an opportunity to learn high-throughput techniques in use. One of the particular emphases of the book is to elucidate the molecular mechanisms in cancer. The discovery of biomarkers and anti-cancer drugs using systems biology approach is also extensively discussed.
Author: Asfar S Azmi
Publisher: Springer Science & Business Media
ISBN: 9400748191
Category : Medical
Languages : en
Pages : 425
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Book Description
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.
Author: Alfredo Cesario
Publisher: Springer Science & Business Media
ISBN: 9400715676
Category : Medical
Languages : en
Pages : 496
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Book Description
This teaching monograph on systems approaches to cancer research and clinical applications provides a unique synthesis, by world-class scientists and doctors, of laboratory, computational, and clinical methods, thereby establishing the foundations for major advances not possible with current methods. Specifically, the book: 1) Sets the stage by describing the basis of systems biology and bioinformatics approaches, and the clinical background of cancer in a systems context; 2) Summarizes the laboratory, clinical, data systems analysis and bioinformatics tools, along with infrastructure and resources required; 3) Demonstrates the application of these tools to cancer research; 4) Extends these tools and methods to clinical diagnosis, drug development and treatment applications; and 5) Finishes by exploring longer term perspectives and providing conclusions. This book reviews the state-of-the-art, and goes beyond into new applications. It is written and highly referenced as a textbook and practical guide aimed at students, academics, doctors, clinicians, industrialists and managers in cancer research and therapeutic applications. Ideally, it will set the stage for integration of available knowledge to optimize communication between basic and clinical researchers involved in the ultimate fight against cancer, whatever the field of specific interest, whatever the area of activity within translational research.
Author: David H. Nguyen
Publisher: Springer
ISBN: 3319256017
Category : Medical
Languages : en
Pages : 68
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Book Description
This exciting SpringerBrief presents evidence for new ideas that will challenge several theories of how cancer biology is understood. Cancer biology has undergone several intellectual revolutions in the past 50 years. A mutation-centric view of cancer has given way to the tumor microenvironment view. Reductionistic studies of one gene at a time have given way to systems biology approaches that analyze the whole genome (omics) at the same time. However, this text combines the complex levels studying cancer at the molecular biology level, endocrinology level, and transcriptomics level. What researchers are now realizing is that there is a need to combine omics with physiology concepts in order to better understand cancer and this book will give insight to the merging of these two fields in order to define how cancer is studied in the future.
Author: Edwin Wang
Publisher: CRC Press
ISBN: 9781439811863
Category : Computers
Languages : en
Pages : 456
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Book Description
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 discov
Author: Tressa R. Hood
Publisher:
ISBN:
Category :
Languages : en
Pages : 45
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Book Description
Gene fusions have long been known to drive cancer. Initial discovery of gene fusions was opportunistic, and functional assessment was done individually and experimentally. There is no comprehensive systems biology approach to understanding the impact of gene fusions on the signaling networks within tumor cells. An integrative computational approach was taken to achieve a better understanding of gene fusions and their complex influence on pathways and interaction networks in the context of lung cancer. Using well-studied fusions and publicly available gene expression data, the effect of fusion events on the expression pattern of gene networks revealed unique differences in tumors with gene fusions, tumors without gene fusions, and normal samples. This approach identifies gene expression signatures associated with specific fusions, and provides a model for integrating experimental and pathway data to better understand the biology of a fusion genes and their roles in oncogenesis.
Author: Irina Kareva
Publisher: Academic Press
ISBN: 012813674X
Category : Medical
Languages : en
Pages : 120
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Book Description
Understanding Cancer from a Systems Biology Point of View: From Observation to Theory and Back starts with a basic question, why do we sometimes observe accelerated metastatic growth after resection of primary tumors? Next, it helps readers understand the systemic nature of cancer and how it affects treatment approaches and decisions. The book puts together aspects of cancer that many readers have most likely never combined, using unfamiliar, novel methods. It is a valuable resource for cancer researchers, cancer biologists, mathematicians and members of the biomedical field who are interested in applying systems biology methodologies for understanding and treating cancer. Explains the systemic nature of cancer and how it affects decisions on treatment Brings a variety of methods together, showing, in detail, the logical approach to finding answers to complex questions Discusses the theoretical underpinnings of cancer as a systemic disease, providing the reader with valuable information on applicable cases
Author: Manish I. Patel
Publisher: Springer Science & Business Media
ISBN: 3642156029
Category : Technology & Engineering
Languages : en
Pages : 173
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Book Description
Model integration – the process by which different modelling efforts can be brought together to simulate the target system – is a core technology in the field of Systems Biology. In the work presented here model integration was addressed directly taking cancer systems as an example. An in-depth literature review was carried out to survey the model forms and types currently being utilised. This was used to formalise the main challenges that model integration poses, namely that of paradigm (the formalism on which a model is based), focus (the real-world system the model represents) and scale. A two-tier model integration strategy, including a knowledge-driven approach to address model semantics, was developed to tackle these challenges. In the first step a novel description of models at the level of behaviour, rather than the precise mathematical or computational basis of the model, is developed by distilling a set of abstract classes and properties. These can accurately describe model behaviour and hence describe focus in a way that can be integrated with behavioural descriptions of other models. In the second step this behaviour is decomposed into an agent-based system by translating the models into local interaction rules. The book provides a detailed and highly integrated presentation of the method, encompassing both its novel theoretical and practical aspects, which will enable the reader to practically apply it to their model integration needs in academic research and professional settings. The text is self-supporting. It also includes an in-depth current bibliography to relevant research papers and literature. The review of the current state of the art in tumour modelling provides added value.
