Resultado de la búsqueda
88 búsqueda de la palabra clave 'biology'
Refinar búsqueda Generar rss de la búsqueda
Link de la búsqueda
Título : Combinatorial Computational Biology of RNA : Pseudoknots and Neutral Networks Tipo de documento: documento electrónico Autores: Reidys, Christian ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2011 Número de páginas: X, 258 p Il.: online resource ISBN/ISSN/DL: 978-0-387-76731-4 Idioma : Inglés (eng) Palabras clave: Mathematics Computer science Evolutionary biology Combinatorics Biomathematics Mathematical and Computational Biology Discrete in Science Clasificación: 51 Matemáticas Resumen: In this monograph, new combinatorial and computational approaches in the study of RNA structures are presented which enhance both mathematics and computational biology. It begins with an introductory chapter, which motivates and sets the background of this research. In the following chapter, all the concepts are systematically developed. The reader will find * integration of more than forty research papers covering topics like, RSK-algorithm, reflection principle, singularity analysis and random graph theory * systematic presentation of the theory of pseudo-knotted RNA structures including their generating function, uniform generation as well as central and discrete limit theorems * computational biology of pseudo-knotted RNA structures, including dynamic programming paradigms and a new folding algorithm * analysis of neutral networks of pseudoknotted RNA structures and their random graph theory, including neutral paths, giant components and connectivity All algorithms presented in the book are implemented in C and are freely available through a link on springer.com. A proofs section at the end contains the necessary technicalities. This book will serve graduate students and researchers in the fields of discrete mathematics, mathematical and computational biology. It is suitable as a textbook for a graduate course in mathematical and computational biology Nota de contenido: Introduction -- Secondary Structures, Pseudoknot RNA and Beyond -- Folding Sequences into Structures -- Evolution of RNA Sequences -- Methods -- References -- Index En línea: http://dx.doi.org/10.1007/978-0-387-76731-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33077 Combinatorial Computational Biology of RNA : Pseudoknots and Neutral Networks [documento electrónico] / Reidys, Christian ; SpringerLink (Online service) . - New York, NY : Springer New York, 2011 . - X, 258 p : online resource.
ISBN : 978-0-387-76731-4
Idioma : Inglés (eng)
Palabras clave: Mathematics Computer science Evolutionary biology Combinatorics Biomathematics Mathematical and Computational Biology Discrete in Science Clasificación: 51 Matemáticas Resumen: In this monograph, new combinatorial and computational approaches in the study of RNA structures are presented which enhance both mathematics and computational biology. It begins with an introductory chapter, which motivates and sets the background of this research. In the following chapter, all the concepts are systematically developed. The reader will find * integration of more than forty research papers covering topics like, RSK-algorithm, reflection principle, singularity analysis and random graph theory * systematic presentation of the theory of pseudo-knotted RNA structures including their generating function, uniform generation as well as central and discrete limit theorems * computational biology of pseudo-knotted RNA structures, including dynamic programming paradigms and a new folding algorithm * analysis of neutral networks of pseudoknotted RNA structures and their random graph theory, including neutral paths, giant components and connectivity All algorithms presented in the book are implemented in C and are freely available through a link on springer.com. A proofs section at the end contains the necessary technicalities. This book will serve graduate students and researchers in the fields of discrete mathematics, mathematical and computational biology. It is suitable as a textbook for a graduate course in mathematical and computational biology Nota de contenido: Introduction -- Secondary Structures, Pseudoknot RNA and Beyond -- Folding Sequences into Structures -- Evolution of RNA Sequences -- Methods -- References -- Index En línea: http://dx.doi.org/10.1007/978-0-387-76731-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33077 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar
Título : Mathematical Biology : An Introduction with Maple and Matlab Tipo de documento: documento electrónico Autores: Shonkwiler, Ronald W ; SpringerLink (Online service) ; Herod, James Editorial: New York, NY : Springer New York Fecha de publicación: 2009 Colección: Undergraduate Texts in Mathematics, ISSN 0172-6056 Número de páginas: XIII, 551 p Il.: online resource ISBN/ISSN/DL: 978-0-387-70984-0 Idioma : Inglés (eng) Palabras clave: Life sciences Application software Bioinformatics Computational biology Applied mathematics Engineering Probabilities Biomathematics Sciences Sciences, general Mathematical and Biology Computer Appl. in Probability Theory Stochastic Processes Applications of Mathematics Clasificación: 51 Matemáticas Resumen: This text presents mathematical biology as a field with a unity of its own, rather than only the intrusion of one science into another. It updates an earlier successful edition and greatly expands the concept of the "computer biology laboratory," giving students a general perspective of the field before proceeding to more specialized topics. The book focuses on problems of contemporary interest, such as cancer, genetics, and the rapidly growing field of genomics. It includes new chapters on parasites, cancer, and phylogenetics, along with an introduction to online resources for DNA, protein lookups, and popular pattern matching tools such as BLAST. In addition, the emerging field of algebraic statistics is introduced and its power illustrated in the context of phylogenetics. A unique feature of the book is the integration of a computer algebra system into the flow of ideas in a supporting but unobtrusive role. Syntax for both the Maple and Matlab systems is provided in a tandem format. The use of a computer algebra system gives the students the opportunity to examine "what if" scenarios, allowing them to investigate biological systems in a way never before possible. For students without access to Maple or Matlab, each topic presented is complete. Graphic visualizations are provided for all mathematical results. Mathematical Biology includes extensive exercises, problems and examples. A year of calculus with linear algebra is required to understand the material presented. The biology presented proceeds from the study of populations down to the molecular level; no previous coursework in biology is necessary. The book is appropriate for undergraduate and graduate students studying mathematics or biology and for scientists and researchers who wish to study the applications of mathematics and computers in the natural sciences Nota de contenido: Cells, Signals, Growth, and Populations -- Reproduction and the Drive for Survival -- Interactions Between Organisms and Their Environment -- Age-Dependent Population Structures -- Random Movements in Space and Time -- Neurophysiology -- The Biochemistry of Cells -- Biology, Mathematics, and a Mathematical Biology Laboratory -- Systems and Diseases -- The Biological Disposition of Drugs and Inorganic Toxins -- A Biomathematical Approach to HIV and AIDS -- Parasites and Their Diseases -- Cancer: A Disease of the DNA -- Some Mathematical Tools -- Genomics -- Genetics -- Genomics -- Phylogenetics En línea: http://dx.doi.org/10.1007/978-0-387-70984-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33845 Mathematical Biology : An Introduction with Maple and Matlab [documento electrónico] / Shonkwiler, Ronald W ; SpringerLink (Online service) ; Herod, James . - New York, NY : Springer New York, 2009 . - XIII, 551 p : online resource. - (Undergraduate Texts in Mathematics, ISSN 0172-6056) .
ISBN : 978-0-387-70984-0
Idioma : Inglés (eng)
Palabras clave: Life sciences Application software Bioinformatics Computational biology Applied mathematics Engineering Probabilities Biomathematics Sciences Sciences, general Mathematical and Biology Computer Appl. in Probability Theory Stochastic Processes Applications of Mathematics Clasificación: 51 Matemáticas Resumen: This text presents mathematical biology as a field with a unity of its own, rather than only the intrusion of one science into another. It updates an earlier successful edition and greatly expands the concept of the "computer biology laboratory," giving students a general perspective of the field before proceeding to more specialized topics. The book focuses on problems of contemporary interest, such as cancer, genetics, and the rapidly growing field of genomics. It includes new chapters on parasites, cancer, and phylogenetics, along with an introduction to online resources for DNA, protein lookups, and popular pattern matching tools such as BLAST. In addition, the emerging field of algebraic statistics is introduced and its power illustrated in the context of phylogenetics. A unique feature of the book is the integration of a computer algebra system into the flow of ideas in a supporting but unobtrusive role. Syntax for both the Maple and Matlab systems is provided in a tandem format. The use of a computer algebra system gives the students the opportunity to examine "what if" scenarios, allowing them to investigate biological systems in a way never before possible. For students without access to Maple or Matlab, each topic presented is complete. Graphic visualizations are provided for all mathematical results. Mathematical Biology includes extensive exercises, problems and examples. A year of calculus with linear algebra is required to understand the material presented. The biology presented proceeds from the study of populations down to the molecular level; no previous coursework in biology is necessary. The book is appropriate for undergraduate and graduate students studying mathematics or biology and for scientists and researchers who wish to study the applications of mathematics and computers in the natural sciences Nota de contenido: Cells, Signals, Growth, and Populations -- Reproduction and the Drive for Survival -- Interactions Between Organisms and Their Environment -- Age-Dependent Population Structures -- Random Movements in Space and Time -- Neurophysiology -- The Biochemistry of Cells -- Biology, Mathematics, and a Mathematical Biology Laboratory -- Systems and Diseases -- The Biological Disposition of Drugs and Inorganic Toxins -- A Biomathematical Approach to HIV and AIDS -- Parasites and Their Diseases -- Cancer: A Disease of the DNA -- Some Mathematical Tools -- Genomics -- Genetics -- Genomics -- Phylogenetics En línea: http://dx.doi.org/10.1007/978-0-387-70984-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33845 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar Modeling in Computational Biology and Biomedicine / SpringerLink (Online service) ; Cazals, Frédéric ; Kornprobst, Pierre (2013)
Título : Modeling in Computational Biology and Biomedicine : A Multidisciplinary Endeavor Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Cazals, Frédéric ; Kornprobst, Pierre Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2013 Otro editor: Imprint: Springer Número de páginas: XXVI, 318 p Il.: online resource ISBN/ISSN/DL: 978-3-642-31208-3 Idioma : Inglés (eng) Palabras clave: Mathematics Bioinformatics Applied mathematics Engineering Biomathematics Mathematical and Computational Biology Applications of Biology/Bioinformatics Clasificación: 51 Matemáticas Resumen: Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience Nota de contenido: Foreword by Olivier Faugeras -- Foreword by Joël Janin -- Preface -- Part I Bioinformatics -- 1.Modeling Macro-molecular Complexes: a Journey Across Scales. F.Cazals, T.Dreyfus, and C.H. Robert -- 1.1.Introduction -- 1.2.Modeling Atomic Resolution -- 1.3.Modeling Large Assemblies -- 1.4.Outlook -- 1.5.Online Resources -- References -- 2.Modeling and Analysis of Gene Regulatory Networks. G.Bernot, J-P.Comet, A.Richard, M.Chaves, J-L.Gouzé, and F.Dayan -- 2.1.Introduction -- 2.2.Continuous and Hybrid Models of Genetic Regulatory Networks -- 2.3.Discrete Models of GRN -- 2.4.Outlook -- 2.5.Online Resources -- 2.6.Acknowledgments -- References -- Part II Biomedical Signal and Image Analysis -- 3.Noninvasive Cardiac Signal Analysis Using Data Decomposition Techniques. V.Zarzoso, O.Meste, P.Comon, D.G.Latcu, and N.Saoudi -- 3.1.Preliminaries and Motivation -- 3.2.T-Wave Alternans Detection via Principal Component Analysis -- 3.3.Atrial Activity Extraction via Independent Component Analysis -- 3.4.Conclusion and Outlook -- 3.5.Online Resources -- References -- 4.Deconvolution and Denoising for Confocal Microscopy. P.Pankajakshan, G.Engler, L.Blanc-Féraud, and J.Zerubia -- 4.1.Introduction -- 4.2.Development of the Auxiliary Computational Lens -- 4.3.Outlook -- 4.4.Selected Online Resources -- References -- 5.Statistical Shape Analysis of Surfaces in Medical Images Applied to the Tetralogy of Fallot Heart. K.McLeod, T.Mansi, M.Sermesant, G.Pongiglione, and X.Pennec -- 5.1.Introduction -- 5.2.Statistical Shape Analysis -- 5.3.Shape Analysis of ToF Data -- 5.4.Conclusion -- 5.5.Online Resources -- References -- 6.From Diffusion MRI to Brain Connectomics. A.Ghosh and R.Deriche -- 6.1.Introduction -- 6.2.A Brief History of NMR and MRI -- 6.3.Nuclear Magnetic Resonance and Diffusion -- 6.4.From Diffusion MRI to Tissue Microstructure -- 6.5.Computational Framework for Processing Diffusion MR Images -- 6.6.Tractography: Inferring the Connectivity -- 6.7.Clinical Applications 6.8.Conclusion -- 6.9.Online Resources -- References -- Part III Modeling in neuroscience -- 7.Single-Trial Analysis of Bioelectromagnetic Signals: The Quest for Hidden Information. M.Clerc, T.Papadopoulo, and C.Bénar -- 7.1.Introduction -- 7.2.Data-driven Approaches: Non-linear Dimensionality Reduction -- 7.3.Model-Driven Approaches: Matching Pursuit and its Extensions -- 7.4.Success Stories -- 7.5.Conclusion -- 7.6.Selected Online Resources -- References -- 8 Spike Train Statistics from Empirical Facts to Theory: The Case of the Retina. B.Cessac and A.Palacios -- 8.1.Introduction -- 8.2.Unraveling the Neural Code in the Retina via Spike Train Statistics Analysis -- 8.3.Spike Train Statistics from a Theoretical Perspective -- 8.4.Using Gibbs Distributions to Analysing Spike Trains Statistics -- 8.5.Conclusion -- 8.6.Outlook -- 8.7.Online Resources -- References -- Biology, Medicine and Biophysics -- Mathematics and Computer Science -- Index En línea: http://dx.doi.org/10.1007/978-3-642-31208-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32513 Modeling in Computational Biology and Biomedicine : A Multidisciplinary Endeavor [documento electrónico] / SpringerLink (Online service) ; Cazals, Frédéric ; Kornprobst, Pierre . - Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013 . - XXVI, 318 p : online resource.
ISBN : 978-3-642-31208-3
Idioma : Inglés (eng)
Palabras clave: Mathematics Bioinformatics Applied mathematics Engineering Biomathematics Mathematical and Computational Biology Applications of Biology/Bioinformatics Clasificación: 51 Matemáticas Resumen: Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience Nota de contenido: Foreword by Olivier Faugeras -- Foreword by Joël Janin -- Preface -- Part I Bioinformatics -- 1.Modeling Macro-molecular Complexes: a Journey Across Scales. F.Cazals, T.Dreyfus, and C.H. Robert -- 1.1.Introduction -- 1.2.Modeling Atomic Resolution -- 1.3.Modeling Large Assemblies -- 1.4.Outlook -- 1.5.Online Resources -- References -- 2.Modeling and Analysis of Gene Regulatory Networks. G.Bernot, J-P.Comet, A.Richard, M.Chaves, J-L.Gouzé, and F.Dayan -- 2.1.Introduction -- 2.2.Continuous and Hybrid Models of Genetic Regulatory Networks -- 2.3.Discrete Models of GRN -- 2.4.Outlook -- 2.5.Online Resources -- 2.6.Acknowledgments -- References -- Part II Biomedical Signal and Image Analysis -- 3.Noninvasive Cardiac Signal Analysis Using Data Decomposition Techniques. V.Zarzoso, O.Meste, P.Comon, D.G.Latcu, and N.Saoudi -- 3.1.Preliminaries and Motivation -- 3.2.T-Wave Alternans Detection via Principal Component Analysis -- 3.3.Atrial Activity Extraction via Independent Component Analysis -- 3.4.Conclusion and Outlook -- 3.5.Online Resources -- References -- 4.Deconvolution and Denoising for Confocal Microscopy. P.Pankajakshan, G.Engler, L.Blanc-Féraud, and J.Zerubia -- 4.1.Introduction -- 4.2.Development of the Auxiliary Computational Lens -- 4.3.Outlook -- 4.4.Selected Online Resources -- References -- 5.Statistical Shape Analysis of Surfaces in Medical Images Applied to the Tetralogy of Fallot Heart. K.McLeod, T.Mansi, M.Sermesant, G.Pongiglione, and X.Pennec -- 5.1.Introduction -- 5.2.Statistical Shape Analysis -- 5.3.Shape Analysis of ToF Data -- 5.4.Conclusion -- 5.5.Online Resources -- References -- 6.From Diffusion MRI to Brain Connectomics. A.Ghosh and R.Deriche -- 6.1.Introduction -- 6.2.A Brief History of NMR and MRI -- 6.3.Nuclear Magnetic Resonance and Diffusion -- 6.4.From Diffusion MRI to Tissue Microstructure -- 6.5.Computational Framework for Processing Diffusion MR Images -- 6.6.Tractography: Inferring the Connectivity -- 6.7.Clinical Applications 6.8.Conclusion -- 6.9.Online Resources -- References -- Part III Modeling in neuroscience -- 7.Single-Trial Analysis of Bioelectromagnetic Signals: The Quest for Hidden Information. M.Clerc, T.Papadopoulo, and C.Bénar -- 7.1.Introduction -- 7.2.Data-driven Approaches: Non-linear Dimensionality Reduction -- 7.3.Model-Driven Approaches: Matching Pursuit and its Extensions -- 7.4.Success Stories -- 7.5.Conclusion -- 7.6.Selected Online Resources -- References -- 8 Spike Train Statistics from Empirical Facts to Theory: The Case of the Retina. B.Cessac and A.Palacios -- 8.1.Introduction -- 8.2.Unraveling the Neural Code in the Retina via Spike Train Statistics Analysis -- 8.3.Spike Train Statistics from a Theoretical Perspective -- 8.4.Using Gibbs Distributions to Analysing Spike Trains Statistics -- 8.5.Conclusion -- 8.6.Outlook -- 8.7.Online Resources -- References -- Biology, Medicine and Biophysics -- Mathematics and Computer Science -- Index En línea: http://dx.doi.org/10.1007/978-3-642-31208-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32513 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar
Título : Stochastic Approaches for Systems Biology Tipo de documento: documento electrónico Autores: Ullah, Mukhtar ; SpringerLink (Online service) ; Wolkenhauer, Olaf Editorial: New York, NY : Springer New York Fecha de publicación: 2011 Número de páginas: XXXII, 290 p Il.: online resource ISBN/ISSN/DL: 978-1-4614-0478-1 Idioma : Inglés (eng) Palabras clave: Mathematics Bioinformatics Systems biology Probabilities Biomathematics Probability Theory and Stochastic Processes Biology Mathematical Computational Clasificación: 51 Matemáticas Resumen: This textbook focuses on stochastic modelling and its applications in systems biology. In addition to a review of probability theory, the authors introduce key concepts, including those of stochastic process, Markov property, and transition probability, side by side with notions of biochemical reaction networks. This leads to an intuitive presentation guided by a series of biological examples that are revisited throughout the text. The text shows how the notion of propensity, the chemical master equation and the stochastic simulation algorithm arise as consequences of the Markov property. The nontrivial relationships between various stochastic approaches are derived and illustrated. The text contains many illustrations, examples and exercises to communicate methods and analyses. Matlab code to simulate cellular systems is also provided where appropriate and the reader is encouraged to experiment with the examples and case studies provided. Senior undergraduate and graduate students in applied mathematics, the engineering and physical sciences as well as researchers working in the areas of systems biology, theoretical and computational biology will find this text useful Nota de contenido: Preface.- Acknowledgements -- Acronyms, notation -- Matlab functions, revisited examples -- Introduction -- Biochemical reaction networks -- Randomness -- Probability and random variables -- Stochastic modeling of biochemical networks -- The 2MA approach -- The 2MA cell cycle model -- Hybrid Markov processes -- Wet-lab experiments and noise -- Glossary En línea: http://dx.doi.org/10.1007/978-1-4614-0478-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33225 Stochastic Approaches for Systems Biology [documento electrónico] / Ullah, Mukhtar ; SpringerLink (Online service) ; Wolkenhauer, Olaf . - New York, NY : Springer New York, 2011 . - XXXII, 290 p : online resource.
ISBN : 978-1-4614-0478-1
Idioma : Inglés (eng)
Palabras clave: Mathematics Bioinformatics Systems biology Probabilities Biomathematics Probability Theory and Stochastic Processes Biology Mathematical Computational Clasificación: 51 Matemáticas Resumen: This textbook focuses on stochastic modelling and its applications in systems biology. In addition to a review of probability theory, the authors introduce key concepts, including those of stochastic process, Markov property, and transition probability, side by side with notions of biochemical reaction networks. This leads to an intuitive presentation guided by a series of biological examples that are revisited throughout the text. The text shows how the notion of propensity, the chemical master equation and the stochastic simulation algorithm arise as consequences of the Markov property. The nontrivial relationships between various stochastic approaches are derived and illustrated. The text contains many illustrations, examples and exercises to communicate methods and analyses. Matlab code to simulate cellular systems is also provided where appropriate and the reader is encouraged to experiment with the examples and case studies provided. Senior undergraduate and graduate students in applied mathematics, the engineering and physical sciences as well as researchers working in the areas of systems biology, theoretical and computational biology will find this text useful Nota de contenido: Preface.- Acknowledgements -- Acronyms, notation -- Matlab functions, revisited examples -- Introduction -- Biochemical reaction networks -- Randomness -- Probability and random variables -- Stochastic modeling of biochemical networks -- The 2MA approach -- The 2MA cell cycle model -- Hybrid Markov processes -- Wet-lab experiments and noise -- Glossary En línea: http://dx.doi.org/10.1007/978-1-4614-0478-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33225 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar
Título : Systems Biology : International Research and Development Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Marvin Cassman ; Adam Arkin ; Frank Doyle ; KATAGIRI, FUMIAKI ; LAUFFENBURGER, DOUGLAS ; STOKES, CYNTHIA Editorial: Dordrecht : Springer Netherlands Fecha de publicación: 2007 Número de páginas: XVIII, 262 p Il.: online resource ISBN/ISSN/DL: 978-1-4020-5468-6 Idioma : Inglés (eng) Palabras clave: Mathematics Bioinformatics Developmental biology Biomathematics Mathematical and Computational Biology Clasificación: 51 Matemáticas Resumen: Systems biology is defined for the purpose of this study as the understanding of biological network behaviors, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment. This involves a variety of approaches, such as the identification and validation of networks, the creation of appropriate datasets, the development of tools for data acquisition and software development, and the use of modeling and simulation software in close linkage with experiment. All of these are discussed in this volume. Of course, the definition becomes ambiguous at the margins, but at the core is the focus on networks, which makes it clear that the goal is to understand the operation of the systems, rather than the component parts. It was concluded that the U.S. is currently ahead of the rest of the world in systems biology, largely because of earlier investment by funding organizations and research institutions. This is reflected in a large number of active research groups, and educational programs, and a diverse and growing funding base. However, there is evidence of rapid development outside the U.S., much of it begun in the last two to three years. Overall, however, the picture is of an active field in the early stages of explosive growth. This volume is aimed at academic researchers, government research agency representatives and graduate students Nota de contenido: Executive Summary and Introduction -- Data and Databases -- Network Inference -- Modeling and Network Organization -- Systems Biology in Plant Research -- Education, National Programs, and Infrastructure in Systems Biology En línea: http://dx.doi.org/10.1007/978-1-4020-5468-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34578 Systems Biology : International Research and Development [documento electrónico] / SpringerLink (Online service) ; Marvin Cassman ; Adam Arkin ; Frank Doyle ; KATAGIRI, FUMIAKI ; LAUFFENBURGER, DOUGLAS ; STOKES, CYNTHIA . - Dordrecht : Springer Netherlands, 2007 . - XVIII, 262 p : online resource.
ISBN : 978-1-4020-5468-6
Idioma : Inglés (eng)
Palabras clave: Mathematics Bioinformatics Developmental biology Biomathematics Mathematical and Computational Biology Clasificación: 51 Matemáticas Resumen: Systems biology is defined for the purpose of this study as the understanding of biological network behaviors, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment. This involves a variety of approaches, such as the identification and validation of networks, the creation of appropriate datasets, the development of tools for data acquisition and software development, and the use of modeling and simulation software in close linkage with experiment. All of these are discussed in this volume. Of course, the definition becomes ambiguous at the margins, but at the core is the focus on networks, which makes it clear that the goal is to understand the operation of the systems, rather than the component parts. It was concluded that the U.S. is currently ahead of the rest of the world in systems biology, largely because of earlier investment by funding organizations and research institutions. This is reflected in a large number of active research groups, and educational programs, and a diverse and growing funding base. However, there is evidence of rapid development outside the U.S., much of it begun in the last two to three years. Overall, however, the picture is of an active field in the early stages of explosive growth. This volume is aimed at academic researchers, government research agency representatives and graduate students Nota de contenido: Executive Summary and Introduction -- Data and Databases -- Network Inference -- Modeling and Network Organization -- Systems Biology in Plant Research -- Education, National Programs, and Infrastructure in Systems Biology En línea: http://dx.doi.org/10.1007/978-1-4020-5468-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34578 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar Permalink
PermalinkPermalinkPermalink
Permalink
