Systems Biology: Properties of Reconstructed Networks

Book Description

Genome sequences are now available that enable us to determine the biological components that make up a cell or an organism. The new discipline of systems biology examines how these components interact and form networks, and how the networks generate whole cell functions corresponding to observable phenotypes. This textbook describes how to model networks, determine their properties, and relate these to phenotypic functions. Some knowledge of linear algebra and biochemistry is required, since the book reflects the irreversible trend of increasing mathematical content in biology education.

Customer Reviews:

A great review of network reconstructions.......2006-06-03

While this may not be an all encompassing review of what systems biology is, it provides an insightful view on network reconstruction. I've found this book very helpful and well written (being a first edition, it does have a few typos, but this is normal). It has a very logical flow, but it is written on the level of a professional or graduate student interested in entering the field of systems biology.

The Regulatory Genome: Gene Regulatory Networks In Development And Evolution

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A real theory of biology and evolution

The Regulatory Genome: Gene Regulatory Networks In Development And Evolution
Eric H. Davidson
Manufacturer: Academic Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0120885638

Book Description

Gene regulatory networks are the most complex, extensive control systems found in nature. The interaction between biology and evolution has been the subject of great interest in recent years. The author, Eric Davidson, has been instrumental in elucidating this relationship. He is a world renowned scientist and a major contributor to the field of developmental biology.

The Regulatory Genome beautifully explains the control of animal development in terms of structure/function relations of inherited regulatory DNA sequence, and the emergent properties of the gene regulatory networks composed of these sequences. New insights into the mechanisms of body plan evolution are derived from considerations of the consequences of change in developmental gene regulatory networks. Examples of crucial evidence underscore each major concept. The clear writing style explains regulatory causality without requiring a sophisticated background in descriptive developmental biology. This unique text supersedes anything currently available in the market.

* The only book in the market that is solely devoted to the genomic regulatory code for animal development
* Written at a conceptual level, including many novel synthetic concepts that ultimately simplify understanding
* Presents a comprehensive treatment of molecular control elements that determine the function of genes
* Provides a comparative treatment of development, based on principles rather than description of developmental processes
* Considers the evolutionary processes in terms of the structural properties of gene regulatory networks
* Includes 42 full-color descriptive figures and diagrams

Customer Reviews:

A real theory of biology and evolution.......2007-03-23

This book will be a revelation to any biologist who has not been reading the literature on development and embryology attentively. Davidson eloquently articulates a real theory of the mechanism by which the genome computes the embryologic development of bilaterian animals. The argument is carefully developed from simple principles to more complex implications. The figures are a major part of the book's exposition, and repay very careful reading of the legends along with the associated text. The references are as current as 2006, so the book is quite cutting edge in its outlook. I heartily recommend it to any biologically sophisticated reader. It does presume elementary knowledge about biochemistry and molecular biology at about the freshman/sophomore college level. Enjoy!

Average customer rating:

Thinking as an internalized movement!
Readable and wide-ranging, but all from just one theoretical perspective
Amazing Neuroscience synthesis!
read it.
Very worthwhile

I of the Vortex: From Neurons to Self
Rodolfo R. Llinas
Manufacturer: The MIT Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0262122332

Amazon.com

What is it about neuroscience that graces its practitioners with humility? Rodolfo Llinas of the NYU School of Medicine continues this tradition of quietly tackling the deepest issues in I of the Vortex. This exposition on the evolution and development of consciousness is accessible and intriguing enough to interest readers more philosophically than scientifically oriented. Grounded in research, the book posits our awareness as an artifact of the cortico-thalamic binding of perceptions and movements in synchrony; Llinas uses this theory as a launching pad for more far-reaching considerations of selfhood all the more relevant for their correlation with the facts.

Charmingly illustrated with artistic and scientific images cleverly supporting the arguments, the book is a quick if challenging read, and it explains all the scientific basics for those approaching from the humanities. Synthesizing evolution, philosophy, and neuroscience is becoming an increasingly popular endeavor for introspective eggheads, and we should be grateful: the question of consciousness affects us all and touches on every other field, from theology to particle physics. I of the Vortex is a welcome contribution to the theory of mind and essential reading for the introspective. --Rob Lightner

Book Description

In I of the Vortex, Rodolfo Llinas, a founding father of modern brain science, presents an original view of the evolution and nature of mind. According to Llinas, the "mindness state" evolved to allow predictive interactions between mobile creatures and their environment. He illustrates the early evolution of mind through a primitive animal called the "sea squirt." The mobile larval form has a brainlike ganglion that receives sensory information about the surrounding environment. As an adult, the sea squirt attaches itself to a stationary object and then digests most of its own brain. This suggests that the nervous system evolved to allow active movement in animals. To move through the environment safely, a creature must anticipate the outcome of each movement on the basis of incoming sensory data. Thus the capacity to predict is most likely the ultimate brain function. One could even say that Self is the centralization of prediction.

At the heart of Llinas's theory is the concept of oscillation. Many neurons possess electrical activity, manifested as oscillating variations in the minute voltages across the cell membrane. On the crests of these oscillations occur larger electrical events that are the basis for neuron-to-neuron communication. Like cicadas chirping in unison, a group of neurons oscillating in phase can resonate with a distant group of neurons. This simultaneity of neuronal activity is the neurobiological root of cognition. Although the internal state that we call the mind is guided by the senses, it is also generated by the oscillations within the brain. Thus, in a certain sense, one could say that reality is not all "out there," but is a kind of virtual reality.

Customer Reviews:

Thinking as an internalized movement!.......2007-06-24

Jorge Borges wrote, "I am not sure that I exist, actually. I am all the writers that I have read, all the people that I have met, all the women that I have loved; all the cities that I have visited, all my ancestors... Perhaps I would have liked to be my father, who wrote but has the decency of not publishing".
In the book "I of the vortex" Rodolfo Llinas gives another perspective on who am "I" and where "I" comes from, looking into the deep and dark recesses of the brain as a neuroscientist and physician, leaving God out from the game, unlike his maestro John Eccles, a dedicated theist, who wrote that "there is a Divine Providence operating over and above the materialistic happenings of biological evolution".
The ultimate thesis Llinas nominates is: "thinking is an internalized movement". He makes his point very clearly, based on his extensive knowledge and experience both as a scientist and writer. Perhaps thinking is an internalized movement? Perhaps not! The book "I of the vortex" is the ultimate read for those who ask Questions. An excellent book.

Readable and wide-ranging, but all from just one theoretical perspective.......2006-10-23

What is the "self" in neural terms? Few would be bold enough to claim an answer to that question. Yet in "I of the Vortex: From Neurons to Self," Rodolfo Llinas sketches a very compelling picture of how the self, consciousness, and intelligence may arise in the brain.

Essentially, Llinas's argument goes as follows. First, brains are really only found in animals that move (so, obviously, plants do not have brains). In fact, at least one animal - the sea squirt - actually devours its own brain once it no longer needs to move. Although simple movements might be caused by oscillatory pattern generators in the spinal cord, the brain is necessary for more complex, sensory-guided movement. Why should this be so?

The answer Llinas provides is prediction, or in other words, a sensorimotor internal model of the world based on "dt lookahead" functions, interfacing the motor and sensory systems. Synchronized oscillations from the cerebellum (Llinas's area of expertise) carry out the motor-side of this computation, giving rise to the characteristic 8-12 Hz periodicity of the neural signals that command voluntary movements. At a higher frequency (40 Hz), other neuronal oscillations throughout the thalamocortical system serve to bind sensory representations together. And the subjective, cognitive correlate of the intersection of these oscillations is no less than the self: "this temporally coherent event that binds, in the time domain, the fractured components of external and internal reality into a single construct is what we call the 'self.'"

But wait, doesn't that mean that all animals have a sense of "self"- even the lowly sea squirt (at least before it eats its brain)? It would seem so. But that's not the end of Llinas's more controversial claims. Llinas also suggests that neural networks explain "very little concerning the actual functioning of the nervous system itself," advocating instead the idea that most of our cognitive abilities are genetically prewired at birth. Along these lines, Llinas endorses Chomsky's idea that genes may to a large extent determine language, and furthermore that language exists in many species besides homo sapiens.

It is here that "I of the Vortex" starts to seem more like a manifesto than a careful scientific analysis. For example, after introducing the basics of neurophysiology and comparative neurology in the first half of the book, Llinas skips the cognitive level of analysis almost altogether and starts extrapolating directly to issues of consciousness, awareness, and selfhood. This bias against direct investigations of cognition (something arguably very important for understanding consciousness) is nowhere more apparent than when he refers to cognitive neuroscience as "neophrenology." But without this important middle-level of analysis, Llinas is mostly shooting from the hip in the second half of the book - and aiming for concepts that are simply too far removed from Llinas's expertise in cellular neurophysiology.

On the whole, Llinas has done an admirable job of outlining one particular view of how neuronal dynamics may give rise to consciousness in an embodied cognition framework. In this sense, "I of the Vortex" makes an excellent companion to other high-level introductions to cognitive neuroscience.

Amazing Neuroscience synthesis!.......2005-08-14

The book presents an amazing Neuroscience synthesis that covers all the aspects: from ions to synergistic systems. It gives a thought-provoking explanation of the origin of the brain through evolution. It also explains the concepts of 'qualias' and 'fixed action patterns' in such an integrative manner and concludes that everything was perfectly made to synergistically create our predictive brains.

read it........2004-09-07

If you are going to read one book about neuroscience, consciousness, or the meaning of life, this should be it. Dr. Llinas has made some unusually innovative and profound assertions about how the self ("soul") might be generated from the mechanical workings of the brain. While the answer to the hard problem of consciousness remains elusive, I can honestly say after having read many books on the subject, that this is as close as it gets.

Very worthwhile.......2002-05-20

The author presents quite a plausible theory of mind, based on his work as a neuroscientist. I suspect Llinas is very much on the right track to illuminating the physical basis of consciousness.

Building chapter-by-chapter simultaneously on the apparent evolutionary development from the simplest neuronal system to the centralized brain, and on the results of brain scans and other experiments, Llinas brings us calmly and reasonably to the resultant human mind of today.

For Llinas, consciousness is the synchronized 40Hz firing of regions of the cortex over time. That is, consciousness is not just a given pattern of firing in 3-space, but is a 4-space relation. That additional dimension of time multiplies enormously the potential number of brain patterns that could occur in an individual. But it also makes the topic that much harder to study.

The writing feels like it has been written by someone who knows alot: there are many points where conceptual connections are not made entirely explicit (because it probably seemed so self-evident to Llinas) and the reader must fill in those gaps. Also, some of his non-neurologic language is quite technical: the description of the "self" as a calculated eigenvector, or the "vortex" which is essentially an attractor (as known in mathematics), that can make Llinas sound like a cold, hard-nosed scientist.

However, Llinas is refreshingly 'human'. For him, it is quite reasonable to assume (as a common consequence of evolution and similarity of brain structure) that many other species have forms of consciousness. Indeed, he devotes an entire chapter to qualia, and contends that qualia exist as essential brain feature, not only for humans but for cats and dogs and most other animals with brains of the same evolutionary genre (and that even in the case of invertebrate (octopus) brains he argues that the burden of proof is on those who would deny qualia).

Book Description

The Handbook of Computational Statistics - Concepts and Methods is divided into 4 parts. It begins with an overview of the field of Computational Statistics, how it emerged as a seperate discipline, how it developed along the development of hard- and software, including a discussion of current active research.

The second part presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and it discusses some of the basic methodologies for transformation, data base handling and graphics treatment.

The third part focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data.

Finally a set of selected applications like Bioinformatics, Medical Imaging, Finance and Network Intrusion Detection highlight the usefulness of computational statistics.

The Handbook of Brain Theory and Neural Networks (Bradford Book)

Average customer rating:

Excellent reference work on brain theory
Misleading title, a useful book otherwise
Basic science for consciousness
Excellent compilation
Neural Network Bible

The Handbook of Brain Theory and Neural Networks (Bradford Book)

Manufacturer: The MIT Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0262511029

Book Description

In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to great questions: How does the brain work? How can we build intelligent machines?

While many books discuss limited aspects of one subfield or another of brain theory and neural networks, the Handbook covers the entire sweep of topics--from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks.

Expository material makes the book accessible to readers with varied backgrounds while still offering a clear view of the recent, specialized research on specific topics.

Customer Reviews:

Excellent reference work on brain theory.......2007-01-05

The articles in this work are written by a who's who list of authors from the cognitive and computational neuroscience community. Each article is useful for getting an initial bearing on a topic from this dynamic field. The references for each article serve as useful "jumping off points" for further learning. It should be noted that this text is not a typical college textbook -- it is a reference work. As such, a beginner to the field should consider one of the other introductory textbooks (perhaps "The Cognitive Neurosciences").

Misleading title, a useful book otherwise.......2005-01-04

Look through this book to convince yourself that an exact brain theory does not exist. The arrangement of the articles by the first letter of their title tells it all (consider classifying animals by the first letter of their name). The editors wrongly assume that mathematical methods equal theory; actually, theory is a small conceptual tent under which a large number of experimentally established facts can be gathered. In most cases, mathematics is a very useful tool in pitching this tent, but it has little to do with the tent itself.

An exact theory of the brain may be possible and we are in dire need of it. Unfortunately, nobody has come up with it yet. This book is an encyclopedia of various mathematical methods that have been used to solve various neuroscience problems. These methods and solutions are as diverse as the problems themselves. Don't look for common themes in this book. If you are looking for a unified brain theory, you'll be much better off reading standard neuroscience textbooks. I do hope one day we'll be able to cast these vague ideas into something precise and, most likely, mathematical. Sadly, not today. I own a copy of this book and use it to remind me why and how we have failed so far.

It should be kept in mind that it is not at all clear that "neural" networks can emulate consciousness. They may or they may not. Firstly, a single neuron resembles a computer processor in its complexity and is a constantly evolving entity. Secondly, only 10% of brain cells are neurons and the remaining 90% (glial cells) now too appear to be involved in information processing. At a more fundamental level, consciousness may be less algorithmic and computational than we expect. Finally, the brain and the reality "outside the brain" are a two-way street. As the great neuroscientist Cajal put it, "As long as our brain remains an arcanum, the Universe, a reflection of its structure, will also be a mystery". If we assume the brain analyzes something, we need to define a reality independent of this analysis -- a hardly possible task if standard "input-output" approaches are used.

If the title of this book were "Current Mathematical Methods in Neurosciences", I'd have no problem giving it five stars.

November 2005: The chapters in the second edition are still arranged alphabetically. I refuse to believe neuro-mathematicians cannot think more coherently.

One final note for those looking for serious conceptual advances on the theoretical front: do no miss "Spikes: Exploring the Neural Code" (edited by F. Rieke) and "Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics" by Paul Glimcher.

Basic science for consciousness.......2001-10-10

Research is tedious, but if you want to know the nitty-gritty of mind-brain theory and neural networking, this book is an invaluable resource for basic, relevant, and accessible papers on the subjects. Encompassing seminal works from an unusually broad range of disciplines, here is an outstanding reference for those concerned with the mechanisms of intelligence.

Excellent compilation.......2001-06-03

This complilation of articles by leading experts in the field gives an excellent overview of studies in cognitive theory and the theory and applications of neural networks. The first two parts of the book give an overview and background of the properties of neurons and gives guidance to the reader on what sequence the articles are to be read. I did not read all of the articles, but only those that piqued my interest. I found the following articles particularly well-written and informative: 1. "Applications of Neural Networks": Outlines the diverse applications of neural networks to signal processing, time series, imaging, etc. 2. "Astronomy": Neural network applications in astronomy, such as adaptive optics and telescope guidance. 3. "Chains of Coupled Oscillators": Their connection with the lamprey central pattern generator. 4. "Chaos in Axons": An excellent review of chaos experimentally in squid axons and numerically with nerve equations. 5. "Collective Behavior of Coupled Oscillators": A study of the phase and complex Ginzburg-Landau model. 6. "Computer Modeling Methods for Neurons": Good overview of numerical modeling of neurons. 7. "Computing with Attractors": Overview of omputing and feedback networks with attractors and a fascinating discussion of the possible existence of attractors in the brain. 8. "Constrained Optimization and the Elastic Net": Useful discussion of application of neural networks to optimization problems. 9. "Data Clustering and Learning": Good discussion of parameter estimation of mixture models by parametric statistics and vector quantization of a data set by combinatorial optimization. 10. "Diffusion Models of Neuron Activity": Discusses 1-dimensional stochastic diffusion models for the neuron membrane potential. 11. "Disease: Neural Network Models": Interesting overview of neural net computational models of various mental illnesses. 12. "Dynamics and Bifurcation of Neural Networks": Discussion of neural nets and their behavior as dynamical systems. 13. "Emotion and Computational Neuroscience": Fascinating discussion of computational models of emotion. 14. "Investment Management": A discussion of tactical asset allocation neural network methods in asset management. 15. "Learning and Centralization: Theoretical Bounds": Overview of computational learning theory. 16. "Locust Flight": Interesting neural network study of the locust flight system. 17. "Neural Optimization": Discussion of combinatorial optimization using Ising and Potts neural networks. 18. "PAC Learning and Neural Networks": Overview of the Valiant "probabilistically correct learning paradigm in neural networks. 19. "Protein Structure Prediction": Neural network applications to prediction of protein secondary structure. 20. "Schema Theory": Extremely interesting overview of schemas. 21. "Speech Recognition: Pattern Matching": Excellent discussion of the applications of hidden Markov models to speech recognition. 22. "Statistical Mechanics of Neural Networks": Discussion of the use of the Hopfield model in neural networks. 23. Vapnik-Chervonenkis Dimension of Neural Networks": Very interesting discussion of the VC-dimension of neural networks.

Neural Network Bible.......2000-07-29

This is THE neural network and brain theory reference. Owning it is like owning an entire library, though much more compact.

Book Description

Life is so diverse and complex that is seems impossible to extract the general principles governing each individual living system. Fortunately, however, the unrelenting growth of the power of modern computers has opened up entirely unexpected avenues of opportunity for us in exploring the construction of artificial living systems. This has created the possibility to design and conduct dedicated experiments with these systems, and has generated interest in the idea of formulating a set of "general principles of the living state" which are quite independent of a particular implementation. Such a "theory of living systems" might equally well-predict the outcome of experiments performed on the protean living system which gave rise to life on earth, e.g., and RNA world, and those worlds in which information is coded in binary strings compiled to programs that have the ability to self-replicate: thus and instance of "Artificial Life." This book and CD-ROM have been developed in a lab-oriented course taught at Cal Tech in 1995 and 1996, and simultaneously augmented by Artificial Life research conducted there. The courses have been attended by an interdisciplinary group of students from backgrounds in physics, computer science, and the computational neural sciences. Pre- requisite understanding of statistical physics and thermodynamics, basic biology, as well as familiarity with computer architectures and scientific computing techniques are assumed. This project is an attempt to bring together the necessary theoretical groundwork for understanding the dynamics of systems of self-replicating information, as well as the result from initial experiments carried out with artificial living systems based on this paradigm.

Customer Reviews:

Great Content, Author Can't Explain Clearly Though.......2000-11-14

I bought this book to understand the mathematics and physics in A-Life and Complexity. Instead I found this book very long winded and difficult to comprehend exactly what was trying to be said. The content and layout of the book is great, just wish a better writer had been the author of this book. Lots of fancy, big words that are not needed to get the basic points across. Very hard to understand what is being said. It takes smarts and skill to explain complicated, abstract ideas in a meaningful manner. This book does not do that. I wish it did!

At times cryptic, but nevertheless marvellous.......2000-06-02

This is the ONLY book I have seen which brings together all the many and various strands which are essential to the exciting new subjects arising currently around the question: What is Life? It is a stunning tour de force of the basic knowledge you need to possess to work in the areas of A-life or biological complexity.

I should warn: it's not a book I could read through in an afternoon, by any means. At times the descriptions are a little cryptic, so that I had to work at understanding what was being said. But the effort I had to put in was always rewarded with greater understanding. Thank you, Chris Adami.

Hard Science.......2000-05-10

Adami demonstrates how to use the tools of artificial life to conduct pure scientific research. A very clear and readable textbook on the subject, Adami makes me want to go back to graduate school. Here is a chance to take an introductory course in an exciting field of research that is truely table-top science. I loved the book and I didn't even use the CD and software that came with it.

An excellent textbook for this rapidly changing field........1998-08-24

Adami's book is the first comprehensive review of issues pertinent to the field of artificial life. The book is a textbook based on his lectures at CalTech. Some of the topics are a bit brief (Turing machines are summarized in four pages) but that is to be expected for a book whose goal is to integrate concepts from the fields of biology, chemistry, statistics, computer science, information science, etc. I found the book fascinating and Chris includes a CD-rom and several chapters on the Avida simulation developed at CalTech. There are numerous references and problems at the end of each chapter.

Systems Biology: Volume II: Networks, Models, and Applications (Series in Systems Biology)

Average customer rating:

The State of the Art as it Exists Today

Systems Biology: Volume II: Networks, Models, and Applications (Series in Systems Biology)

Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Hardcover

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ASIN: 0195300807

Book Description

The advent of genome sequencing and associated technologies has transformed biologists' ability to measure important classes of molecules and their interactions. This expanded cellular view has opened the field to thousands of interactions that previously were outside the researchers' reach. The processing and interpretation of these new vast quantities of interconnected data call for sophisticated mathematical models and computational methods. Systems biology meets this need by combining genomic knowledge with theoretical, experimental and computational approaches from a number of traditional scientific disciplines to create a mechanistic explanation of cellular systems and processes. Systems Biology I: Genomics and Systems Biology II: Networks, Models, and Applications offer a much-needed study of genomic principles and their associated networks and models. Written for a wide audience, each volume presents a timely compendium of essential information that is necessary for a comprehensive study of the subject. The chapters in the two volumes reflect the hierarchical nature of systems biology. Chapter authors-world-recognized experts in their fields-provide authoritative discussions on a wide range of topics along this hierarchy. Volume I explores issues pertaining to genomics that range from prebiotic chemistry to noncoding RNAs. Volume II covers an equally wide spectrum, from mass spectrometry to embryonic stem cells. The two volumes are meant to provide a reliable reference for students and researchers alike.

Customer Reviews:

The State of the Art as it Exists Today.......2006-11-17

The term 'systems biology' was coined to describe the field of scientific inquiry which takes a global approach to the understanding of cells and the elucidation of biological processes and mechanisms. It is an integrated approach that brings together and leverages theoretical, experimental, and computational approaches in order to establish connections among important molecules or groups of molecules in order to aid the eventual mechanistic explanation of cellular processes and systems.

This is a field that simply did not exist a decade ago, and is the result of the advent of genome sequencing and associated technologies. This has spurred the development of specialized equipment and sophisticated computer programs that have basically developed into its own specialty as well as affecting virtually all aspects of biology.

This series of two books cover the present state of the art in the field by enlisting specialist writers from literally around the world to contribute chapters based on their own expertise and research. As such these volumes are well in advance of anything that can be written by any single individual.

The editors:

Isidore Rigoutsos is manager of Bioinformatics and Pattern Discovery at IBM.

Gregory Stephanopoulos is Professor of Chemical Engineering and Biotechnology at MIT.

Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)

Average customer rating:

Terrible
the worst book I have ever read
Could have been a great one.
An excellent book.
A very bad book. A colection of references w/o explanations

Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)
Pierre Baldi , and Søren Brunak
Manufacturer: The MIT Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 026202506X

Book Description

An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory, which is the situation in molecular biology. The goal in machine learning is to extract useful information from a body of data by building good probabilistic models--and to automate the process as much as possible.

In this book Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed both at biologists and biochemists who need to understand new data-driven algorithms and at those with a primary background in physics, mathematics, statistics, or computer science who need to know more about applications in molecular biology.

This new second edition contains expanded coverage of probabilistic graphical models and of the applications of neural networks, as well as a new chapter on microarrays and gene expression. The entire text has been extensively revised.

Customer Reviews:

Terrible.......2006-03-16

I'm a graduate student, reading a lot of bioinformatics materials. This is by far the worst text I've read on the subject. Poorly explained, poorly edited. Poor.

the worst book I have ever read.......2005-11-06

Just a collection of formulae, in an unclear way. Once we tried to use it in our seminar of bioinformatics, but after a few chapters we had to give it up for its bad writing. I could not find any reason to buy it or read it.

Could have been a great one........2003-12-14

This book is decidedly a mix: some very good information, combined with some very puzzling omissions and uneven editing.

First, the good. The description of stochastic context free grammars is the best I've seen. I don't know any other reference that even hint at how to use generative grammars to evaluate likelihoods. Once they caught my interest, though, the authors did not carry through with training and evaluation algorithms I could really use. I suspect that parts of the information are there, but I'll have to go back over their opaque notation again to work out just what they've given and just what's been left out.

This same pattern - an interesting introduction with missing or mysterious development - recurs throughout the book. The discussion on clustering and phylogeny goes the same way: a number of techniques are mentioned but not developed. The authors mention a tree drawing problem, not just building the tree's topology, but ordering the branches for the most informative rendering. Again, a critical topic and one that most authors miss - in the end, these authors miss it, too, by mentioning but not filling in the idea.

Their discussion of neural nets suffers badly from the authors' partial presentation. Evaluation of network output for a given input is relatively straightforward, and they present it in some detail. Training the net is the real problem, though, and is given less than a page.

Baldi and Brunak give more of the fundamentals than most authors. For example, they explain the maximum entropy principle well enough that I'll use it in lots of other areas. They give some coverage to topics of intermediate complexity, such as the forward and backward algorithms for HMM training. Finally, they fizzle out at the higher levels of complexity - the Baum-Welch algorithm could have followed from the forward and backward methods, but is left as a reference to another book.

There is some good here, especially in the fundamentals behind important techniques. The discussions I wanted - the more avanced topics, in forms I can use - are often weak, missing, or impenetrable. Just a bit more work, clearly within the authors' capability, would have made this a landmark reference.

An excellent book........2001-10-23

Very well written, clear, and self-contained. The authors provide a masterly treatment of machine learning methods (neural networks, hidden markov models, etc.) and their applications to fundamental problems in sequence analyis and biology. The book goes all the way from first principles to advanced research topics and should be valuable for both students and researchers. Second edition has many new topics, including DNA microarrays. Requires some concentration but mathematical details are summarized in the appendices. I strongly recommend it for anyone with an interest in bioinformatics and/or machine learning.

A very bad book. A colection of references w/o explanations.......2001-09-19

I just bought this book and am COMPLETEly disappointed with it.
Here is why. The book is badly written, hard to read and follow. Although it is said that this is a book is for " many readers", it is really for those who have already known all the algorithms. It is simply impossible to learn the algorithms from this book. The chapter on neural network is a few pages. It provieds a few equations for backpropagation. That is it! It is pretty much true for every thing else. Equations, hard to understand sentences, abbreviations with no explnantions, tons of citations everywhere. A book should strive to explain, and not to cite what other papers and go look there all the time. I suspect the few good reviews here are from the authors themselves.

Book Description

The establishment of ecological networks in Europe and greenways in America has required application of the principles of landscape ecology to land use planning. This book provides a thorough overview of recent developments, combining theoretical concepts of landscape ecology with the practice of landscape planning and management. In addition to biological and physical considerations for biodiversity protection and restoration, equal coverage is given to cultural and aesthetic issues illustrating how sustainable land use policies can be implemented.

Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)

Average customer rating:

Informative, but not information I can use
Excellent survey of the field
it's about time!!!

Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)

Manufacturer: The MIT Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0262524236

Book Description

The advent of ever more sophisticated molecular manipulation techniques has made it clear that cellular systems are far more complex and dynamic than previously thought. At the same time, experimental techniques are providing an almost overwhelming amount of new data. It is increasingly apparent that linking molecular and cellular structure to function will require the use of new computational tools.

This book provides specific examples, across a wide range of molecular and cellular systems, of how modeling techniques can be used to explore functionally relevant molecular and cellular relationships. The modeling techniques covered are applicable to cell, developmental, structural, and mathematical biology; genetics; and computational neuroscience. The book, intended as a primer for both theoretical and experimental biologists, is organized in two parts: models of gene activity and models of interactions among gene products. Modeling examples are provided at several scales for each subject. Each chapter includes an overview of the biological system in question and extensive references to important work in the area.

Customer Reviews:

Informative, but not information I can use.......2004-05-03

Regulatory networks are central to every aspect of computational biology. Determining what they are, and what genes, proteins, and post-translational modifications interact is a major and exciting field of study.

I just didn't come away from this book with that excitement. I was hoping for more about the large-scale regulation networks, but these papers go down to the quantum mechanics of interactions between pairs of molecules. I appreciate that the exact interactions matter, and that computation is probably the only way to examine some kinds of interactions (e.g. the ones in lethal mutations). It's just not what I think of as a "network."

I was also hoping for some more specifics about the computation techniques. There were some interesting insights here. For example, I never thought about the similarities between steady state chemical equilibrium and steady state Markov model behavior before, but the formalisms have striking similarities. I was also interested in some of the information-based measures for determining how well a model represents a system. I learned that the statistical assumptions behind normal chemical "equilibrium" break down at the scale of bacteria - instead, presence or absence of individual molecules matters more. Still, those were isolated kinds of facts and never came together into a whole for me.

The range of views was worthwhile. On the whole, though, the models all seemed very low-level to me, probably not well suited to handling more than a few dozen interactions, and the computation specifics were not always explicit. I'm still looking for a book with more information that I can apply directly.

Excellent survey of the field.......2001-08-04

An excellent survey for anyone contemplating doing research in this area. The authors make a special effort to identify the open research problems, what has been done to date and what there is very little of. This book will bridge the gap for anyone with a background in Molecular Biology that wants to build computer models for cellular and genetic activities. It is especially focused on gene regulation, but also covers other modeling areas such as diffusion. In reading this book, you will appreciatge both the good start this field is off to, but also the long way to go before a complete cell can be modeled. A great area to do pioneering work.

it's about time!!!.......2001-04-03

For many years, biologists have been accumulating descriptions of biological "parts" with an almost complete lack of a framework for understanding how those parts might really work together. This book represents the first and so far only example I have seen of an effort to describe modeling techniques that are right now being developed to construct such a framework. There are other books on "computational biology", but most of them are focused only on measuring and comparing different strands of molecules -- this book describes how computational techniques are starting to be applied to actually trying to understand how those molecules work together to generate life. On the outside jacket of the book, Bruce Alberts, President of the National Academy of Science, AND the guy whose book on molecular biology I had to buy for a lot of money when I was in college, describes the authors of this book as being "Brave". I would say it is an introduction to a "Brave New World". This has to be where biology is going -- Each of the chapters are written by different people, and as such there is some variation in readability. I also wish that the color illustrations were part of the chapter they refer to instead of being grouped in the middle. But most of the chapters start with enough of an overview to be understandable to anyone with a decent background in biology. And WOW -- biology is going to get much more exciting!! Oh one other thing -- the art on the inside of the jacket is wonderful - especially in contrast to the black cover with its standard diagram of metabolism -- I wonder if there is a message there :-) .

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