Bioinformatics Computing

Rating:
Summary: Comprehensive Introduction to the filed of Bioinformatics
Review: Bergeron wrote this book such that if you have a computer background, you can relate to the topic at hand, and if you have a biology background, you can pick up the material quickly. He uses one to teach the other, and does so rather comprehensively. Major topics and areas of interests in bioinformatics are covered, such as:
* Databases
* Networks and the Internet
* Bioinformatics search engines
* Data mining techniques
* Statistics
* Pattern Matching
* Simulation techniques and modeling

Any of these topics deserve a volume of books dedicated to them, but the author gives the readers enough information that can be useful in determining where to go next. Even though the topics are mostly computing related, the author takes a great care at talking about these topics in the context of Bioinformatics. He even lists the specific applications of each topic at the beginning of each chapter to aid the reader in relating to the topic at hand. For example, after reading the chapter on modeling and simulation, you would know that modeling is used to determine the efficacy of drugs and to determine drug side effects during the drug discovery process.

Databases are probably one of the most important and well known tools in Bioinformatics. The enormous amount of data available for analysis requires large and fast databases. In fact, the amount of data in bioinformatics doubles every eighteen months, so databases and database design is an integral part of bioinformatics computing. In addition to the vast amount of raw data (sequence data and protein data for example) that is stores in databases, the analysis such as pattern matching, simulation and visualization of data requires constant access to databases. The author talks about what are know as primary databases, databases that are used to store raw data, and other value added databases, the one's that store analyzed and/or verified data. One thing that reader gets out databases is the realization of what the data life cycle is in the bioinformatics world, and how it affects all the application areas of bioinformatics.

The databases around the world are either somehow integrated together ease the task of data discovery and data mining. Due to the vast amount of information available, various data mining techniques have been developed over the years to assist in finding the data that a researcher is looking for. Tasks such as data enrichment, missing value analysis for sequence data, data characterization and data distribution analysis mark some of the tasks that data mining techniques needs to accomplish. A number of data mining techniques such as hidden Markov Models, Decision Trees, Neural Networks and Genetic Algorithms are talked about and the pro's and con's of each one is discusses in detail. A bioinformatician needs to be at least aware of the various data mining techniques and should have an overview how they work and why they work in general.

After the data has been discovered, a method of visualization that can get the point across, per se, needs to be used. Visualization and simulation techniques are talked about to show the reader what a bioinformatician needs to do with the information found. There are a number of graphical tools available out there, some free and some not, that are used heavily in this business to aid the understanding of the vast amount of information that is available. Various modeling techniques are being used today to aid with the drug discovery process and figuring out the side effect of newly developed drugs. I would say that this area of bioinformatics will see the most growth in the coming years, and the author, Bryan Bergeron, does a great job discussing this topic.

Statistics is another technique used heavily in bioinformatics computing. Even though most of the statistical tools, Matlab and many others, have been used for a number of years, one must know the theory and reason behind using numerous statistical techniques in Bioinformatics. These techniques are integrated into bioinformatics search engines and the software applications for modeling and simulations, but one still needs to know how they work. Bioinformatics is a new field of study, and not by any means been perfected, so there are still a number research track and advancements that are still untapped, thus making the theory behind how some of the available tools work very important in this field.

Bryn Bergeron in Bioinformatics Computing gives the necessary background for anyone interested in the field of bioinformatics. After reading this book, a reader can get a good idea of which area s/he wants to pursue further. The topics are broken into logical units that can aid the reader in realizing what specific field of bioinformatics is more interesting than others.

Even if you don't decide to pickup one of many advanced books in this topic, you should know about an industry that is growing rapidly, and Bergeron's book can aid you to do just that.



Rating:
Summary: Bioinformatics for now and the future
Review: Dr, Beregeron ofers a sensible yet visionary exposition of the field. For me, the future direction of this field is most compelling. It is a primer that can be challenging to the most sophisticated afficionado, also.

Rating:
Summary: Solid introduction to this field of biology
Review: Ok, I'm not done yet with the book but after two chapters, I could already share with people something: this book is a solid introduction to the field of biocomputing. It cover many aspects in 10 differents chapters (database, data mining, collaboration, read the table of contents).

The autor is enthousiast about his field of research but he doesn't miss an important thing: criticism!! At the end of chapter, you have a small dose of concerns he have about biocomputing. Where we could make mystakes, what we should do?

I'm about to choose if I want to do my master degree in this discipline and this book is great to introduce me with a large perspective to this branch of science.

If you working in this industry, this book might be a little bit boring but even for me who work 5 years with computers networks and databases, both chapters about those technologies learned me something interesting so... I'm quite happy about my decision to acquire this book.

Rating:
Summary: A must read!
Review: This book was a pleasant surprise. It's one of the few books on bioinformatics that I've read that doesn't assume the reader has a PhD in biochemistry or mathematics. It's a gentle but thorough introduction to many of the problems faced by life scientists who are trying to get a handle on this thing called bioinformatics. I've been working in the life sciences for years, and this is the first book I've read that explains how I can make use of the various search engines, genomic analysis tools, and the dozens of genomics databases worldwide in my day-to-day life.

I especially appreciate the author's frank analysis of the state of the art at the end of each chapter. He seems to put a balanced spin on the field, pointing out the vast potential of bioinformatics computing in practical medicine and materials synthesis, while grounding the reader in current political and economic realities that are limiting many aspects of the field.

I consider it a must read.

Rating:
Summary: A must read!
Review: This book was a pleasant surprise. It's one of the few books on bioinformatics that I've read that doesn't assume the reader has a PhD in biochemistry or mathematics. It's a gentle but thorough introduction to many of the problems faced by life scientists who are trying to get a handle on this thing called bioinformatics. I've been working in the life sciences for years, and this is the first book I've read that explains how I can make use of the various search engines, genomic analysis tools, and the dozens of genomics databases worldwide in my day-to-day life.

I especially appreciate the author's frank analysis of the state of the art at the end of each chapter. He seems to put a balanced spin on the field, pointing out the vast potential of bioinformatics computing in practical medicine and materials synthesis, while grounding the reader in current political and economic realities that are limiting many aspects of the field.

I consider it a must read.