Learn IT - Books tags bioinformatics

The 3rd International Workshop on Intelligent Data Analysis and Management (Springer Proceedings in Complexity)

Springer, 2013

These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving...

Maximum Mac OS X Security

Sams Publishing, 2003

While Mac OS X is becoming more and more stable with each release, its UNIX/BSD underpinnings have security implications that ordinary Mac users have never before been faced with. Mac OS X can be used as both a powerful Internet server, or, in the wrong hands, a very powerful attack launch point.

Yet most Mac OS X books are generally...

Constraint Logic Programming using Eclipse

Cambridge University Press, 2007

Constraint logic programming lies at the intersection of logic programming, optimisation and artificial intelligence. It has proved a successful tool in many areas including production planning, transportation scheduling, numerical analysis and bioinformatics. Eclipse is one of the leading software systems that realise its underlying...

Bayesian Reasoning and Machine Learning

Cambridge University Press, 2012

We live in a world that is rich in data, ever increasing in scale. This data comes from many dierent sources in science (bioinformatics, astronomy, physics, environmental monitoring) and commerce (customer databases, nancial transactions, engine monitoring, speech recognition, surveillance, search). Possessing the knowledge as to...

Success in Evolutionary Computation (Studies in Computational Intelligence)

Springer, 2008

Darwinian evolutionary theory is one of the most important theories in human history for it has equipped us with a valuable tool to understand the amazing world around us. There can be little surprise, therefore, that Evolutionary Computation (EC), inspired by natural evolution, has been so successful in providing high quality solutions in a large...

Language and Automata Theory and Applications: 5th International Conference

Springer, 2012

These proceedings contain the papers that were presented at the 5th International Conference on Language and Automata Theory and Applications (LATA 2011), held in Tarragona, Spain, during May 26–31, 2011.

The scope of LATA is rather broad, including: algebraic language theory; algorithms for semi-structured...

53: Scientific Foundations of Clinical Practice: Part II, An Issue of Pediatric Clinics, 1e (The Clinics: Internal Medicine)

Saunders, 2006

In the last decade, the delineation of the human genome and the development of high throughput genomics and proteomics have transformed the practice of Pediatrics. The study of normal childhood growth and development, and pediatric diseases now focuses on the delineation of normal and abnormal gene expression, resultant cellular and organ...

Handbook of Granular Computing

John Wiley & Sons, 2008

Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest...

53: Scientific Foundations of Clinical Practice: Part I, An Issue of Pediatric Clinics, 1e (The Clinics: Internal Medicine)

Saunders, 2006

Data Mining in Bioinformatics (Advanced Information and Knowledge Processing)

Springer, 2004

The aim of this book is to introduce the reader to some of the best techniques for data mining in bioinformatics in the hope that the reader will build on them to make new discoveries on his or her own. The book contains twelve chapters in four parts, namely, overview, sequence and structure alignment, biological...

Utility-Based Learning from Data

CRC Press, 2010

Statistical learning — that is, learning from data — and, in particular, probabilistic model learning have become increasingly important in recent years. Advances in information technology have facilitated an explosion of available data. This explosion has been accompanied by theoretical advances, permitting new and...

Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

O'Reilly, 2015

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

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