Intelligent Bioinformatics

Bioinformatics is contributing to some of the most important advances in medicine and biology. At the forefront of this exciting new subject are techniques known as artificial intelligence which are inspired by the way in which nature solves the problems it faces. This book provides a unique insight into the complex problems of bioinformatics and the innovative solutions which make up ‘intelligent bioinformatics’. Intelligent Bioinformatics requires only rudimentary knowledge of biology, bioinformatics or computer science and is aimed at interested readers regardless of discipline. Three introductory chapters on biology, bioinformatics and the complexities of search and optimisation equip the reader with the necessary knowledge to proceed through the remaining eight chapters, each of which is dedicated to an intelligent technique in bioinformatics. The book also contains many links to software and information available on the internet, in academic journals and beyond, making it an indispensable reference for the 'intelligent bioinformatician'. Intelligent Bioinformatics will appeal to all postgraduate students and researchers in bioinformatics and genomics as well as to computer scientists interested in these disciplines, and all natural scientists with large data sets to analyse.

Produk Detail:

  • Author : Edward Keedwell
  • Publisher : John Wiley & Sons
  • Pages : 294 pages
  • ISBN : 0470021764
  • Rating : 3/5 from 1 reviews
CLICK HERE TO GET THIS BOOKIntelligent Bioinformatics

Intelligent Bioinformatics

Intelligent Bioinformatics
  • Author : Edward Keedwell,Ajit Narayanan
  • Publisher : John Wiley & Sons
  • Release : 13 December 2005
GET THIS BOOKIntelligent Bioinformatics

Bioinformatics is contributing to some of the most important advances in medicine and biology. At the forefront of this exciting new subject are techniques known as artificial intelligence which are inspired by the way in which nature solves the problems it faces. This book provides a unique insight into the complex problems of bioinformatics and the innovative solutions which make up ‘intelligent bioinformatics’. Intelligent Bioinformatics requires only rudimentary knowledge of biology, bioinformatics or computer science and is aimed at interested

Bioinformatics

Bioinformatics
  • Author : Pierre Baldi,Professor Pierre Baldi,Søren Brunak,Francis Bach
  • Publisher : MIT Press
  • Release : 19 January 2021
GET THIS BOOKBioinformatics

Pierre Baldi and Soren 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 at two types of researchers and students. First are the biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function. Second are those with a primary background in physics, mathematics, statistics,

Artificial Intelligence in Bioinformatics

Artificial Intelligence in Bioinformatics
  • Author : Mario Cannataro,Pietro Hiram Guzzi,Giuseppe Agapito,Chiara Zucco,Marianna Milano
  • Publisher : Elsevier
  • Release : 15 April 2021
GET THIS BOOKArtificial Intelligence in Bioinformatics

Artificial Intelligence is used in several application domains to solve problems with improved accuracy and speed. This work reviews the main applications of Artificial Intelligence in Bioinformatics, from omics analysis, to deep learning and network mining. A main need for a new resource in this area is related to the fact that Artificial Intelligence is mainly treated in computer science texts, where the main focus is on computational aspects. On the other hand, bioinformatics books focus mainly on bioinformatics key

Application Of Omics, Ai And Blockchain In Bioinformatics Research

Application Of Omics, Ai And Blockchain In Bioinformatics Research
  • Author : Tsai Jeffrey J P,Ng Ka-lok
  • Publisher : World Scientific
  • Release : 14 October 2019
GET THIS BOOKApplication Of Omics, Ai And Blockchain In Bioinformatics Research

With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare.Two such areas are: (i) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (ii) blockchain technology will enable medical doctors to securely

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications
  • Author : K. G. Srinivasa,G. M. Siddesh,S. R. Manisekhar
  • Publisher : Springer Nature
  • Release : 30 January 2020
GET THIS BOOKStatistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.

Machine Learning in Bioinformatics

Machine Learning in Bioinformatics
  • Author : Yanqing Zhang,Jagath C. Rajapakse
  • Publisher : John Wiley & Sons
  • Release : 23 February 2009
GET THIS BOOKMachine Learning in Bioinformatics

An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science

Bioinformatics Computing

Bioinformatics Computing
  • Author : Bryan P. Bergeron
  • Publisher : Prentice Hall Professional
  • Release : 19 January 2021
GET THIS BOOKBioinformatics Computing

Comprehensive and concise, this handbook has chapters on computing visualization, large database designs, advanced pattern matching and other key bioinformatics techniques. It is a practical guide to computing in the growing field of Bioinformatics--the study of how information is represented and transmitted in biological systems, starting at the molecular level.

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics
  • Author : Yi Pan,Jianxin Wang,Min Li
  • Publisher : John Wiley & Sons
  • Release : 07 October 2013
GET THIS BOOKAlgorithmic and Artificial Intelligence Methods for Protein Bioinformatics

An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and

Evolutionary Computation in Bioinformatics

Evolutionary Computation in Bioinformatics
  • Author : Gary B. Fogel,David W. Corne,Gary B.. Fogel
  • Publisher : Morgan Kaufmann
  • Release : 19 January 2021
GET THIS BOOKEvolutionary Computation in Bioinformatics

This book offers a definitive resource that bridges biology and evolutionary computation. The authors have written an introduction to biology and bioinformatics for computer scientists, plus an introduction to evolutionary computation for biologists and for computer scientists unfamiliar with these techniques.

Artificial Intelligence and Molecular Biology

Artificial Intelligence and Molecular Biology
  • Author : Lawrence Hunter
  • Publisher : Aaai Press
  • Release : 19 January 1993
GET THIS BOOKArtificial Intelligence and Molecular Biology

These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. The enormous amount of data generated by the Human Genome Project and other large-scale biological research has created a rich and challenging domain for research in artificial intelligence. These original contributions provide a current sampling of AI approaches to problems of biological significance; they are

Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living

Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
  • Author : Sigeru Omatu,Miguel P. Rocha,Jose Bravo,Florentino Fdez Riverola,Emilio Corchado,Andrés Bustillo,Juan Manuel Corchado Rodríguez
  • Publisher : Springer Science & Business Media
  • Release : 08 June 2009
GET THIS BOOKDistributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living

This book constitutes the refereed proceedings of the 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, held in Salamanca, Spain in June 2009. The 167 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 230 submissions. The papers are organized in thematic sections on theoretical foundations and models; learning and adaptation; self-organizing networks, methods and applications; fuzzy systems; evolutionary computation and genetic algoritms; pattern recognition; formal languages in linguistics; agents and multi-agent on intelligent systems; brain-computer interfaces (

Introduction to Machine Learning and Bioinformatics

Introduction to Machine Learning and Bioinformatics
  • Author : Sushmita Mitra,Sujay Datta,Theodore Perkins,George Michailidis
  • Publisher : CRC Press
  • Release : 05 June 2008
GET THIS BOOKIntroduction to Machine Learning and Bioinformatics

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors

Artificial Intelligence Methods and Tools for Systems Biology

Artificial Intelligence Methods and Tools for Systems Biology
  • Author : W. Dubitzky,Francisco Azuaje
  • Publisher : Springer Science & Business Media
  • Release : 05 January 2005
GET THIS BOOKArtificial Intelligence Methods and Tools for Systems Biology

This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain. As design blueprint, the book is intended for scientists and other professionals tasked with developing and using AI technologies in the context of life sciences research. As a user guide,