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Artificial Intelligence In Bioinformatics

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Intelligent Bioinformatics

Intelligent Bioinformatics Book
Author : Edward Keedwell,Ajit Narayanan
Publisher : John Wiley & Sons
Release : 2005-12-13
ISBN : 0470021764
Language : En, Es, Fr & De

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Book Description :

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.

Advanced AI Techniques and Applications in Bioinformatics

Advanced AI Techniques and Applications in Bioinformatics Book
Author : Loveleen Gaur,Arun Solanki,Samuel Fosso Wamba,Noor Zaman Jhanjhi
Publisher : CRC Press
Release : 2021-10-18
ISBN : 100046301X
Language : En, Es, Fr & De

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Book Description :

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

Advanced AI Techniques and Applications in Bioinformatics

Advanced AI Techniques and Applications in Bioinformatics Book
Author : Loveleen Gaur,Arun Solanki,Samuel Fosso Wamba,Noor Zaman Jhanjhi
Publisher : CRC Press
Release : 2021-10-18
ISBN : 1000462986
Language : En, Es, Fr & De

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Book Description :

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

Introduction to Machine Learning and Bioinformatics

Introduction to Machine Learning and Bioinformatics Book
Author : Sushmita Mitra,Sujay Datta,Theodore Perkins,George Michailidis
Publisher : CRC Press
Release : 2019-08-30
ISBN : 9780367387235
Language : En, Es, Fr & De

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Book Description :

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 explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website. Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today's biological experiments.

Machine Learning in Bioinformatics

Machine Learning in Bioinformatics Book
Author : Yanqing Zhang,Jagath C. Rajapakse
Publisher : Wiley
Release : 2009-02-23
ISBN : 0470397411
Language : En, Es, Fr & De

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Book Description :

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 data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.

Machine Learning in Bioinformatics

Machine Learning in Bioinformatics Book
Author : Ernesto Damiani
Publisher : Unknown
Release : 2002
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Machine Learning in Bioinformatics book written by Ernesto Damiani, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics Book
Author : Yi Pan,Jianxin Wang,Min Li
Publisher : John Wiley & Sons
Release : 2013-10-07
ISBN : 1118567811
Language : En, Es, Fr & De

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Book Description :

Algorithmic 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 solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

https www frontiersin org research topics 9029 artificial intelligence bioinformatics development and application of tools for omics and inter omic

https   www frontiersin org research topics 9029 artificial intelligence bioinformatics development and application of tools for omics and inter omic Book
Author : Angelo Facchiano,Dominik Heider,Davide Chicco
Publisher : Frontiers Media SA
Release : 2020-06-18
ISBN : 2889637522
Language : En, Es, Fr & De

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Book Description :

Download https www frontiersin org research topics 9029 artificial intelligence bioinformatics development and application of tools for omics and inter omic book written by Angelo Facchiano,Dominik Heider,Davide Chicco, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Artificial Intelligence in Bioinformatics

Artificial Intelligence in Bioinformatics Book
Author : Mario Cannataro,Pietro Hiram Guzzi,Giuseppe Agapito,Chiara Zucco,Marianna Milano
Publisher : Elsevier
Release : 2021-04-15
ISBN : 9780128229521
Language : En, Es, Fr & De

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Book Description :

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 methods and only touch basic aspects of Artificial Intelligence, machine learning and data mining. To face those issues, the book combines a rigorous introduction of Artificial Intelligence methods in the context of bioinformatics with a deep and systematic review of how those methods are incorporated in bioinformatics tasks and processes. This book first recalls main methods and theory behind Artificial Intelligence, including emergent fields such as Sentiment Analysis and Network Alignment. It then surveys how Artificial Intelligence is exploited in main bioinformatics applications, including sequence analysis, structure analysis, functional analysis, protein classification, omics analysis, biomarker discovery, integrative bioinformatics, protein interaction analysis, metabolic networks analysis, network embedding, ontologies, text mining, reasoning in bioinformatics and explainable models in bioinformatics. Bridges the gap between computer science and bioinformatics, combining an introduction to Artificial Intelligence methods with a systematic review of its applications in the life sciences Brings readers up to speed with current trends and methods in a dynamic and growing field Provides academic teachers with a complete resource, covering fundamental concepts as well as applications

Artificial Intelligence and Heuristic Methods in Bioinformatics

Artificial Intelligence and Heuristic Methods in Bioinformatics Book
Author : Paolo Frasconi,Ron Shamir
Publisher : Unknown
Release : 2003
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

The 14 papers consider how various methods in artificial intelligence are applied to problems in bioinformatics. Among the topics are statistical learning and kernel methods in bioinformatics, new machine learning methods for predicting protein topologies, multiple sequence alignments information in structure and function prediction, pattern discovery and the algorithms of surprise, the computational identification of regulatory sites in DNA sequences, computer system gene discovery for promoter structure analysis, and data acquisition and analysis in near-genome-wide expressions screening of tumor suppressor pathways using model cell lines with inducible transcription factors. There is no subject index. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).

Artificial Intelligence in Bioinformatics

Artificial Intelligence in Bioinformatics Book
Author : Dave W. Corne
Publisher : Unknown
Release : 2001
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Artificial Intelligence in Bioinformatics book written by Dave W. Corne, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

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

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques  Tools  and Applications Book
Author : K. G. Srinivasa,G. M. Siddesh,S. R. Manisekhar
Publisher : Springer
Release : 2020-01-31
ISBN : 9789811524448
Language : En, Es, Fr & De

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Book Description :

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.

Artificial Intelligence in Bioinformatics

Artificial Intelligence in Bioinformatics Book
Author : Mario Cannataro,Pietro Hiram Guzzi,Giuseppe Agapito,Chiara Zucco,Marianna Milano
Publisher : Elsevier
Release : 2021-04-01
ISBN : 0128229292
Language : En, Es, Fr & De

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Book Description :

Artificial Intelligence in Bioinformatics: From Omics Analysis to Deep Learning and Network Mining reviews the main applications of the topic, from omics analysis to deep learning and network mining. The book includes a rigorous introduction on bioinformatics, also reviewing how methods are incorporated in tasks and processes. In addition, it presents methods and theory, including content for emergent fields such as Sentiment Analysis and Network Alignment. Other sections survey how Artificial Intelligence is exploited in bioinformatics applications, including sequence analysis, structure analysis, functional analysis, protein classification, omics analysis, biomarker discovery, integrative bioinformatics, protein interaction analysis, metabolic networks analysis, and much more. Bridges the gap between computer science and bioinformatics, combining an introduction to Artificial Intelligence methods with a systematic review of its applications in the life sciences Brings readers up-to-speed on current trends and methods in a dynamic and growing field Provides academic teachers with a complete resource, covering fundamental concepts as well as applications

Impact of Artificial Intelligence on Bioinformatics

Impact of Artificial Intelligence on Bioinformatics Book
Author : Kiran Sree Pokkuluri,S. S. S. N Usha Devi Nedunuri,Mohan R.
Publisher : Unknown
Release : 2016-08-14
ISBN : 9783659882029
Language : En, Es, Fr & De

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Book Description :

Download Impact of Artificial Intelligence on Bioinformatics book written by Kiran Sree Pokkuluri,S. S. S. N Usha Devi Nedunuri,Mohan R., available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Data Analytics in Bioinformatics

Data Analytics in Bioinformatics Book
Author : Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
Publisher : John Wiley & Sons
Release : 2021-01-20
ISBN : 111978560X
Language : En, Es, Fr & De

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Book Description :

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning 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 data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Artificial Intelligence and Heuristic Methods in Bioinformatics

Artificial Intelligence and Heuristic Methods in Bioinformatics Book
Author : Paolo Frasconi,Ron Shamir
Publisher : NATO Science Series: Computer & Systems Sciences
Release : 2003
ISBN : 9781586032944
Language : En, Es, Fr & De

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Book Description :

This work focuses on methods and algorithms developed within the artificial intelligence community. These include machine learning, data mining, and pattern recognition. These methods provide solutions for the challenges posed by the progressive transformation of biology into data-massive science.

Practical Applications of Computational Biology and Bioinformatics 13th International Conference

Practical Applications of Computational Biology and Bioinformatics  13th International Conference Book
Author : Florentino Fdez-Riverola,Miguel Rocha,Mohd Saberi Mohamad,Nazar Zaki,José A. Castellanos-Garzón
Publisher : Springer
Release : 2019-08-20
ISBN : 3030238733
Language : En, Es, Fr & De

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Book Description :

This book features 21 papers spanning many different sub-fields in bioinformatics and computational biology, presenting the latest research on the practical applications to promote fruitful interactions between young researchers in different areas related to the field. Next-generation sequencing technologies, together with other emerging and diverse experimental techniques, are evolving rapidly, creating numerous types of omics data. These, in turn, are creating new challenges for the expanding fields of bioinformatics and computational biology, which seek to analyse, process, integrate and extract meaningful knowledge from such data. This calls for new algorithms and approaches from fields such as databases, statistics, data mining, machine learning, optimization, computer science, machine learning and artificial intelligence. Clearly, biology is increasingly becoming a science of information, requiring tools from the computational sciences. To address these challenges, we have seen the emergence of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific areas is, more than ever, vital to boost the research efforts in the field and contribute to the training of the new generation of interdisciplinary scientists.

7th International Conference on Practical Applications of Computational Biology Bioinformatics

7th International Conference on Practical Applications of Computational Biology   Bioinformatics Book
Author : Mohd Saberi Mohamad,Loris Nanni,Miguel P. Rocha,Florentino Fdez-Riverola
Publisher : Springer Science & Business Media
Release : 2013-04-19
ISBN : 3319005782
Language : En, Es, Fr & De

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Book Description :

The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘13 hopes to contribute to this effort promoting this fruitful interaction. PACBB'13 technical program included 19 papers from a submission pool of 32 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly have promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work that is being developed by each of the participants.

Special Issue Artificial Intelligence in Bioinformatics

Special Issue Artificial Intelligence in Bioinformatics Book
Author : David Corne
Publisher : Unknown
Release : 2001
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Special Issue Artificial Intelligence in Bioinformatics book written by David Corne, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Distributed Computing Artificial Intelligence Bioinformatics Soft Computing and Ambient Assisted Living

Distributed Computing  Artificial Intelligence  Bioinformatics  Soft Computing  and Ambient Assisted Living Book
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 : 2009-06-08
ISBN : 3642024807
Language : En, Es, Fr & De

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Book Description :

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 (bci); multiobjetive optimization; robotics; bioinformatics; biomedical applications; ambient assisted living (aal) and ambient intelligence (ai); other applications.