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Author: Dr. Lohitha Lakshmi Kanchi and Dr. Lakshmi Praveena Tunuguntla
Publisher: Ashok Yakkaldevi
ISBN: 1329037723
Category : Art
Languages : en
Pages : 139
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Book Description
Among numerous cancers, breast cancer is one type of cancer in which most tumors are formed in females' breasts and rarely in males. Cell growth remains irregular in this type of cancer, and a cancerous tumor in the breast of women develops without a gap. The increasing occurrence of breast cancer in women typically leads to the death of females. Breast Cancer may be caused due to inherited DNA or abnormal change in DNA / RNA structure. The structure and arrangement of nucleotides in genomes decide the characteristics of living organisms. During the transition from parent to child via inheritance, certain abnormal changes in the arrangement of genes take place. The search for disease incidence and control procedures are being carried out quickly, despite considerable progress in breast cancer. It is determined that one reason for the origin and spread of breast cancer in subsequent generations is also genetic. Researchers concentrate on studying cancer cell gene sequences to detect instances of similarities and unusual changes in gene structure from parent to generation of children
Author: Dr. Lohitha Lakshmi Kanchi and Dr. Lakshmi Praveena Tunuguntla
Publisher: Ashok Yakkaldevi
ISBN: 1329037723
Category : Art
Languages : en
Pages : 139
Get Book Here
Book Description
Among numerous cancers, breast cancer is one type of cancer in which most tumors are formed in females' breasts and rarely in males. Cell growth remains irregular in this type of cancer, and a cancerous tumor in the breast of women develops without a gap. The increasing occurrence of breast cancer in women typically leads to the death of females. Breast Cancer may be caused due to inherited DNA or abnormal change in DNA / RNA structure. The structure and arrangement of nucleotides in genomes decide the characteristics of living organisms. During the transition from parent to child via inheritance, certain abnormal changes in the arrangement of genes take place. The search for disease incidence and control procedures are being carried out quickly, despite considerable progress in breast cancer. It is determined that one reason for the origin and spread of breast cancer in subsequent generations is also genetic. Researchers concentrate on studying cancer cell gene sequences to detect instances of similarities and unusual changes in gene structure from parent to generation of children
Author: Sanghamitra Bandyopadhyay
Publisher: World Scientific
ISBN: 9812708898
Category : Computers
Languages : en
Pages : 353
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Book Description
Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers. This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter. Sample Chapter(s). Chapter 1: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (160 KB). Contents: Overview: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (H Tang & S Kim); An Introduction to Soft Computing (A Konar & S Das); Biological Sequence and Structure Analysis: Reconstructing Phylogenies with Memetic Algorithms and Branch-and-Bound (J E Gallardo et al.); Classification of RNA Sequences with Support Vector Machines (J T L Wang & X Wu); Beyond String Algorithms: Protein Sequence Analysis Using Wavelet Transforms (A Krishnan & K-B Li); Filtering Protein Surface Motifs Using Negative Instances of Active Sites Candidates (N L Shrestha & T Ohkawa); Distill: A Machine Learning Approach to Ab Initio Protein Structure Prediction (G Pollastri et al.); In Silico Design of Ligands Using Properties of Target Active Sites (S Bandyopadhyay et al.); Gene Expression and Microarray Data Analysis: Inferring Regulations in a Genomic Network from Gene Expression Profiles (N Noman & H Iba); A Reliable Classification of Gene Clusters for Cancer Samples Using a Hybrid Multi-Objective Evolutionary Procedure (K Deb et al.); Feature Selection for Cancer Classification Using Ant Colony Optimization and Support Vector Machines (A Gupta et al.); Sophisticated Methods for Cancer Classification Using Microarray Data (S-B Cho & H-S Park); Multiobjective Evolutionary Approach to Fuzzy Clustering of Microarray Data (A Mukhopadhyay et al.). Readership: Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, artificial intelligence, data mining, machine learning, electrical engineering, system science; researchers in pharmaceutical industries.
Author: Altuna Akalin
Publisher: CRC Press
ISBN: 1498781861
Category : Mathematics
Languages : en
Pages : 463
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Book Description
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Author: K. R. Venugopal
Publisher: Springer
ISBN: 3642001939
Category : Computers
Languages : en
Pages : 354
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Book Description
The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.
Author: Richard C. Deonier
Publisher: Springer Science & Business Media
ISBN: 0387288074
Category : Computers
Languages : en
Pages : 543
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Book Description
This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.
Author: Gestal Pose, Marcos
Publisher: IGI Global
ISBN: 1615208941
Category : Computers
Languages : en
Pages : 451
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Book Description
"This publication presents a series of practical applications of different Soft Computing techniques to real-world problems, showing the enormous potential of these techniques in solving problems"--Provided by publisher.
Author: Jason T. L. Wang
Publisher: Springer Science & Business Media
ISBN: 9781852336714
Category : Computers
Languages : en
Pages : 356
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Book Description
Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.
Author: Bhanu Prasad
Publisher: Springer
ISBN: 3540774653
Category : Technology & Engineering
Languages : en
Pages : 384
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Book Description
Softcomputing techniques play a vital role in the industry. This book presents several important papers presented by some of the well-known scientists from all over the globe. The main techniques of soft computing presented include ant-colony optimization, artificial immune systems, artificial neural networks, Bayesian models. The book includes various examples and application domains such as bioinformatics, detection of phishing attacks, and fault detection of motors.
Author: Geraldine A. Van der Auwera
Publisher: O'Reilly Media
ISBN: 1491975164
Category : Science
Languages : en
Pages : 496
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Book Description
Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytesâ??or over 50 million gigabytesâ??of genomic data, and theyâ??re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian Oâ??Connor of the UC Santa Cruz Genomics Institute, guide you through the process. Youâ??ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra
Author: Ivan Zelinka
Publisher: Springer
ISBN: 9811319367
Category : Computers
Languages : en
Pages : 870
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Book Description
This book (CCIS 837) constitutes the refereed proceedings of the Second International Conference on Soft Computing Systems, ICSCS 2018, held in Sasthamcotta, India, in April 2018. The 87 full papers were carefully reviewed and selected from 439 submissions. The papers are organized in topical sections on soft computing, evolutionary algorithms, image processing, deep learning, artificial intelligence, big data analytics, data minimg, machine learning, VLSI, cloud computing, network communication, power electronics, green energy.
