How Long to Read Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms

How Long Does it Take to Read Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms?

It takes the average reader 3 hours and 53 minutes to read Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms by Md. Zia Ur Rahman

Assuming a reading speed of 250 words per minute. Learn more

Description

This book addresses the issue of improving the accuracy in exon prediction in DNA sequences using various adaptive techniques based on different performance measures that are crucial in disease diagnosis and therapy. First, the authors present an overview of genomics engineering, structure of DNA sequence and its building blocks, genetic information flow in a cell, gene prediction along with its significance, and various types of gene prediction methods, followed by a review of literature starting with the biological background of genomic sequence analysis. Next, they cover various theoretical considerations of adaptive filtering techniques used for DNA analysis, with an introduction to adaptive filtering, properties of adaptive algorithms, and the need for development of adaptive exon predictors (AEPs) and structure of AEP used for DNA analysis. Then, they extend the approach of least mean squares (LMS) algorithm and its sign-based realizations with normalization factor for DNA analysis. They also present the normalized logarithmic-based realizations of least mean logarithmic squares (LMLS) and least logarithmic absolute difference (LLAD) adaptive algorithms that include normalized LMLS (NLMLS) algorithm, normalized LLAD (NLLAD) algorithm, and their signed variants. This book ends with an overview of the goals achieved and highlights the primary achievements using all proposed techniques. This book is intended to provide rigorous use of adaptive signal processing algorithms for genetic engineering, biomedical engineering, and bioinformatics and is useful for undergraduate and postgraduate students. This will also serve as a practical guide for Ph.D. students and researchers and will provide a number of research directions for further work. Features Presents an overview of genomics engineering, structure of DNA sequence and its building blocks, genetic information flow in a cell, gene prediction along with its significance, and various types of gene prediction methods Covers various theoretical considerations of adaptive filtering techniques used for DNA analysis, introduction to adaptive filtering, properties of adaptive algorithms, need for development of adaptive exon predictors (AEPs), and structure of AEP used for DNA analysis Extends the approach of LMS algorithm and its sign-based realizations with normalization factor for DNA analysis Presents the normalized logarithmic-based realizations of LMLS and LLAD adaptive algorithms that include normalized LMLS (NLMLS) algorithm, normalized LLAD (NLLAD) algorithm, and their signed variants Provides an overview of the goals achieved and highlights the primary achievements using all proposed techniques Dr. Md. Zia Ur Rahman is a professor in the Department of Electronics and Communication Engineering at Koneru Lakshmaiah Educational Foundation (K. L. University), Guntur, India. His current research interests include adaptive signal processing, biomedical signal processing, genetic engineering, medical imaging, array signal processing, medical telemetry, and nanophotonics. Dr. Srinivasareddy Putluri is currently a Software Engineer at Tata Consultancy Services Ltd., Hyderabad. He received his Ph.D. degree (Genomic Signal Processing using Adaptive Signal Processing algorithms) from the Department of Electronics and Communication Engineering at Koneru Lakshmaiah Educational Foundation (K. L. University), Guntur, India. His research interests include genomic signal processing and adaptive signal processing. He has published 15 research papers in various journals and proceedings. He is currently a reviewer of publishers like the IEEE Access and IGI.

How long is Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms?

Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms by Md. Zia Ur Rahman is 227 pages long, and a total of 58,339 words.

This makes it 77% the length of the average book. It also has 71% more words than the average book.

How Long Does it Take to Read Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms Aloud?

The average oral reading speed is 183 words per minute. This means it takes 5 hours and 18 minutes to read Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms aloud.

What Reading Level is Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms?

Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms?

Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms by Md. Zia Ur Rahman is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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