Artificial Intelligence Technologies for Computational Biology

By: Ranjeet Kumar Rout (Editor), Saiyed Umer (Editor), Sabha Sheikh (Editor), Amrit Lal Sangal (Editor)

Write A Review

eText | 10 November 2022 | Edition Number 1

At a Glance

Format
ePUB

eText

$97.90

or 4 interest-free payments of $24.48 with

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing.

It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems.

The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology.

This book:

• Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis.

• Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems.

• Presents the application of evolutionary computations for fractal visualization of sequence data.

• Explores the use of genetic algorithms for pair-wise and multiple sequence alignments.

• Examines the roles of efficient computational techniques in biology.