Artificial Intelligence Technologies for Computational Biology

個数:

Artificial Intelligence Technologies for Computational Biology

  • 提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
    重要ご説明事項
    1. 納期遅延や、ご入手不能となる場合が若干ございます。
    2. 複数冊ご注文の場合は、ご注文数量が揃ってからまとめて発送いたします。
    3. 美品のご指定は承りかねます。

    ●3Dセキュア導入とクレジットカードによるお支払いについて
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Hardcover:ハードカバー版/ページ数 324 p.
  • 言語 ENG
  • 商品コード 9781032160009
  • DDC分類 570.28563

Full Description

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.

Contents

1. Graph Representation Learning for Protein Classification 2. Prediction of Methylation Sites in Protein Sequences 3. A Taxonomy of e-Healthcare Techniques and Solutions 4. Classification of Lung Diseases Using Machine Learning Techniques 5. Multi-Objective Bacterial Foraging Optimization 6. Artificial Intelligence for Biomedical Informatics 7. A Novel Approach for Feature Selection Using Artificial Neural Networks and Particle Swarm Optimization. 8. DL-based Diabetic Retinopathy Stage Classification from Retinal Fundus Images 9. Cancer Diagnosis from Histopathology Images Using Deep Learning: A Review 10. Skin Lesion Classification by Using Deep Tree-CNN
Prakash Choudhary and Sameer Mansuri 11. Diagnose Covid-19 On Its Early Stages Using Lung CT Images 12. Impact of Machine Learning Practices on Biomedical Informatics 13. Recognition of Types of Arrhythmia 14. ML and DL Algorithms on Multi-Modal Omics Data.

最近チェックした商品