Mohlo by se vám také líbit

Více informací o knize Computational Intelligence for Genomics Data

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 476 bodů

Anotace knihy

Computational Intelligence for Genomics Data presents a comprehensive overview of machine learning and deep learning techniques being developed for the analysis of genomic data and the development of disease prediction models. The book focuses on machine and deep learning techniques applied to dimensionality reduction, feature extraction, and expressive gene selection. The book includes the design, algorithms and simulations on MATLAB and Python for the larger prediction models. It also explores the possibilities of software and hardware-based applications and devices for genomic disease prediction models by providing case studies and multiple examples. This book will be a helpful resource for researchers, graduate students and professional engineers who are developing new data analysis techniques and prediction models for the analysis of genomics data.

• Provides comparative analysis of machine learning and deep learning methods in the analysis of genomic data, discussing the major design challenges, best practices, pitfalls and research potential
• Explores machine and deep learning techniques applied to dimensionality reduction, feature extraction, data selection and their application in genomics
• Presents case studies of various diseases based on gene microarray expression data including: cancer, liver disorders, neuromuscular disorders, and neurodegenerative disorders

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer programming / software development Algorithms & data structures

• Plný název: Computational Intelligence for Genomics Data
• Autor: Babita Pandey, Valentina Emilia Balas, Suman Lata Tripathi, Devendra Kumar Pandey, Mufti Mahmud
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 300
• EAN: 9780443300806
• ISBN: 0443300801
• ID: 46090306
• Nakladatelství: Elsevier Science
• Hmotnost: 450 g
• Rozměry: 235 × 191 mm
• Datum vydání: 01. February 2025

Oblíbené z jiného soudku

---

---

---