Artificial intelligence (AI) in cell and genetic engineering edited by Sudip Mandal

Format:

Book

Contributor:

Mandal, Sudip, editor.

Series:

Methods in molecular biology (Clifton, N.J.) 1940-6029

Methods in molecular biology 1940-6029

Language:

English

Subjects (All):

Genetic engineering.

Artificial intelligence--Biological applications.

Artificial intelligence.

Artificial intelligence--Medical applications.

Cells.

Physical Description:

1 online resource

Place of Publication:

Springer US 2025

New York, NY Humana Press 2025

Summary:

This volume focuses on how different artificial intelligence (AI) techniques like Artificial Neural Network, Support Vector Machine, Random Forest, k-means Clustering, Rough Set Theory, and Convolutional Neural Network models are used in areas of cell and genetic engineering. The chapters this book cover a variety of topics such as molecular modelling in drug discovery, design of precision medicine, protein structure prediction, and analysis using AI. Readers can also learn about AI-based biomolecular spectroscopy, cell culture-system, AI-based drug discovery, and next generation sequencing. The book also discusses the application of AI in analysis of genetic diseases such as finding genetic insights of oral and maxillofacial cancer, early screening and diagnosis of autism, and classification of breast cancer microarray data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Artificial Intelligence (AI) in Cell and Genetic Engineering is a valuable resource for readers in various research communities who want to learn more about the real-life application of artificial intelligence and machine learning in systems biology, biotechnology, bioinformatics, and health-informatics especially in the field of cell and genetic engineering

Contents:

Overview of Molecular Modelling in Drug Discovery with a Special Emphasis on the Applications of Artificial Intelligence

Integrative AI-Based Approaches to Connect the Multiome to Use Microbiome-Metabolome Interactive Outcome as Precision Medicine

Artificial Intelligence (AI) Based Protein Structure Prediction and Analysis

Artificial Intelligence in Cellular and Biomolecular Spectroscopy: A New Horizon

R-Based Protocols to Predict Synthetic Lethal Interactions in Cancers using Machine-Learning Tools

Advancements in AI for Computational Biology and Bioinformatics: A Comprehensive Review

Integrating Genetic Insights and Artificial Intelligence for Enhanced Oral and Maxillofacial Cancer Care

AI-Based Drug Discovery and Design for Different Genetic Designs

AI-Assisted Cell Culture-System

Review on Advancement of AI in Cell Engineering and Molecular Biology

High-Throughput Virtual Screening of Small Molecule Modulators against Viral Proteins

AI Revolutionizing Cell and Genetic Engineering: Innovations and Applications

Recent Developments in the Application of Artificial Intelligence and Machine Learning in Early Screening and Diagnosis of Autism

Artificial Intelligence in CRISPR-Cas Systems: A Review of Tool Applications

Machine Learning Approaches for the Identification of Genetic Interactions

Artificial Intelligence-Based Genome Editing in CRISPR/Cas9

Harnessing the Power of AI in Cell and Genetic Engineering

MLCDL: A Critical Practice and Implementation of Multi-Tissue Classification and Diagnosis Using Deep Learning Algorithm

Classification of Breast Cancer Microarray Data and Identification of Responsible Genes using Rough Set Theory

Deep-Genomics: Deep Learning Based Analysis of Genome-Sequenced Data for Identification of Gene Alterations

The Use of AI for Phenotype-Genotype Mapping

Interface of Artificial Intelligence with Conventional Biostatistics in Healthcare Research

Review on Advancement of AI in Nutrigenomics

In Silico Validation of AI-Assisted Drugs in Healthcare

From DNA to Big Data: NGS Technologies and Their Applications

Review on Advancement of AI in Synthetic Biology

Notes:

Includes index

Online resource; title from PDF title page (SpringerLink, viewed July 1, 2025)

Other Format:

Print version :

ISBN:

9781071646908

1071646907

OCLC:

1526043055

Publisher Number:

CIPO000300909

Access Restriction:

Restricted for use by site license