£162.99

Elsevier Robust Theoretical Models in Medicinal Chemistry: QSAR, Artificial Intelligence, Machine Learning, and Deep Learning

Name: Robust Theoretical Models in Medicinal Chemistry: QSAR, Artificial Intelligence, Machine Learning, and Deep Learning
Brand: Elsevier
Price: 162.99 GBP
Availability: InStock

AI & Machine Learning

It has never been this cheap. We have no record of a lower price.

£163 today · cheaper than every other day in the last 3 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 49 days · 49 data points (no recent data)

Historical

Generating forecast…

Price Distribution

Price distribution over 49 days • 1 price levels

Days at Price

Price Analysis

Most common price: £163 (49 days, 100.0%)

Price range: £163 - £163

Price levels: 1 different prices over 49 days

Description

Robust Theoretical Models in Medicinal Chemistry: QSAR, Artificial Intelligence, Machine Learning, and Deep Learning serves as a valuable resource chock full of applications extending into multiple knowledge domains. The meticulous construction of a robust model holds significance, not only in drug discovery but also in engineering, chemistry, pharmaceutical, and food-related research, illustrating the broad spectrum of fields where QSAR methodologies can be instrumental. The activities considered in QSAR span chemical measurements and biological assays, making this approach a versatile tool applicable across various scientific domains. Currently, QSAR finds extensive use in diverse disciplines, prominently in drug design and environmental risk assessment. Quantitative Structure-Activity Relationships (QSAR) represent a concerted effort to establish correlations between structural or property descriptors of compounds and their respective activities. These physicochemical descriptors encompass a wide array of parameters, accounting for hydrophobicity, topology, electronic properties, and steric effects, and can be determined empirically or, more recently, through advanced computational methods. Provides specific introductions and discussions on QSAR theory and methods Analyzes QSAR applicability in Pharmaceutical Chemistry, Food Science, and Environmental Sciences Builds, validates, and interprets robust, predictive, and reliable QSAR models

Product Specifications

Brand: Elsevier
Format: paperback
ASIN: 0443274207
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 05 December 2026
Listed Since: 23 October 2024

Barcode

No barcode data available

Elsevier Robust Theoretical Models in Medicinal Chemistry: QSAR, Artificial Intelligence, Machine Learning, and Deep Learning

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Resilient Futures: System Dynamics, Tech Innovations, and Climate Resilience

Computational Modeling of Intelligent Soft Matter: Shape Memory Polymers and Hydrogels

Simulation and Machine Learning Models for Energy Policy Design

Machine Learning for Materials Discovery: Numerical Recipes and Practical Applications (Machine Intelligence for Materials Science)

Nanobiomaterials and Nanomedicines for Metabolic Disorders (Nanotechnology in Biomedicine)

AI and Machine Learning for Digital Twins: Predictive Analytics and Systems Optimization

Advances in Image Processing, Reliability, and Artificial Intelligence: Data Centred-Techniques and Applications in Edge Computing

Protecting and Mitigating Against Cyber Threats: Deploying Artificial Intelligence and Machine Learning

Wellness Management Powered by AI Technologies (Machine Learning in Biomedical Science and Healthcare Informatics)

Artificial Intelligence and Machine Learning in Data Science and Analytics

The Prediction of Future Pandemics: Artificial Intelligence and Nanotechnology Approaches (Micro and Nano Technologies)

The Geoinformatics Frontier: AI, Big Data, and Crowdsourced Technologies (Earth Observation)

Artificial Intelligence: Data and Model Safety

Human-Machine Interface for Intelligent Vehicles: Design Methodology and Cognitive Evaluation

Multimodal Remote Sensing Fusion and Classification: Algorithms and Applications (Earth Observation)

Integrated Gas Sensing and Biomarker Detection: Sensor Technology and Machine Learning Applications

Advanced Nanomaterials and Nanocomposites for Bioelectrochemical Systems (Micro and Nano Technologies)

Cyanoximes: Chemistry, Coordination and Organometallic Compounds and their Applications

Role of Artificial Intelligence, Telehealth, and Telemedicine in Medical Virology (Medical Virology: From Pathogenesis to Disease Control)

Artificial Intelligence in Chemical Engineering

Artificial Intelligence, Fintech, and Financial Inclusion (Innovations in Big Data and Machine Learning)

Dynamic Mechanical and Creep-Recovery Behavior of Polymer-Based Composites: Mechanical and Mathematical Modeling

A Mastering the Minds of Machines: A Journey into Deep Learning and AI

Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems: Fundamentals, Technologies, and Solutions