Molecular Networking 1st Edition

Discover the definitive guide to mapping molecular relationships with Molecular Networking, 1st Edition by Caroline Desgranges and Jerome Delhommelle. This authoritative work cuts through complexity to reveal how network-based approaches transform chemical and biological data into actionable insight.

Grounded in clear theory and pragmatic examples, the book walks readers through constructing, visualizing, and interpreting molecular networks. From algorithmic principles to real-world applications in metabolomics, drug discovery, materials science, and systems biology, Desgranges and Delhommelle blend rigorous explanation with practical strategies that researchers and advanced students can apply immediately.

Whether you’re a computational chemist, bench scientist, data analyst, or graduate student, you’ll appreciate the accessible treatment of key topics: data preprocessing, similarity metrics, clustering, network topology, and integrating machine learning for predictive modeling. Each section emphasizes reproducible workflows and decision-making—helping you choose methods that suit your datasets and research goals.

Ideal for academic and industry settings across North America, Europe, the UK, Canada, Australia, and Asia, this edition serves as both a graduate-level textbook and a hands-on reference for labs and teams tackling complex molecular datasets. Readers will gain the confidence to translate network patterns into hypotheses, accelerate discovery pipelines, and communicate findings with clarity.

Add Molecular Networking, 1st Edition to your professional library to master a transformative analytical framework that’s reshaping modern chemistry and biology. Order now to start building smarter, more interpretable molecular models and stay at the forefront of data-driven discovery.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.