We’re excited to introduce the Decoding Evolution book series, published in collaboration with Springer Nature and created by Dr. Carlo Pecoraro. This collection of high-quality textbooks complements the practical training offered through Physalia-courses, bridging theory and practice to make advanced bioinformatics, genomics, and data science accessible to students, educators, and researchers alike.

Inspired by years of teaching experience and close work with researchers, the Decoding Evolution series tackles real-world challenges in applying bioinformatics methods to biological and evolutionary questions. Each volume is based on lectures and course materials developed for Physalia-courses, ensuring content that is both cutting-edge and classroom-tested.

The series supports knowledge transfer of emerging techniques and provides practical guidance for handling complex datasets in life sciences. We look forward to expanding the series with more titles covering essential topics in bioinformatics and evolutionary biology.

📘 We are proud to announce the first published book in the series, from Springer Nature: Deep Learning for Life Scientists
Authors: Dr. Filippo Biscarini & Dr. Nelson Nazzicari

This volume introduces deep learning fundamentals and applications in life sciences, guiding readers from neural network theory to hands-on Python notebooks. It empowers biologists to apply AI tools in areas from cancer diagnostics to wildlife monitoring.