This second edition offers a comprehensive examination of statistical methods applicable to bioassay, with emphasis on dose-response relationships, parallel line assays, and probit/logit analysis. It is an essential reference for pharmacologists, statisticians, and researchers involved in experimental biology.
This introductory textbook provides an accessible overview of genome science and bioinformatics for undergraduate and graduate students. It covers the structure, function, and evolution of genomes, as well as the tools used to analyze genomic data, such as microarrays and sequencing technologies.
A textbook that introduces foundational physics concepts through biomedical contexts. Designed for students in life sciences and allied health fields. Covers mechanics, fluids, thermodynamics, waves, electricity, and magnetism, with applied problems and case studies in human physiology and medicine.
This third edition provides comprehensive, practical guidance on the techniques used in the analysis of plant chemicals. It covers modern chromatographic, spectrophotometric, and bioassay methods for identifying and quantifying secondary metabolites in plants
This book presents a detailed treatment of algorithm design and analysis techniques. It covers foundational topics such as algorithm complexity, searching and sorting, dynamic programming, greedy methods, and graph algorithms. With a focus on clarity and simplicity, the book is suitable for undergraduate students in computer science and engineering, offering both theoretical insights and practi…
This book provides a comprehensive introduction to the fundamental concepts of algorithm analysis and design. It covers topics such as time and space complexity, divide and conquer, dynamic programming, greedy algorithms, backtracking, and graph algorithms. Designed for undergraduate computer science and engineering students, the text emphasizes both theoretical foundations and practical implem…
A comprehensive and widely used textbook covering logic, set theory, combinatorics, graph theory, number theory, and algorithmic applications. Practical examples and extensive exercises suit both self-study and course use.