{"product_id":"quantitative-biology-mathematical-models-of-life-processes-9798196329593","title":"Quantitative Biology: Mathematical Models of Life Processes","description":"\u003cp\u003e • Author(s): Z. Dickin\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Life Sciences - Biology\u003c\/p\u003e\u003cp\u003eQuantitative Biology represents one of the most important transformations in modern life sciences. For centuries, biology was primarily a descriptive discipline focused on observation, classification, and qualitative understanding of living organisms. While these approaches laid the foundation of biological knowledge, they were limited in their ability to explain \u003ci\u003ehow\u003c\/i\u003e biological systems work in a predictive and systematic way.\u003cbr\u003eWith the rapid development of mathematics, physics, computer science, and data analytics, biology has undergone a profound shift. Today, biological systems are increasingly studied through \u003cb\u003emathematical models, computational simulations, statistical analysis, and artificial intelligence techniques\u003c\/b\u003e. This interdisciplinary approach has given rise to the field of \u003cb\u003eQuantitative Biology\u003c\/b\u003e, which aims to understand life in terms of numbers, equations, algorithms, and networks.\u003cbr\u003eThis textbook has been designed to provide a \u003cb\u003ecomprehensive, structured, and integrated introduction\u003c\/b\u003e to Quantitative Biology. It brings together key concepts from molecular biology, genetics, biophysics, systems biology, ecology, neuroscience, bioinformatics, biostatistics, and synthetic biology, presenting them in a unified framework.\u003cbr\u003eThe main objective of this book is to help learners develop a \u003cb\u003econceptual as well as analytical understanding\u003c\/b\u003e of biological systems. Rather than memorizing isolated facts, students are encouraged to understand the underlying principles that govern life processes, such as: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eGrowth and dynamics of populations\u003c\/li\u003e\n\u003cli\u003eMolecular interactions and enzyme kinetics\u003c\/li\u003e\n\u003cli\u003eGenetic regulation and evolutionary change\u003c\/li\u003e\n\u003cli\u003eNeural computation and brain modeling\u003c\/li\u003e\n\u003cli\u003eEcosystem structure and environmental interactions\u003c\/li\u003e\n\u003cli\u003eData-driven biological discovery using AI and computational tools\u003c\/li\u003e\n\u003c\/ul\u003eEach chapter builds progressively, starting from fundamental concepts and advancing toward modern research topics such as molecular simulation, systems biology, and artificial intelligence in life sciences. Mathematical formulations are introduced in a simplified and accessible manner so that learners from both biology and interdisciplinary backgrounds can benefit.\u003cbr\u003eThis book is particularly useful for: \u003cul\u003e\n\u003cli\u003eUndergraduate and postgraduate students of life sciences\u003c\/li\u003e\n\u003cli\u003eStudents preparing for competitive examinations (SSC, WBCS, NEET, CSIR-NET, etc.)\u003c\/li\u003e\n\u003cli\u003eResearchers entering computational and theoretical biology\u003c\/li\u003e\n\u003cli\u003eAnyone interested in the integration of biology with mathematics and computing\u003c\/li\u003e\n\u003c\/ul\u003eAn important feature of this textbook is its \u003cb\u003eintegrated approach\u003c\/b\u003e. Instead of treating disciplines separately, it highlights how different areas of science interact to form a complete understanding of living systems. For example, enzyme kinetics is linked with thermodynamics, population biology is connected to differential equations, and genomics is combined with machine learning.\u003cbr\u003eIn addition to theoretical explanations, this book also emphasizes: \u003cul\u003e\n\u003cli\u003eReal-world biological applications\u003c\/li\u003e\n\u003cli\u003eModeling frameworks\u003c\/li\u003e\n\u003cli\u003eStatistical reasoning\u003c\/li\u003e\n\u003cli\u003eComputational methods\u003c\/li\u003e\n\u003cli\u003eEmerging technologies in biology\u003c\/li\u003e\n\u003c\/ul\u003eThe field of Quantitative Biology is evolving rapidly, and new discoveries are continuously reshaping our understanding of life. Technologies such as \u003cb\u003eCRISPR gene editing, single-cell sequencing, deep learning, and molecular simulation\u003c\/b\u003e are revolutionizing biology and medicine. This textbook aims to provide a strong conceptual foundation to understand and engage with these advancements.\u003cbr\u003eIt is hoped that this work will inspire learners to appreciate biology not just as a descriptive science, but as a \u003cb\u003eprecise, predictive, and mathematically grounded discipline\u003c\/b\u003e that holds the key to solving many of the world's most pressing challenges in health, environment, and technology. \u003cp\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47892828815511,"sku":"9798196329593","price":2122.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798196329593.webp?v=1781189266","url":"https:\/\/atlanticbooks.com\/products\/quantitative-biology-mathematical-models-of-life-processes-9798196329593","provider":"Atlantic Books","version":"1.0","type":"link"}