{"title":"Computational Molecular Biology","description":"\u003cp\u003eDelve into the fascinating world of Computational Molecular Biology. Explore titles covering bioinformatics, genomics, and proteomics. Perfect for researchers and students alike, find your next insightful read here.\u003c\/p\u003e","products":[{"product_id":"learning-and-inference-in-computational-systems-biology-book-neil-d-lawrence-9780262013864","title":"Learning and Inference in Computational Systems Biology","description":"\u003cp\u003e\u003cb\u003eTools and techniques for biological inference problems at scales ranging from genome-wide to pathway-specific.\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eComputational systems biology unifies the mechanistic approach of systems biology with the data-driven approach of computational biology. Computational systems biology aims to develop algorithms that uncover the structure and parameterization of the underlying mechanistic model--in other words, to answer specific questions about the underlying mechanisms of a biological system--in a process that can be thought of as learning or inference. This volume offers state-of-the-art perspectives from computational biology, statistics, modeling, and machine learning on new methodologies for learning and inference in biological networks.The chapters offer practical approaches to biological inference problems ranging from genome-wide inference of genetic regulation to pathway-specific studies. Both deterministic models (based on ordinary differential equations) and stochastic models (which anticipate the increasing availability of data from small populations of cells) are considered. 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Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. \u003ci\u003eAn Introduction to Bioinformatics Algorithms\u003c\/i\u003e is one of the first books on bioinformatics that can be used by students at an undergraduate level. 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