Models and Algorithms for Biomolecules and Molecular Networks.pdf
The subjects of the book are biomolecules and biomolecular networks. The first part of the book will cover the areas of structural and geometric models of biomolecules and their shape characterization. First, there will be a discussion of geometry of proteins, including voids and pockets, their scaling properties and origin, and how to effectively use them to infer and characterize the biological functions of proteins, as well as the detection of backbone similarity of proteins regardless of the sequence ordering. This will be followed by a discussion of the development of sampling techniques for conformations of biomolecules, and effective scoring functions to identify those that are similar to native structures. Then, there will be a discussion on models and computational techniques for studying folding and dynamics of protein molecules.
The second part of the book will cover interaction networks of biomolecules. This will include stochastic models for networks with small copy numbers of molecular species, as those arising in genetic circuits, protein synthesis, and transcription binding, and algorithms of computing the properties of stochastic molecular networks. There will be a section on signal transduction networks that arise, for example, complex interactions between the numerous constituents such as DNA, RNA, proteins and small molecules in a complex biochemical system such as a cell. Experimental protocols and algorithmic methodologies necessary to synthesize these networks will also be included. Of special interest will be the problem of synthesizing these networks from double-causal experimental evidences and methods for reverse engineering such networks based on experimental protocols.