One of the foundations of molecular biology is how the interactions of proteins with DNA control many aspects of gene expression. Since the mid-20th century discoveries of the lac repressor and operator and the competition between the cI and cro proteins for the same segment of DNA, we have learned an enormous amount about the interactions of proteins with DNA and their control of fundamental processes in the cell. Introduction to Protein-DNA Interactions: Structure, Thermodynamics, and Bioinformatics describes what we know about protein-DNA interactions from the complementary perspectives of molecular and structural biology and bioinformatics and how each perspective informs the others. A particular emphasis is on how insights from experimental work can be translated into specific computational approaches to create unified view of the field and a fuller understanding of protein-DNA interactions.
One of the foundations of molecular biology is how the interactions of proteins with DNA control many aspects of gene expression. Since the mid-20th century discoveries of the lac repressor and operator and the competition between the cI and cro proteins for the same segment of DNA, we have learned an enormous amount about the interactions of proteins with DNA and their control of fundamental processes in the cell. Introduction to Protein-DNA Interactions: Structure, Thermodynamics, and Bioinformatics describes what we know about protein-DNA interactions from the complementary perspectives of molecular and structural biology and bioinformatics and how each perspective informs the others. A particular emphasis is on how insights from experimental work can be translated into specific computational approaches to create unified view of the field and a fuller understanding of protein-DNA interactions.
Depite the rapid expansion of the field of biophysics, there are very few books that comprehensively treat specific topics in this area. Recently, the field of single molecule biophysics has developed very quickly, and a few books specifically treating single molecule methods are beginning to appear. However, the promise of single molecule biophysics is to contribute to the understanding of specific fields of biology using new methods. This book would focus on the specific topic of the biophysics of DNA-protein interactions, and would include the use of new approaches, including both bulk methods as well as single molecule methods. This would make the book attractive to anyone working in the general area of DNA-protein interactions, which is of course a much wider market than just single molecule biophysicists or even biophysicists. The subject of the book will be the biophysics of DNA-protein interactions, and will include new methods and results that describe the physical mechanism by which proteins interact with DNA. For example, there has been much recent work on the mechanism by which proteins search for specific binding sites on DNA. A few chapters will be devoted to experiments and theory that shed light on this important problem. We will also cover proteins that alter DNA properties to facilitate interactions important for transcription or replication. Another section of the book will cover the biophysical mechanism by which motor proteins interact with DNA. Finally, we will cover larger protein-DNA complexes, such as replication forks, recombination complexes, DNA repair interactions, and their chromatin context.
This book provides both in-depth background and up-to-date information in this area. The chapters are organized by general themes and principles, written by experts who illustrate topics with current findings. Topics covered include: - the role of ions and hydration in protein-nucleic acid interactions - transcription factors and combinatorial specificity - indirect readout of DNA sequence - single-stranded nucleic acid binding proteins - nucleic acid junctions and proteins, - RNA protein recognition - recognition of DNA damage. It will be a key reference for both advanced students and established scientists wishing to broaden their horizons.
"A key aspect of DNA is its ability to form a variety of structures, this book explains the origins and importance of such structures"--Provided by publisher.
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Learn vital information about drug-DNA interactions from Drug-DNA Interactions: Structures and Spectra, the only comprehensive book written about this topic. Understand the types of structural and bonding information that can be obtained using specific physico-chemical methods and discover how to design new drugs that are more effective than current treatments and have fewer side effects. Find detailed information about X-ray crystallography, NMR spectroscopy, molecular modeling, and optical spectroscopy such as UV-Visible absorption, fluorescence, circular dichroism (CD), flow linear dichroism (FLD), infrared (IR) and Raman spectroscopy.
This book is indexed in Chemical Abstracts ServiceThe interactions of proteins with other molecules are important in many cellular activities. Investigations have been carried out to understand the recognition mechanism, identify the binding sites, analyze the the binding affinity of complexes, and study the influence of mutations on diseases. Protein interactions are also crucial in structure-based drug design.This book covers computational analysis of protein-protein, protein-nucleic acid and protein-ligand interactions and their applications. It provides up-to-date information and the latest developments from experts in the field, using illustrations to explain the key concepts and applications. This volume can serve as a single source on comparative studies of proteins interacting with proteins/DNAs/RNAs/carbohydrates and small molecules.
