From the beginning of the OMICs biology era, science has been pursuing the reduction of the complex "e;genome-wide"e; assays in order to understand the essential biology that lies beneath it.
Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells ('systems') involved in a living organism.
This volume guides readers through the field of systems medicine by defining the terminology, and describing how established computational methods form bioinformatics and systems biology can be taken forward to an integrative systems medicine approach.
This volume guides readers through the field of systems medicine by defining the terminology, and describing how established computational methods form bioinformatics and systems biology can be taken forward to an integrative systems medicine approach.
Mass Spectrometry Data Analysis in Proteomics is an in-depth guide to the theory and practice of analyzing raw mass spectrometry (MS) data in proteomics.
Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells ('systems') involved in a living organism.
Computational biology is an interdisciplinary field that applies mathematical, statistical, and computer science methods to answer biological questions, and its importance has only increased with the introduction of high-throughput techniques such as automatic DNA sequencing, comprehensive expression analysis with microarrays, and proteome analysis with modern mass spectrometry.
In Post-Transcriptional Gene Regulation, renowned authors present current technical approaches to most aspects of post-transcriptional control and provide a useful and versatile laboratory bench resource.
Due to their versatility, along with the diminishing costs of library synthesis and the growth of commercial support, peptide microarrays will likely expand beyond being just a research tool into an adaptable and powerful platform to be harnessed for wider drug discovery and point-of-care applications.
With the detailed genomic information that is now becoming available, we have a plethora of data that allows researchers to address questions in a variety of areas.
While extremely large datasets describing gene sequences, mRNA transcripts, protein abundance, and metabolite concentrations are increasingly commonplace, these represent only starting 'parts lists' that are usually insufficient to unlock mechanistic insights on their own right.
As the use of high-throughput screening expands and creates more interest in the academic community, the need for detailed reference materials becomes ever more pressing.
In Protein Dynamics: Methods and Protocols, expert researchers in the field detail both experimental and computational methods to interrogate molecular level fluctuations.
Small molecule microarrays (SMM) were introduced just a decade ago in 1999 and, within a short space of time, have already established themselves as a vibrant, next generation platform for high-throughput screening.
The existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950's, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes.
Rapid advances in computer science, biology, chemistry, and other disciplines are enabling powerful new computational tools and models for toxicology and pharmacology.
Biomedical Literature Mining, discusses the multiple facets of modern biomedical literature mining and its many applications in genomics and systems biology.
Exploring the 2-D gel mapping field, the chapters in this book are separated into four different categories: Part I talks about 2-D maps reproducibility and maps modeling; Part II describes the image analysis tools that provide spot volume datasets; Part III is about the statistical methods applied to spot volume datasets to identify candidate biomarkers; and Part IV discusses differential analysis from direct image analysis tools.
Since each human is genetically distinctive, responding differently to disease-causing factors as well as drugs, the field pharmacogenomics arose to develop personalized medicine, or medicine that deals with the complexity of the human body.
Recent improvements in the efficiency, quality, and cost of genome-wide sequencing have prompted biologists and biomedical researchers to move away from microarray-based technology to ultra high-throughput, massively parallel genomic sequencing (Next Generation Sequencing, NGS) technology.
The post-genomic revolution is witnessing the generation of petabytes of data annually, with deep implications ranging across evolutionary theory, developmental biology, agriculture, and disease processes.
Progress in functional proteomics has been limited for a long time, partially caused by limitations in assay sensitivity and sample capacity; however, protein microarrays have the ability to overcome these limitations so that a highly parallel analysis of hundreds of proteins in thousands of samples is attainable.
Integrated bioinformatics solutions have become increasingly valuable in past years, as technological advances have allowed researchers to consider the potential of omics for clinical diagnosis, prognosis, and therapeutic purposes, and as the costs of such techniques have begun to lessen.
In Tiling Arrays: Methods and Protocols, expert researchers in the field detail many of the methods which are now commonly used to study tiling microarrays in genomic discovery .
Protein Design: Method and Applications, Second Edition expands upon the previous edition with current, detailed ideas on how to approach a potential protein design project.
This book provides current glycoinformatics methods and protocols used to support the determination of carbohydrate structures in biological samples as well as carbohydrate structure databases, the interaction of carbohydrates with proteins, and theoretical and experimental methods to study their three-dimensional structure and dynamics.
Not only is the quantity of life science data expanding, but new types of biological data continue to be introduced as a result of technological development and a growing understanding of biological systems.
Over the past 40 years the field of molecular simulations has evolved from picosecond studies of isolated macromolecules in vacuum to studies of complex, chemically heterogeneous biological systems consisting of millions of atoms, with the simulation time scales spanning up to milliseconds.
Blockchains Surge::: "e;A Deeper Understanding of the Technology Behind Bitcoin and Other Digital Currencies"e; [The Future of Cryptocurrencies in 2024.
