With the rapid development of proteomic technologies in the life sciences and in clinical applications, many bioinformatics methodologies, databases, and software tools have been developed to support comparative proteomics study.
As a fairly new and expansive area of study, plant systems biology has been approached by scientists from fields as varied as plant physiology and astrophysics, creating a wide variety of techniques and methods to further this vital research.
Carbohydrate microarrays emerged as a key technology for the deciphering of the glycospace by providing a multiplex technology where tens to hundreds of carbohydrates/protein interactions can be probed in parallel.
Due to the failing "e;one-drug-fits-all"e; model, it has become increasingly necessary to develop personalized medicine that treats whole systems and brings the right drug to the right patient with the right dosages.
In Plant Metabolic Flux Analysis, expert researchers in the field provide detailed experimental procedures for each step of the flux quantification workflow.
Presenting an area of research that intersects with and integrates diverse disciplines, including molecular biology, applied informatics, and statistics, among others, Bioinformatics for Omics Data: Methods and Protocols collects contributions from expert researchers in order to provide practical guidelines to this complex study.
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 .
In past decades, the area of bioinformatics has proved to be both dynamic and vital, producing a wide spectrum of novel approaches and assuming an increasingly important role in modern bio-technological development.
The rapidly developing methods of systems biology can help investigators in various areas of modern biomedical research to make inference and predictions from their data that intuition alone would not discern.
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.
Structural genomics is a newly emerging field that has arisen following the successful footsteps of the major sequencing efforts generally bundled under the heading "e;genomics"e;.
Rapid advances in computer science, biology, chemistry, and other disciplines are enabling powerful new computational tools and models for toxicology and pharmacology.
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.
In the early years of microarray technology, efforts were directed mainly at profiling expressed genes, while recently the microarray platform has been adapted into diverse applications directed toward the investigation of the physical genome.
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.
With the ultimate goal of systematically and robustly defining the specific perturbations necessary to alter a cellular phenotype, systems metabolic engineering has the potential to lead to a complete cell model capable of simulating cell and metabolic function as well as predicting phenotypic response to changes in media, gene knockouts/overexpressions, or the incorporation of heterologous pathways.
In Protein Dynamics: Methods and Protocols, expert researchers in the field detail both experimental and computational methods to interrogate molecular level fluctuations.
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.
Molecular modeling has undergone a remarkable transformation in the last 20 years, as biomolecular simulation moves from the realm of specialists to the wider academic community.
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.
Systems biology is the study of interactions between assorted components of biological systems with the aim of acquiring new insights into how organisms function and respond to different stimuli.
Chemogenomics aims toward the systematic identification of small molecules that interact with the products of the genome and modulate their biological function.
Chemical library technologies have brought about dramatic changes in the drug discovery process, and, though still evolving, they have become an integral part of ongoing drug discovery research.
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.
Protein microarrays have been used for a wide variety of important tasks, such as identifying protein-protein interactions, discovering disease biomarkers, identifying DNA-binding specificity by protein variants, and for characterization of the humoral immune response.
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.
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.
Over the past twenty years, the development of chromatin immunoprecipitation, or ChIP, assays has immensely enhanced the biological significance of the multifaceted DNA-binding proteins.
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.
From basic performing of sequence alignment through a proficiency at understanding how most industry-standard alignment algorithms achieve their results, Multiple Sequence Alignment Methods describes numerous algorithms and their nuances in chapters written by the experts who developed these algorithms.
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.
The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction.
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.
