SpringerBriefs in Systems Biology – serie

​​ ​Using genome sequencing, one can predict possible interactions among proteins. There are very few titles that focus on protein-protein interaction predictions in bacteria. The authors will describe these methods and further highlight its use to predict various biological pathways and complexity of the cellular response to various environmental conditions. Topics include analysis of complex genome-scale protein-protein interaction networks, effects of reference genome selection on prediction accuracy, and genome sequence templates to predict protein function.

This Brief reports on the interplay of an amino-acid mutation towards substrate which could lead to enhanced effects on mutant. These effects need  to  be given consideration in  the  engineering  processes of protein stability and further exploration of such learning are required to provide novel indication for selection of an enzymes.  There  are  very  few  reports  showing  such  stable,  energy  efficient  model  towards  improved  protein function prediction screening in-silico structure based mutagenesis of xylanases from Thermomyces lanuginosus​

Advances in technological and analytical methods have fostered rapid growth of systems biology and synthetic biology.  There continues to be rapid changes and discoveries in both fields with a small number of recent peer-reviewed reviews indicating some of the relationships between systems biology and synthetic biology.  This proposed SpringerBrief will cover core concepts of systems biology and synthetic biology and illustrate the implementation of associated research methodologies for an integrated approach to specifically address engineering microorganisms for biofuel production.​

The goal of this book is to introduce the biological and technical aspects of next generation sequencing methods, as well as algorithms to assemble these sequences into whole genomes. The book is organized into two parts; part 1 introduces NGS methods and part 2 reviews assembly algorithms and gives a good insight to these methods for readers new to the field. Gathering information, about sequencing and assembly methods together, helps both biologists and computer scientists to get a clear idea about the field. Chapters will include information about new sequencing technologies such as ChIp-seq, ChIp-chip, and De Novo sequence assembly. ​

A key experiment in biomedical research is monitoring the expression of different proteins in order to detect changes that occur in biological systems under different experimental conditions.  The method that is most widely used is the Western blot analysis.  While Western blot is a workhorse in laboratories studying protein expression and has several advantages, it also has a number of significant limitations.  In particular, the method is semi-quantitative with limited dynamic range.  Western blot focuses on a single protein per sample with only a small number of representative samples analyzed in an experiment.  New quantitative tools have been needed for some time to at least supplement, & possibly replace, the Western blot. Mass spectrometric methods have begun to compete with Western blot for routine quantitative analyses of proteins.  One of these methods is based on the tandem mass spectrometry technique of selected reaction monitoring (SRM), which is also called multiple reaction monitoring (MRM).  Selected reaction monitoring is actually an older tandem mass spectrometry technique, first described in the late 70s, that is widely utilized in the quantitative analysis of small molecules like drugs & metabolites.  The use of selected reaction monitoring for the quantitative analysis of proteins has a number of advantages.  Most importantly, it is fundamentally quantitative with a wide dynamic range.  The output of the analysis is a numerical result that can range over several orders of magnitude.  Other advantages include sufficient specificity & sensitivity to detect low abundance proteins in complex mixtures.  Finally, selected reaction monitoring can be multiplexed to allow the quantitative analysis of relatively large numbers of proteins in a single sample in a single experiment.     This Brief will explain both the theoretical & experimental details of the selected reaction monitoring experiment as it is appliedto proteins. ​

With the rise of systems biology as an approach in biochemistry research, using high throughput techniques such as mass spectrometry to generate metabolic profiles of cancer metabolism is becoming increasingly popular. There are examples of cancer metabolic profiling studies in the academic literature; however they are often only in journals specific to the metabolomics community. This book will be particularly useful for post-graduate students and post-doctoral researchers using this pioneering technique of network-based correlation analysis. The approach can be adapted to the analysis of any large scale metabolic profiling experiment to answer a range of biological questions in a range of species or for a range of diseases.

The introduction of Next Generation Sequencing (NGS) technologies resulted in a major transformation in the way scientists extract genetic information from biological systems, revealing limitless insight about the genome, transcriptome and epigenome of any species. However, with NGS, came its own challenges that require continuous development in the sequencing technologies and bioinformatics analysis of the resultant raw data and assembly of the full length genome and transcriptome. Such developments lead to outstanding improvements of the performance and coverage of sequencing and improved quality for the assembled sequences, nevertheless, challenges such as sequencing errors, expensive processing and memory usage for assembly and sequencer specific errors remains major challenges in the field.This book aims to provide brief overviews the NGS field with special focus on the challenges facing the NGS field, including information on different experimental platforms, assembly algorithms and software tools, assembly error correction approaches and the correlated challenges.

This book serves as a brief introduction to phylogenetic trees and molecular evolution for biologists and biology students. It does so by presenting the main concepts in a variety of ways: first visually, then in a history, next in a dice game, and finally in simple equations.The content is primarily designed to introduce upper-level undergraduate and graduate students of biology to phylogenetic tree reconstruction and the underlying models of molecular evolution.  A unique feature also of interest to experienced researchers is the emphasis on simple ways to quantify the uncertainty in the results more fully than is possible with standard methods.

This SpringerBrief focuses on clinical nutrition research, particularly on the effects of slowly absorbed carbohydrates on postprandial glucose metabolism in type 2 diabetes. Slowlyabsorbed carbohydrates will cause gradual increases in blood glucose and insulin levels, and may therefore be effective as part of a treatment strategy for glycemic control and reduction of cardiovascular complications in type 2 diabetes.

Providing a comprehensive overview of cutting-edge research on Omics applications in plant sciences field,“Plant Stress Tolerance” focuses on different approaches towards plant stress tolerance including both biotic stresses and abiotic stresses. This book outlines the challenges facing this area of research, with solid, up-to-date information for graduate students, academic scientists and researchers on using the recent advances of Omics technologies on plant stresses.

This book is a practical review which focuses on computational analysis and on in silico approaches towards the systematic discovery of various key functional gene expression elements in microalgae as a model. So far, in this regard very little information is available. Efficient stepwise procedures for analysing the matrix attachment regions (MARs) are outlined, as well as for translation initiation sites (TIS), signal peptide (SP) sequences, gene optimization and transformation systems. These outlines can be efficiently deployed as practical models for the systematic discovery of key expression elements and for the optimization of cis/transgenes in other micro/organisms. The first chapter is an introduction on the key gene expression elements analysed in this book, including scaffold/matrix attachment regions, translation initiation sites, signal peptides as well as gene optimization. Chapter 2 focuses on systematic strategies and computational approaches toward in silico analysis of each factor. The analyses outcomes is assessed individually in chapter 3 followed by developing the specific conceptual models for each element in Chapter 4. The concluding remarks are discussed in Chapter 5. This work is of interest to computational and experimental biologists interested in transcriptional regulation analysis as well as to researchers and scientists who wish to consider the use of bioinformatics and computational biology in design, analysis, or regulatory reviews of key gene expression elements for the production of recombinant proteins experiments.