Most genome-wide assays provide averages across large numbers of cells, but recent technological advances promise to overcome this limitation. Pioneering single-cell assays are now available for genome, epigenome, transcriptome, proteome, and metabolome profiling. Here, we describe how these different dimensions can be combined into multi-omics assays that provide comprehensive profiles of the same cell.
Is the European Union (EU) regulatory framework for genetically modified organisms (GMOs) adequate for emerging techniques, such as genome editing? This has been discussed extensively for more than 10 years. A recent proposal from The Netherlands offers a way to break the deadlock. Here, we discuss how the proposal would affect examples from public plant research.
Clustered regularly interspaced short palindromic repeats (CRISPR) technology has enabled genetic engineering feats previously considered impracticable, offering great hopes for solutions to problems facing society. We consider it timely to highlight how CRISPR can benefit public health, medicine, and agriculture in sub-Saharan Africa (SSA) and offer recommendations for successful implementation.
Highlights • The current status of the Pichia pastoris genome is shown to lack extensive functional annotation. • GO annotation transfer and literature curation pipelines improve the functional annotation of genomes. • Pipelines and tools that can improve the annotation status of the genomes of Pichia pastoris and many industrial microbes are considered. • Well-annotated genome sequences will facilitate the utilization of these microbes in a broader range of synthetic biology applications.
Highlights • We review recent advances in nucleic acid chemistry and polymerase engineering that have enabled the synthesis, replication, and evolution of a wide range of nucleic acid-like synthetic genetic polymers (XNAs) with improved chemical and biological stability. • We discuss the likely biotechnological impact of the further development of XNA technology for the generation of novel ligands, enzymes, and nanostructures with tailor-made chemistry.
The field of rheology of foods is extensive and a researcher in the field is called upon to interact with a diverse group of scientists and engineers. In arranging this symposium for the AIChE meeting in Chicago in November 1990 the papers were carefully selected to highlight this diversity. All but two of the chapters in this book are based on papers which were presented at this symposium, the additional paper was presented at the Conference on Food Engineering, Chicago, March 1991, and the book opens with an introductory overview. All the papers are peer–reviewed research contributions. The chapters cover a range of applications of food rheology to such areas as food texture, stability, and processing. This volume will be a reference source for workers within this wide and varied field..
There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. Introduction to stochastic process modelling as an alternative modelling technique Shows how stochastic modelling may be succesful where the traditional technique fails Overview of stochastic modelling in process technology in the research literature Illustration of the principle by a wide range of practical examples In-depth and self-contained discussions Points the way to both mathematical and technological research in a new, rewarding field.
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The identification and validation of biomarkers for diagnosing Alzheimer's disease (AD) and other forms of dementia are increasingly important. To date, ELISA measurement of β-amyloid(1–42), total tau and phospho-tau-181 in cerebrospinal fluid (CSF) is the most advanced and accepted method to diagnose probable AD with high specificity and sensitivity. However, it is a great challenge to search for novel biomarkers in CSF and blood by using modern potent methods, such as microarrays and mass spectrometry, and to optimize the handling of samples (e.g. collection, transport, processing, and storage), as well as the interpretation using bioinformatics. It seems likely that only a combined analysis of several biomarkers will define a patient-specific signature to diagnose AD in the future.