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A Systems Biology Approach to Advancing Adverse Outcome Pathways for Risk Assessment
Social pressure to minimize the use of animal testing, the ever-increasing concern on animal welfare, and the need for more human-relevant and more predictive toxicity tests are some of the drivers for new approaches to chemical screening. This book focuses on The Adverse Outcome Pathway, an analytical construct that describes a sequential chain of causally linked events at different levels of biological organization that lead to an adverse health or ecotoxicological effect. While past efforts have focused on toxicological pathway-based vision for human and ecological health assessment relying on in vitro systems and predictive models, The Adverse Outcome Pathway framework provides a simplified and structured way to organize toxicological information. Within the book, a systems biology approach supplies the tools to infer, link, and quantify the molecular initiating events and the key events and key event relationships leading to adverse outcomes. The advancement of these tools is crucial for the successful implementation of AOPs for regulatory purposes.
Toxicological Evaluation of Electronic Nicotine Delivery Products
Toxicological Evaluation of Electronic Nicotine Delivery Products (ENDP) discusses the scientific basis for the toxicological assessment and evaluation of ENDPs. The book covers aerosol chemistry, in vitro and in vivo studies as well as clinical studies. It provides the basis for the evaluation of short and long term-effects, along with relative risks. It also examines the potential role of ENDPs in tobacco harm reduction and how they may reduce the risk of disease in smokers who switch to them. This book is a comprehensive resource for toxicologists, health practitioners and public health professionals who want the scientific information necessary to assess the relative risk of ENDPs when compared with cigarette smoking and cessation. - Delivers a comprehensive overview of current state of science - Offers an integrated analysis of e-cigarettes and heated tobacco products - Provides guidance for methodologies
Bioinformatics in the Era of Post Genomics and Big Data
Bioinformatics has evolved significantly in the era of post genomics and big data. Huge advancements were made toward storing, handling, mining, comparing, extracting, clustering and analysis as well as visualization of big macromolecular data using novel computational approaches, machine and deep learning methods, and web-based server tools. There are extensively ongoing world-wide efforts to build the resources for regional hosting, organized and structured access and improving the pre-existing bioinformatics tools to efficiently and meaningfully analyze day-to-day increasing big data. This book intends to provide the reader with updates and progress on genomic data analysis, data modeling and network-based system tools.
Nutrition and Obsessive-Compulsive Disorder
Key features – Covers emerging therapeutic and nutritional approaches for the treatment and management of OCD Reviews the role of various micro-nutrients in OCD Discusses the prenatal genetic diagnosis and application of computational modelling in OCD Includes the nutritional and dietary roles in neuropsychiatric disorders like depression and obsessive-compulsive disorder (OCD) Explores the application of nano-biotechnology in OCD
Computational Methods in Systems Biology
This book constitutes the proceedings of the 11th International Conference on Computational Methods in Systems Biology, CMSB 2013, held in Klosterneuburg, Austria, in September 2013. The 15 regular papers included in this volume were carefully reviewed and selected from 27 submissions. They deal with computational models for all levels, from molecular and cellular, to organs and entire organisms.
Data Mining in Drug Discovery
Written for drug developers rather than computer scientists, this monograph adopts a systematic approach to mining scientifi c data sources, covering all key steps in rational drug discovery, from compound screening to lead compound selection and personalized medicine. Clearly divided into four sections, the first part discusses the different data sources available, both commercial and non-commercial, while the next section looks at the role and value of data mining in drug discovery. The third part compares the most common applications and strategies for polypharmacology, where data mining can substantially enhance the research effort. The final section of the book is devoted to systems biology approaches for compound testing. Throughout the book, industrial and academic drug discovery strategies are addressed, with contributors coming from both areas, enabling an informed decision on when and which data mining tools to use for one's own drug discovery project.
Applied Machine Learning Using mlr3 in R
mlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art machine learning capabilities in R. Applied Machine Learning Using mlr3 in R gives an overview of flexible and robust machine learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic machine learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of machine learning approaches to obtain peak performance; building machine learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with cu...
Network Bioscience, 2nd Edition
Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of 'big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being coll...
