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Quantitative Assessment and Validation of Network Inference Methods in Bioinformatics

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889194780 Year: Pages: 191 DOI: 10.3389/978-2-88919-478-0 Language: English
Publisher: Frontiers Media SA
Subject: Biotechnology --- General and Civil Engineering --- Genetics --- Science (General)
Added to DOAB on : 2016-03-10 08:14:33
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Scientists today have access to an unprecedented arsenal of high-tech tools that can be used to thoroughly characterize biological systems of interest. High-throughput “omics” technologies enable to generate enormous quantities of data at the DNA, RNA, epigenetic and proteomic levels. One of the major challenges of the post-genomic era is to extract functional information by integrating such heterogeneous high-throughput genomic data. This is not a trivial task as we are increasingly coming to understand that it is not individual genes, but rather biological pathways and networks that drive an organism’s response to environmental factors and the development of its particular phenotype. In order to fully understand the way in which these networks interact (or fail to do so) in specific states (disease for instance), we must learn both, the structure of the underlying networks and the rules that govern their behavior. In recent years there has been an increasing interest in methods that aim to infer biological networks. These methods enable the opportunity for better understanding the interactions between genomic features and the overall structure and behavior of the underlying networks. So far, such network models have been mainly used to identify and validate new interactions between genes of interest. But ultimately, one could use these networks to predict large-scale effects of perturbations, such as treatment by multiple targeted drugs. However, currently, we are still at an early stage of comprehending methods and approaches providing a robust statistical framework to quantitatively assess the quality of network inference and its predictive potential. The scope of this Research Topic in Bioinformatics and Computational Biology aims at addressing these issues by investigating the various, complementary approaches to quantify the quality of network models. These “validation” techniques could focus on assessing quality of specific interactions, global and local structures, and predictive ability of network models. These methods could rely exclusively on in silico evaluation procedures or they could be coupled with novel experimental designs to generate the biological data necessary to properly validate inferred networks.

Biomarkers of Alzheimer's Disease: The Present and the Future

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889450411 Year: Pages: 218 DOI: 10.3389/978-2-88945-041-1 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2018-02-27 16:16:44
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Alzheimer disease (AD) is a neurodegenerative disorder characterized by significant cognitive deficits, behavioral changes, sleep disorders and loss of functional autonomy. AD represents the main cause of dementia and has become a major public health issue. In addition, the number of patients suffering from AD is growing rapidly as the population ages worldwide. Memory impairment is usually the earliest clinical and core symptom of this disease. The diagnosis at a late clinical stage is relatively easy. However, a delay in the diagnosis is damageable for the handling of patients in terms of optimal medical and social care. The actual interest of the scientific head-ways is to optimize the diagnosis in prodromal stage of the disease and to propose personalized therapeutic solutions to individual patients. New revised AD diagnostic criteria include early alteration of cerebrospinal fluid (CSF) biomarkers: decrease of amyloïd peptides (Aß42), and increase in tau and phosphorylated-tau (p-tau) protein concentration. This recognition of CSF biological biomarkers for the diagnosis of AD is a major step towards the “molecular” diagnosis and follow-up of the disease. Many issues are however still subject of debate. This e-book provides a comprehensive overview of the state of the art of fluid biomarkers for AD, e.g. which novel biomarkers should be implemented in clinical practice for diagnosis or for monitoring treatment or side effects, which ones are new for AD or related dementias or what is the potential of peripheral blood markers. Moreover, the e-Book provides practical guidelines how to optimally and efficiently develop and validate novel biomarker assays, and to document and control pre-analytical variation.

The Role of Play in Child Assessment and Intervention

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889452590 Year: Pages: 150 DOI: 10.3389/978-2-88945-259-0 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Psychology
Added to DOAB on : 2018-02-27 16:16:44
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Play is a ubiquitous and universal aspect of early childhood. Although it may take different forms throughout development and across cultures, decades of research have found play to be related to important, positive outcomes. Play provides children with valuable cognitive, emotional, and interpersonal learning opportunities. It can act as a mode of communication for young children and allows them to practice ways of managing complex interpersonal interactions. Specific aspects of play, such as children’s creativity in pretend play, have been associated with resilience and coping. The significance of play in childhood has led to its frequent use in the assessment of child development and in the implementation of child and parent-child psychological and educational interventions. Historically, however, the validity and efficacy of these interventions have not been rigorously evaluated. Further, few assessment and intervention models have included parents, teachers, and other key caregivers, but have focused only on the child. This Research Topic will bring together the most current literature on the use of play in child assessment and intervention.

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