Search results for "e learning"
showing 10 items of 2703 documents
Principal components analysis: theory and application to gene expression data analysis
2018
Advances in computational power have enabled research to generate significant amounts of data related to complex biological problems. Consequently, applying appropriate data analysis techniques has become paramount to tackle this complexity. However, theoretical understanding of statistical methods is necessary to ensure that the correct method is used and that sound inferences are made based on the analysis. In this article, we elaborate on the theory behind principal components analysis (PCA), which has become a favoured multivariate statistical tool in the field of omics-data analysis. We discuss the necessary prerequisites and steps to produce statistically valid results and provide gui…
Deep Learning Architectures for DNA Sequence Classification
2017
DNA sequence classification is a key task in a generic computational framework for biomedical data analysis, and in recent years several machine learning technique have been adopted to successful accomplish with this task. Anyway, the main difficulty behind the problem remains the feature selection process. Sequences do not have explicit features, and the commonly used representations introduce the main drawback of the high dimensionality. For sure, machine learning method devoted to supervised classification tasks are strongly dependent on the feature extraction step, and in order to build a good representation it is necessary to recognize and measure meaningful details of the items to cla…
A deeper look into natural sciences with physics-based and data-driven measures
2021
Summary With the development of machine learning in recent years, it is possible to glean much more information from an experimental data set to study matter. In this perspective, we discuss some state-of-the-art data-driven tools to analyze latent effects in data and explain their applicability in natural science, focusing on two recently introduced, physics-motivated computationally cheap tools—latent entropy and latent dimension. We exemplify their capabilities by applying them on several examples in the natural sciences and show that they reveal so far unobserved features such as, for example, a gradient in a magnetic measurement and a latent network of glymphatic channels from the mous…
Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes
2020
In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of …
Frailty Quantified by the "Valencia Score" as a Potential Predictor of Lifespan in Mice.
2017
The development of frailty scores suitable for mice and which resemble those used in the clinical scenario is of great importance to understand human frailty. The aim of the study was to determine an individual frailty score for each mouse at different ages and analyze the association between the frailty score and its lifespan. For this purpose, the "Valencia Score" for frailty was used. Thus, a longitudinal study in mice was performed analyzing weight loss, running time and speed, grip strength and motor coordination at the late-adult, mature and old ages (40, 56 and 80 weeks old, respectively). These parameters are equivalent to unintentional weight loss, poor endurance, slowness, weaknes…
Boosting Action Observation and Motor Imagery to Promote Plasticity and Learning
2018
Neural Plasticity, 2018
Adolescent and adult mice display differential sensitivity to the effects of bupropion on the acquisition of a water maze task.
2017
Abstract Background Adolescence is characterized by major neurobiological changes, and the effects of some psychoactive drugs seem to differ between adolescents and adults. Bupropion, an antidepressant that is also used to treat nicotine addiction, induces behavioral actions in both adolescent and adult rodents. However, the effects of this drug on spatial ability have not been compared in animals at different stages of their development. The present study was conducted to assess the effects of bupropion on spatial learning and memory in adolescent and adult mice. Methods Adolescent (post-natal day: PND35-36) and adult (PND >65) NMRI mice received bupropion (10, 20 and 40 mg/kg) or saline d…
The TrkB agonist 7,8-dihydroxyflavone changes the structural dynamics of neocortical pyramidal neurons and improves object recognition in mice
2018
This is a pre-print of an article published in Brain Structure and Function. The final authenticated version is available online at: https://doi.org/10.1007/s00429-018-1637-x. BDNF and its receptor TrkB have important roles in neurodevelopment, neural plasticity, learning, and memory. Alterations in TrkB expression have been described in different CNS disorders. Therefore, drugs interacting with TrkB, specially agonists, are promising therapeutic tools. Among them, the recently described 7,8-dihydroxyflavone (DHF), an orally bioactive compound, has been successfully tested in animal models of these diseases. Recent studies have shown the influence of this drug on the structure of pyramidal …
Temporal profiling of an acute stress-induced behavioral phenotype in mice and role of hippocampal DRR1.
2018
Abstract Understanding the neurobiological mechanisms underlying the response to an acute stressor may provide novel insights into successful stress-coping strategies. Acute behavioral stress-effects may be restricted to a specific time window early after stress-induction. However, existing behavioral test batteries typically span multiple days or even weeks, limiting the feasibility for a broad behavioral analysis following acute stress. Here, we designed a novel comprehensive behavioral test battery in male mice that assesses multiple behavioral dimensions within a sufficiently brief time window to capture acute stress-effects and its temporal profile. Using this battery, we investigated …
Predicting the spatial abundance of Ixodes ricinus ticks in southern Scandinavia using environmental and climatic data
2019
AbstractRecently, focus on tick-borne diseases has increased as ticks and their pathogens have become widespread and represent a health problem in Europe. Understanding the epidemiology of tick-borne infections requires the ability to predict and map tick abundance. We measured Ixodes ricinus abundance at 159 sites in southern Scandinavia from August-September, 2016. We used field data and environmental variables to develop predictive abundance models using machine learning algorithms, and also tested these models on 2017 data. Larva and nymph abundance models had relatively high predictive power (normalized RMSE from 0.65–0.69, R2 from 0.52–0.58) whereas adult tick models performed poorly …