Search results for "ARN"
showing 10 items of 8344 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…
Differential Classical Conditioning of the Nocebo Effect: Increasing Heat-Pain Perception without Verbal Suggestions
2017
Background: Nocebo effects, including nocebo hyperalgesia, are a common phenomenon in clinical routine with manifold negative consequences. Both explicit expectations and learning by conditioning are known to induce nocebo effects, but the specific role of conditioning remains unclear, because conditioning is rarely implemented independent of verbal suggestions. Further, although pain is a multidimensional phenomenon, nocebo effects are usually assessed in subjective ratings only, neglecting, e.g., behavioral aspects. The aim of this study was to test whether nocebo hyperalgesia can be learned by conditioning without explicit expectations, to assess nocebo effects in different response chan…
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…
Let the machine do the work: learning to reduce the energetic cost of walking on a split‐belt treadmill
2019
In everyday tasks such as walking and running, we often exploit the work performed by external sources to reduce effort. Recent research has focused on designing assistive devices capable of performing mechanical work to reduce the work performed by muscles and improve walking function. The success of these devices relies on the user learning to take advantage of this external assistance. Although adaptation is central to this process, the study of adaptation is often done using approaches that seem to have little in common with the use of external assistance. We show in 16 young, healthy participants that a common approach for studying adaptation, split-belt treadmill walking, can be under…
Forager age and foraging state, but not cumulative foraging activity, affect biogenic amine receptor gene expression in the honeybee mushroom bodies
2020
Foraging behavior is crucial for the development of a honeybee colony. Biogenic amines are key mediators of learning and the transition from in-hive tasks to foraging. Foragers vary considerably in their behavior, but whether and how this behavioral diversity depends on biogenic amines is not yet well understood. For example, forager age, cumulative foraging activity or foraging state may all be linked to biogenic amine signaling. Furthermore, expression levels may fluctuate depending on daytime. We tested if these intrinsic and extrinsic factors are linked to biogenic amine signaling by quantifying the expression of octopamine, dopamine and tyramine receptor genes in the mushroom bodies, i…
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 …
Improvement of In Vivo Expression of Genes Delivered by Self-Amplifying RNA Using Vaccinia Virus Immune Evasion Proteins.
2017
Among nucleic acid–based delivery platforms, self-amplifying RNA (saRNA) vectors are of increasing interest for applications such as transient expression of recombinant proteins and vaccination. saRNA is safe and, due to its capability to amplify intracellularly, high protein levels can be produced from even minute amounts of transfected templates. However, it is an obstacle to full exploitation of this platform that saRNA induces a strong innate host immune response. In transfected cells, pattern recognition receptors sense double-stranded RNA intermediates and via activation of protein kinase R (PKR) and interferon signaling initiate host defense measures including a translational shutdow…
Genetic counselling difficulties and ethical implications of incidental findings from array-CGH: a 7-year national survey
2016
Microarray-based comparative genomic hybridization (aCGH) is commonly used in diagnosing patients with intellectual disability (ID) with or without congenital malformation. Because aCGH interrogates with the whole genome, there is a risk of being confronted with incidental findings (IF). In order to anticipate the ethical issues of IF with the generalization of new genome-wide analysis technologies, we questioned French clinicians and cytogeneticists about the situations they have faced regarding IF from aCGH. Sixty-five IF were reported. Forty corresponded to autosomal dominant diseases with incomplete penetrance, 7 to autosomal dominant diseases with complete penetrance, 14 to X-linked di…
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…