Search results for " Learning"
showing 10 items of 5299 documents
Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies
2016
Mieth, Bettina et al.
Partitioned learning of deep Boltzmann machines for SNP data.
2016
Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…
Model selection for factorial Gaussian graphical models with an application to dynamic regulatory networks.
2016
Abstract Factorial Gaussian graphical Models (fGGMs) have recently been proposed for inferring dynamic gene regulatory networks from genomic high-throughput data. In the search for true regulatory relationships amongst the vast space of possible networks, these models allow the imposition of certain restrictions on the dynamic nature of these relationships, such as Markov dependencies of low order – some entries of the precision matrix are a priori zeros – or equal dependency strengths across time lags – some entries of the precision matrix are assumed to be equal. The precision matrix is then estimated by l 1-penalized maximum likelihood, imposing a further constraint on the absolute value…
Neurons in the pigeon caudolateral nidopallium differentiate Pavlovian conditioned stimuli but not their associated reward value in a sign-tracking p…
2016
AbstractAnimals exploit visual information to identify objects, form stimulus-reward associations, and prepare appropriate behavioral responses. The nidopallium caudolaterale (NCL), an associative region of the avian endbrain, contains neurons exhibiting prominent response modulation during presentation of reward-predicting visual stimuli, but it is unclear whether neural activity represents valuation signals, stimulus properties, or sensorimotor contingencies. To test the hypothesis that NCL neurons represent stimulus value, we subjected pigeons to a Pavlovian sign-tracking paradigm in which visual cues predicted rewards differing in magnitude (large vs. small) and delay to presentation (s…
Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs
2017
Detecting higher-order epistatic interactions in Genome-Wide Association Studies (GWAS) remains a challenging task in the fields of genetic epidemiology and computer science. A number of algorithms have recently been proposed for epistasis discovery. However, they suffer from a high computational cost since statistical measures have to be evaluated for each possible combination of markers. Hence, many algorithms use additional filtering stages discarding potentially non-interacting markers in order to reduce the overall number of combinations to be examined. Among others, Mutual Information Clustering (MIC) is a common pre-processing filter for grouping markers into partitions using K-Means…
Deep learning models for bacteria taxonomic classification of metagenomic data.
2018
Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…
Anti-inflammatory and cognitive effects of interferon-β1a (IFNβ1a) in a rat model of Alzheimer’s disease
2018
Background: Aβ 1-42 peptide abnormal production is associated with the development and maintenance of neuroinflammation and oxidative stress in brains from Alzheimer disease (AD) patients. Suppression of neuroinflammation may then represent a suitable therapeutic target in AD. We evaluated the efficacy of IFNβ1a in attenuating cognitive impairment and inflammation in an animal model of AD. Methods: A rat model of AD was obtained by intra-hippocampal injection of Aβ 1-42 peptide (23 μg/2 μl). After 6 days, 3.6 μg of IFNβ1a was given subcutaneously (s.c.) for 12 days. Using the novel object recognition (NOR) test, we evaluated changes in cognitive function. Measurement of pro-inflammatory or …
Negative transfer effects between reference memory and working memory training in the water maze in C57BL/6 mice
2017
The water maze is one of the most widely employed spatial learning paradigms in the cognitive profiling of genetically modified mice. Oftentimes, tests of reference memory (RM) and working memory (WM) in the water maze are sequentially evaluated in the same animals. However, critical difference in the rules governing efficient escape from the water between WM and RM tests is expected to promote the adoption of incompatible mnemonic or navigational strategies. Hence, performance in a given test is likely poorer if it follows the other test instead of being conducted first. Yet, the presence of such negative transfer effects (or proactive interference) between WM and RM training in the water …
A new “sudden fright paradigm” to explore the role of (epi)genetic modulations of the DAT gene in fear-induced avoidance behavior
2020
Alterations in dopamine (DA) reuptake are involved in several psychiatric disorders whose symptoms can be investigated in knock out rats for the DA transporter (DAT-KO). Recent studies evidenced the role of epigenetic DAT modulation in depressive-like behavior. Accordingly, we used heterozygous (HET) rats born from both HET parents (termed MIX-HET), compared to HET rats born from WT-mother and KO-father (MAT-HET), implementing the role of maternal care on DAT modulation. We developed a "sudden fright" paradigm (based on dark-light test) to study reaction to fearful inputs in the DAT-KO, MAT-HET, MIX-HET, and WT groups. Rats could freely explore the whole 3-chambers apparatus; then, they wer…
Barrel cortex: What is it good for?
2017
The rodent whisker system, with barrel cortex as its most prominent structure, has evolved into a powerful model system to study sensory processing. However, despite the vast amount of data collected on barrel cortex neural activity patterns, as well as its circuitry and plasticity, the precise behavioral and cognitive operations for which this structure is needed are still elusive. Proposed functions of barrel cortex include detection, discrimination, coordination of whisker movements during exploratory locomotion or active touch, and associative learning. Departing from a definition of what exactly constitutes a function and how the involvement of a brain area in a specific task can be es…