Search results for "RETRIEVAL"
showing 10 items of 1176 documents
Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics
2015
The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and dai…
Early Cognitive Training Rescues Remote Spatial Memory but Reduces Cognitive Flexibility in Alzheimer’s Disease Mice
2020
Background: Spatial memory dysfunction has been demonstrated in mouse models of Alzheimer’s disease (AD) which is consistent with the clinical finding that the early signature of AD includes difficulties in the formation and/or storage of a memory. A stored memory—a long term memory—can be modulated via process called as memory retrieval that can either lead toward memory reconsolidation or even memory extinction. Objective: We aim to shed light on the fate of the spatial memory during memory reactivation and memory extinction using a water maze task. Methods: In Set-up I, we trained 3-month-old mice (wild-type mice and mice with cerebral β-amyloidosis) and assessed the fate of remote memor…
Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research
2015
A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate glo…
RepeatsDB 2.0: improved annotation, classification, search and visualization of repeat protein structures
2017
RepeatsDB 2.0 (URL: http://repeatsdb.bio.unipd.it/) is an update of the database of annotated tandem repeat protein structures. Repeat proteins are a widespread class of non-globular proteins carrying heterogeneous functions involved in several diseases. Here we provide a new version of RepeatsDB with an improved classification schema including high quality annotations for ∼5400 protein structures. RepeatsDB 2.0 features information on start and end positions for the repeat regions and units for all entries. The extensive growth of repeat unit characterization was possible by applying the novel ReUPred annotation method over the entire Protein Data Bank, with data quality is guaranteed by a…
Variable Ranking Feature Selection for the Identification of Nucleosome Related Sequences
2018
Several recent works have shown that K-mer sequence representation of a DNA sequence can be used for classification or identification of nucleosome positioning related sequences. This representation can be computationally expensive when k grows, making the complexity in spaces of exponential dimension. This issue effects significantly the classification task computed by a general machine learning algorithm used for the purpose of sequence classification. In this paper, we investigate the advantage offered by the so-called Variable Ranking Feature Selection method to select the most informative k − mers associated to a set of DNA sequences, for the final purpose of nucleosome/linker classifi…
MetaCache: context-aware classification of metagenomic reads using minhashing.
2017
Abstract Motivation Metagenomic shotgun sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification, i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes corresponding software tools suffer from either long runtimes, large memory requirements or low accuracy. Results We introduce MetaCache—a novel software for read classification using the big data technique minhashing. Our…
Automatic time-lapse instrument is superior to single-point morphology observation for selecting viable embryos: retrospective study in oocyte donati…
2016
Objective To correlate the different categories provided by a commercial diagnostic test with blastocyst formation, quality, implantation potential, and ongoing pregnancy (OPR) for the purpose of validating the automatic annotations and the classification algorithm. Design Observational, retrospective, multicenter cohort study. Setting University-affiliated private IVF center. Patient(s) A total of 3,002 embryos, including 521 transferred embryos with known implantation, from 626 IVF cycles that were incubated in a conventional incubator and monitored with an automatic time-lapse test. Interventions(s) None. Main Outcome Measure(s) Embryo selection was based on morphology and the classifica…
Towards identifying drug side effects from social media using active learning and crowd sourcing.
2019
Motivation Social media is a largely untapped source of information on side effects of drugs. Twitter in particular is widely used to report on everyday events and personal ailments. However, labeling this noisy data is a difficult problem because labeled training data is sparse and automatic labeling is error-prone. Crowd sourcing can help in such a scenario to obtain more reliable labels, but is expensive in comparison because workers have to be paid. To remedy this, semi-supervised active learning may reduce the number of labeled data needed and focus the manual labeling process on important information. Results We extracted data from Twitter using the public API. We subsequently use Ama…
Author Correction: On the thermodynamic origin of metabolic scaling
2018
The origin and shape of metabolic scaling has been controversial since Kleiber found that basal metabolic rate of animals seemed to vary as a power law of their body mass with exponent 3/4, instead of 2/3, as a surface-to-volume argument predicts. The universality of exponent 3/4 -claimed in terms of the fractal properties of the nutrient network- has recently been challenged according to empirical evidence that observed a wealth of robust exponents deviating from 3/4. Here we present a conceptually simple thermodynamic framework, where the dependence of metabolic rate with body mass emerges from a trade-off between the energy dissipated as heat and the energy efficiently used by the organi…
ACTIVIDAD FÍSICA Y DISCAPACIDAD: UN ESTUDIO CUALITATIVO CON MUJERES EN UN GIMNASIO ADAPTADO
2017
Este estudio explora cómo un grupo de mujeres con discapacidad (n=6) experimentan y perciben la práctica de actividad física en un gimnasio adaptado. Se utilizaron entrevistas semi-estructuradas como instrumento de recogida de datos cualitativos y se realizó un análisis temático inductivo. Los resultados se agruparon en torno a cuatro categorías temáticas emergentes: condición física y autonomía personal; papel paliativo del ejercicio; bienestar psicológico; relación social y apoyo. Destaca la experiencia satisfactoria de las participantes, en la que predomina una valoración positiva de procesos autorregulativos, la concepción social-relacional de la actividad física, y la relevancia del gi…