Results 131 to 140 of about 19,696,345 (257)
Classification of Multifractal Time Series by Decision Tree Methods
, 2018 The article considers classification task of model fractal time series by the methods of machine learning. To classify the series, it is proposed to use the meta algorithms based on decision trees. To modeling the fractal time series, binomial stochastic
Радівілова, Т. А. +2 more
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Dual native G‐quadruplex folding is associated with chromatin looping at the MYC locus
FEBS Open Bio, EarlyView.BG4‐detectable G‐quadruplex (G4) in HaCaT and NHEK keratinocytes identified folded and unfolded G4s enriched at promoters/TSSs and active enhancers, whereas unfolded G4s also overlapped weak/poised enhancers. At MYC–PVT1, 3C‐qPCR detected enhancer–promoter looping only when G4s were simultaneously folded at both regulatory elements under native ...
Dieila Giomo de Lima +7 more
wiley +1 more source
FEBS Open Bio, EarlyView.Using peripheral blood for determining B‐cell or T‐cell clonality is more reliable when we use cell‐free RNA (cfRNA) because cells release blood significantly more RNA than DNA. Next‐generation sequencing (NGS) of cfRNA allows us to evaluate fragment cfRNA and evaluate clonality reliably without the need for prior determination of the specific dominant
Adam Albitar +11 more
wiley +1 more source
Time series classification with feature covariance matrices
, 2017 In this work, a novel approach utilizing feature covariance matrices is proposed for time series classification. In order to adapt the feature covariance matrices into time series classification problem, a feature vector is defined for each point in a ...
Ergezer, Hamza +4 more
core +1 more source
A minimal cellulosome‐like system in Cellulosilyticum lentocellum
FEBS Open Bio, EarlyView.Cellulose‐degrading bacteria typically use cellulosomes, large multi‐enzyme complexes on a scaffold protein. In Cellulosilyticum lentocellum, we characterise a far smaller arrangement, a single scaffold bound to one cellulase through a single cohesin‐dockerin interaction.
John Allan +2 more
wiley +1 more source
SCALE-BOSS-MR: Scalable Time Series Classification Using Multiple Symbolic Representations
Applied SciencesTime-Series-Classification (TSC) is an important machine learning task for many branches of science. Symbolic representations of time series, especially Symbolic Fourier Approximation (SFA), have been proven very effective for this task, given their ...
Apostolos Glenis, George A. Vouros
doaj +1 more source
ACTS: An Active Learning Method for Time Series Classification
, 2017 Active learning has been widely used to select the most informative data for labeling in classification tasks, except for time series classification. The main challenge of active learning in time series classification is to evaluate the informativeness ...
Qiong Luo +5 more
core +1 more source
FEBS Open Bio, EarlyView.A rapid visual test combines DNA amplification, CRISPR–based target verification, and a lateral flow strip to detect Streptococcus suis. The assay gives results in about 45 min, reduces false‐positive interpretation, and does not require fluorescence equipment.
Liu‐xin Li +7 more
wiley +1 more source
Composite Gramian Angular Field for Time-Series Classification
InformationGramian Angular Field (GAF) encodings transform time series into two-dimensional images suitable for convolutional neural network (CNN) classification. Existing applications typically use either the Gramian Angular Summation Field (GASF) or the Gramian ...
Pero Bogunović +2 more
doaj +1 more source
Comparative study on time series classification
, 2007 Time series classification or categorization is an important task in time-series analysis. Unlike traditional methods and problem formulations in time-series analysis, time series classification aims to take whole time sequences as input, and produce ...
Pan, Jia Lin +4 more
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