Results 51 to 60 of about 180,123 (260)
Automatic detection of outliers is universally needed when working with scientific datasets, e.g., for cleaning datasets or flagging novel samples to guide instrument acquisition or scientific analysis.
Hannah R. Kerner +8 more
doaj +1 more source
Pharmacological inhibition of PERK in a DEN‐induced mouse model of liver cancer does not reduce tumor burden but alters cellular stress signaling. Despite blocking PERK activity, downstream stress responses, including CHOP expression, remain active, suggesting compensatory mechanisms within the unfolded protein response that may influence tumor ...
Ada Lerma‐Clavero +5 more
wiley +1 more source
A Comparison of Outlier Detection Techniques for High-Dimensional Data
Outlier detection is a hot topic in machine learning. With the newly emerging technologies and diverse applications, the interest of outlier detection is increasing greatly.
Xiaodan Xu +3 more
doaj +1 more source
CHAOS: Chart Analysis with Outlier Samples
Charts play a critical role in data analysis and visualization, yet real-world applications often present charts with challenging or noisy features. However, "outlier charts" pose a substantial challenge even for Multimodal Large Language Models (MLLMs), which can struggle to interpret perturbed charts.
Moured, O +6 more
openaire +2 more sources
In a murine model of myocardial ischemia and reperfusion (MI/R), the CD36 azapeptide ligand MPE‐298 reduces cardiac injury and transiently lowers left ventricular long‐chain fatty acids (LCFAs) accumulation 3 h after reperfusion, accompanied by a decrease of oxidative stress and inflammation‐associated genes' expression in the heart and adipose tissue.
Jade Gauvin +12 more
wiley +1 more source
Multi-Level Clustering-Based Outlier’s Detection (MCOD) Using Self-Organizing Maps
Outlier detection is critical in many business applications, as it recognizes unusual behaviours to prevent losses and optimize revenue. For example, illegitimate online transactions can be detected based on its pattern with outlier detection.
Menglu Li, Rasha Kashef, Ahmed Ibrahim
doaj +1 more source
The crystal structure of Borrelia burgdorferi nicotinamidase (PncA/BBE22) reveals the correct full‐length protein initiated from a non‐canonical AUU start codon. The structure validates previous biochemical findings and resolves a long‐standing annotation error, demonstrating that the truncated database sequence is structurally incompatible with the ...
Kalvis Brangulis
wiley +1 more source
Analysis and Detection in V-Formations with Outliers
RESUMEN: Una gran variedad de patrones de movimiento puede ser identificada cuando se estudia un conjunto de entidades móviles. Uno de estos patrones se denomina formación en V, ya que su forma se asemeja a dicha letra. Informalmente, un conjunto de entidades exhibe una formación en V si está ubicado en una de sus dos líneas características.
Moreno Arboleda, Francisco Javier +2 more
openaire +5 more sources
Transcripts enriched in codons that trigger P‐site tRNA‐mediated mRNA decay possess stable mRNA
PTMD codons were first described by Mendel et al. as mediators of an mRNA decay pathway dependent on the human protein CNOT3, homologous to yeast Not5. Our findings confirm that PTMD codons destabilize transcripts; however, unlike in yeast, the human pathway specifically targets and slightly destabilizes primarily stable mRNAs.
Rodolfo Lopes Carneiro +1 more
wiley +1 more source
An Outlier Detection Algorithm Based on Cross-Correlation Analysis for Time Series Dataset
Outlier detection is a very essential problem in a variety of application areas. Many detection methods are deficient for high-dimensional time series data sets containing both isolated and assembled outliers.
Hui Lu +3 more
doaj +1 more source

