Results 41 to 50 of about 13,715 (249)
Entropy, 2023 Outlier detection is an important task in the field of data mining and a highly active area of research in machine learning. In industrial automation, datasets are often high-dimensional, meaning an effort to study all dimensions directly leads to data ...
Zihao Li, Liumei Zhang
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FEBS Letters, EarlyView.The pyruvate generator, which causes activation of respiration by extra‐mitochondrial Ca2+, is also present and functional in rat brainstem mitochondria, as it is in other brain regions. This finding is confirmed by experiments with a fully reconstituted malate–aspartate shuttle (MAS).
Grazyna Debska‐Vielhaber +7 more
wiley +1 more source
A Survey on Mixed-Attribute Outlier Detection Methods
CommIT Journal, 2019 In the data era, outlier detection methods play an important role. The existence of outliers can provide clues to the discovery of new things, irregularities in a system, or illegal intruders.
Nur Rokhman
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Benchmarking Outlier Detection Methods for Detecting IEM Patients in Untargeted Metabolomics Data
Metabolites, 2023 Untargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM).
Michiel Bongaerts +9 more
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Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers
Molecular Oncology, EarlyView.This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel +6 more
wiley +1 more source
Temporal and spatial outlier detection in wireless sensor networks
ETRI Journal, 2019 Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed ...
Hoc Thai Nguyen, Nguyen Huu Thai
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, 2022 When dealing with high-dimensional data, such as in biometric, e-commerce, or industrial applications, it is extremely hard to capture the abnormalities in full space due to the curse of dimensionality.
Lingling Li +15 more
core +1 more source
Molecular Oncology, EarlyView.Pre‐analytical handling critically determines liquid biopsy performance. This study defines practical best‐practice conditions for cell‐free DNA (cfDNA) and extracellular vesicle–derived DNA (evDNA), showing how processing time, storage conditions, tube type, and plasma input volume affect DNA integrity and mutation detection.
Jonas Dohmen +11 more
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Outlier Detection in Classification Analysis: An Overview [PDF]
The Egyptian Statistical Journal, 1993 Some of the techniques used for detecting multivariate outliers can be used for detecting outliers in classification analysis. However, detecting outliers in classification analysis is more complicated than in any other analysis since the impact of an ...
Ramses Sadek
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Molecular Oncology, EarlyView.We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source