Results 61 to 70 of about 258,865 (274)
Tumor mutational burden as a determinant of metastatic dissemination patterns
Molecular Oncology, EarlyView.This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal +4 more
wiley +1 more source
Contextual Outlier Interpretation
, 2018 Outlier detection plays an essential role in many data-driven applications to identify isolated instances that are different from the majority. While many statistical learning and data mining techniques have been used for developing more effective ...
Hu, Xia, Liu, Ninghao, Shin, Donghwa
core +1 more source
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
A Geometric Perspective on Functional Outlier Detection
Stats, 2021 We consider functional outlier detection from a geometric perspective, specifically: for functional datasets drawn from a functional manifold, which is defined by the data’s modes of variation in shape, translation, and phase.
Moritz Herrmann, Fabian Scheipl
doaj +1 more source
Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma
Molecular Oncology, EarlyView.Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra +6 more
wiley +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
wiley +1 more source
Adaptive threshold based outlier detection on IoT sensor data: A node-level perspective
Alexandria Engineering JournalThe accuracy and reliability of IoT-based sensor networks depend on validating sensed data, including detecting outliers at the node level. This study proposes an online outlier detection approach using Multiple Linear Regression-based adaptive ...
M. Veera Brahmam, S. Gopikrishnan
doaj +1 more source
EXTENDED APPLIED DATA CLEANING METHODS IN OUTLIER DETECTION FOR RESIDENTIAL CONSUMER [PDF]
Carpathian Journal of Electrical Engineering, 2023 This paper delves into the subject of outlier detection techniques tailored for unique datasets related to residential energy consumption. Building upon the current state of research we introduce the Grubbs and Z-score methods and investigate a range of ...
Dacian I. JURJ +7 more
doaj
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
A New Outlier Detection Model Using Random Walk on Local Information Graph
IEEE Access, 2018 Large number of outlier detection methods have emerged in recent years due to their importance in many real-world applications. The graph-based methods, which can effectively capture the inter-dependencies of related objects, is one of the most powerful ...
Chao Wang, Hui Gao, Zhen Liu, Yan Fu
doaj +1 more source