Results 81 to 90 of about 1,077,907 (260)
Efficient algorithm for testing goodness-of-fit for classification of high dimensional data
Lietuvos Matematikos Rinkinys, 2009 Let us have a sample satisfying d-dimensional Gaussian mixture model (d is supposed to be large). The problem of classification of the sample is considered. Because of large dimension it is natural to project the sample to k-dimensional (k = 1, 2, . . .)
Gintautas Jakimauskas
doaj +1 more source
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
Feature Selection for High Dimensional Data Using Monte Carlo Tree Search
IEEE Access, 2018 Feature selection is the preliminary step in machine learning and data mining. It identifies the most important and relevant features within a dataset by eliminating the redundant or irrelevant features.
Muhammad Umar Chaudhry, Jee-Hyong Lee
doaj +1 more source
Molecular Oncology, EarlyView.To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source
Molecular Oncology, EarlyView.Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley +5 more
wiley +1 more source
Clustering Evaluation in High-Dimensional Data [PDF]
, 2016 Clustering evaluation plays an important role in unsupervised learning systems, as it is often necessary to automatically quantify the quality of generated cluster configurations. This is especially useful for comparing the performance of different clustering algorithms as well as determining the optimal number of clusters in clustering algorithms that
Nenad Tomašev, Miloš Radovanović
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RIPK4 function interferes with melanoma cell adhesion and metastasis
Molecular Oncology, EarlyView.RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski +9 more
wiley +1 more source
Homologous expression and purification of human HAX‐1 for structural studies
FEBS Open Bio, EarlyView.This research protocol provides detailed instructions for cloning, expressing, and purifying large quantities of the intrinsically disordered human HAX‐1 protein, N‐terminally fused to a cleavable superfolder GFP, from mammalian cells. HAX‐1 is predicted to undergo posttranslational modifications and to interact with membranes, various cellular ...
Mariana Grieben
wiley +1 more source
Overview of molecular signatures of senescence and associated resources: pros and cons
FEBS Open Bio, EarlyView.Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas +6 more
wiley +1 more source