Results 61 to 70 of about 379,758 (236)
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
Dimensionality reduction with subgaussian matrices: a unified theory [PDF]
, 2014 We present a theory for Euclidean dimensionality reduction with subgaussian matrices which unifies several restricted isometry property and Johnson-Lindenstrauss type results obtained earlier for specific data sets.
Dirksen, Sjoerd
core
Molecular Oncology, EarlyView.This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns +10 more
wiley +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
Two-Stage Dimensionality Reduction for Social Media Engagement Classification
Applied SciencesThe high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will ...
Jose Luis Vieira Sobrinho +2 more
doaj +1 more source
Using Dimensionality Reduction to Analyze Protein Trajectories
Frontiers in Molecular Biosciences, 2019 In recent years the analysis of molecular dynamics trajectories using dimensionality reduction algorithms has become commonplace. These algorithms seek to find a low-dimensional representation of a trajectory that is, according to a well-defined ...
Gareth A. Tribello, Piero Gasparotto
doaj +1 more source
The Shape and Dimensionality of Phylogenetic Tree-Space Based on Mitochondrial Genomes [PDF]
, 2010 Phylogenetic analyses of large and diverse data sets generally result in large sets of competing phylogenetic trees. Consensus tree methods used to summarize sets of competing trees discard important information regarding the similarity and distribution ...
James C. Wilgenbusch +2 more
core +1 more source
Molecular Oncology, EarlyView.Dimethyl fumarate (DMF) reduces growth of HPV‐positive cervical cancer spheroids and induces ferroptosis in cervical cancer cells via blocking SLC7A11/Glutathione (GSH) axis. Combination of subcytotoxic doses of DMF and cisplatin (CDDP) further suppresses spheroid growth and drives cell death in 2D culture models.
Carolina Punziano +6 more
wiley +1 more source
Molecular Oncology, EarlyView.Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
wiley +1 more source
Optimal Dimensionality Reduction using Conditional Variational AutoEncoder
Transactions on Cryptographic Hardware and Embedded SystemsThe benefits of using Deep Learning techniques to enhance side-channel attacks performances have been demonstrated over recent years. Most of the work carried out since then focuses on discriminative models.
Sana Boussam +4 more
doaj +1 more source