Results 61 to 70 of about 747,976 (285)

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

open access: yesMolecular 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

Human–Object Interaction: Development of a Usability Index for Product Design Using a Hierarchical Fuzzy Axiomatic Design

open access: yesComputation
Consumer product usability has been addressed using tools that evaluate objects to improve user interaction. However, such diversity in approach makes it challenging to select a method for the type of product being assessed.
Mayra Ivette Peña-Ontiveros   +5 more
doaj   +1 more source

Non-linear Learning for Statistical Machine Translation

open access: yes, 2015
Modern statistical machine translation (SMT) systems usually use a linear combination of features to model the quality of each translation hypothesis. The linear combination assumes that all the features are in a linear relationship and constrains that ...
Chen, Huadong   +3 more
core   +1 more source

Transcriptional profiling of circulating extracellular vesicles from prebiopsy prostate cancer patients

open access: yesMolecular Oncology, EarlyView.
RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner   +14 more
wiley   +1 more source

Dynamically rescaled Hamiltonian Monte Carlo for Bayesian Hierarchical Models

open access: yes, 2018
Dynamically rescaled Hamiltonian Monte Carlo (DRHMC) is introduced as a computationally fast and easily implemented method for performing full Bayesian analysis in hierarchical statistical models.
Kleppe, Tore Selland
core   +1 more source

Tumor‐stromal crosstalk and macrophage enrichment are associated with chemotherapy response in bladder cancer

open access: yesFEBS Open Bio, EarlyView.
Chemoresistance in bladder cancer: Macrophage recruitment associated with CXCL1, CXCL5 and CXCL8 expression is characteristic of Gemcitabine/Cisplatin (Gem/Cis) Non‐Responder tumors (right side) while Responder tumors did not show substantial tumor‐stromal crosstalk (left side). All biological icons are attributed to Bioicons: carcinoma, cancerous‐cell‐
Sophie Leypold   +11 more
wiley   +1 more source

Multi‐omics and low‐input proteomics profiling reveals dynamic regulation driving pluripotency initiation in early mouse embryos

open access: yesFEBS Open Bio, EarlyView.
Mouse pre‐implantation development involves a transition from totipotency to pluripotency. Integrating transcriptomics, epigenetic profiling, low‐input proteomics and functional assays, we show that eight‐cell embryos retain residual totipotency features, whereas cytoskeletal remodeling regulated by the ubiquitin‐proteasome system drives progression ...
Wanqiong Li   +8 more
wiley   +1 more source

A Common Platform for Graphical Models in R: The gRbase Package

open access: yesJournal of Statistical Software, 2005
The gRbase package is intended to set the framework for computer packages for data analysis using graphical models. The gRbase package is developed for the open source language, R, and is available for several platforms.
Claus Dethlefsen, Søren Højsgaard
doaj  

Chiral non-linear sigma-models as models for topological superconductivity

open access: yes, 2000
We study the mechanism of topological superconductivity in a hierarchical chain of chiral non-linear sigma-models (models of current algebra) in one, two, and three spatial dimensions. The models have roots in the 1D Peierls-Frohlich model and illustrate
A. Fetter   +25 more
core   +1 more source

Meta‐analysis fails to show any correlation between protein abundance and ubiquitination changes

open access: yesFEBS Open Bio, EarlyView.
We analyzed over 50 published proteomics datasets to explore the relationship between protein levels and ubiquitination changes across multiple experimental conditions and biological systems. Although ubiquitination is often associated with protein degradation, our analysis shows that changes in ubiquitination do not globally correlate with changes in ...
Nerea Osinalde   +3 more
wiley   +1 more source

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