Results 51 to 60 of about 154,546 (314)
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
Difference Frequency Gridless Sparse Array Processing
IEEE Open Journal of Signal ProcessingThis paper introduces a DOA estimation method for sources beyond the aliasing frequency. The method utilizes multiple frequencies of sources to exploit the frequency difference between them, enabling processing at a frequency below the aliasing frequency.
Yongsung Park, Peter Gerstoft
doaj +1 more source
SoftwareX, 2018 Compressive sensing is a computational framework for acquisition and processing of sparse signals at sampling rates below the rates mandated by the Nyquist sampling theorem.
Ervin Sejdić +2 more
doaj +1 more source
Knot Selection in Sparse Gaussian Processes
CoRR, 2020 Knot-based, sparse Gaussian processes have enjoyed considerable success as scalable approximations to full Gaussian processes. Problems can occur, however, when knot selection is done by optimizing the marginal likelihood. For example, the marginal likelihood surface is highly multimodal, which can cause suboptimal knot placement where some knots serve
Nathaniel Garton +2 more
openaire +2 more sources
Advances in the recovery of binary sparse signals [PDF]
, 2019 Recently, the recovery of binary sparse signals from compressed linear systems has received attention due to its several applications. In this contribution, we review the latest results in this framework, that are based on a suitable non-convex ...
Fosson
core
, 2012 (c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or ...
Emiya, Valentin +17 more
core +1 more source
Data aware sparse non-negative signal processing [PDF]
, 2022 Greedy techniques are a well established framework aiming to reconstruct signals which are sparse in some domain of representations. They are renowned for their relatively low computational cost, that makes them appealing from the perspective of real ...
Voulgaris, Konstantinos
core +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
Voxel selection in fMRI data analysis based on sparse representation [PDF]
, 2009 Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI)
Namburi, Praneeth +5 more
core +1 more source
Molecular Oncology, EarlyView.Here, we demonstrate that HS1BP3 interacts with Cortactin through a proline‐rich region (PRR3.1) and show that this interaction, and HS1BP3 itself, promote cancer cell proliferation and invasion. Inhibition of this interaction leads to build‐up of TKS5 in multivesicular endosomes and altered secretion of CD63 and CD9, providing an explanation for the ...
Arja Arnesen Løchen +9 more
wiley +1 more source