Results 41 to 50 of about 28,509 (255)
Graph Regularized Variational Ladder Networks for Semi-Supervised Learning
IEEE Access, 2020 To tackle the problem of semi-supervised learning (SSL), we propose a new autoencoder-based deep model. Ladder networks (LN) is an autoencoder-based method for representation learning which has been successfully applied on unsupervised learning and semi ...
Cong Hu, Xiao-Ning Song
doaj +1 more source
Learning deformable shape manifolds [PDF]
Pattern Recognition, 2012 We propose an approach to shape detection of highly deformable shapes in images via manifold learning with regression. Our method does not require shape key points be defined at high contrast image regions, nor do we need an initial estimate of the shape. We only require sufficient representative training data and a rough initial estimate of the object
Samuel Rivera, Aleix M. Martínez
openaire +2 more sources
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Identification of the plant mitochondrial OrfX protein: A mass spectrometry approach
FEBS Letters, EarlyView.The mitochondrial genome of plants contains an open reading frame, orfx, which encodes a rare protein that has so far escaped mass spectrometric detection. The protein resembles the c‐subunit of bacterial twin‐arginine‐motif‐dependent protein translocases (TatC).
Matthias Döring +3 more
wiley +1 more source
Face manifold: manifold learning for synthetic face generation
Multimedia Tools and Applications, 2023 Face is one of the most important things for communication with the world around us. It also forms our identity and expressions. Estimating the face structure is a fundamental task in computer vision with applications in different areas such as face recognition and medical surgeries.
Kimia Dinashi +2 more
openaire +2 more sources
Interpreting the effects of DNA polymerase variants at the structural level
Molecular Oncology, EarlyView.Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi +7 more
wiley +1 more source
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Visualizing Energy Landscapes through Manifold Learning
Physical Review X, 2021 Energy landscapes provide a conceptual framework for structure prediction, and a detailed understanding of their topological features is necessary to develop efficient methods for their exploration.
Benjamin W. B. Shires +1 more
doaj +1 more source
Molecular Oncology, EarlyView.Many patients with urothelial cancer do not benefit from treatment with pembrolizumab, while at risk of severe side effects. Changes in the levels of circulating tumor DNA early during treatment, measured by a simple and affordable assay that can be easily implemented in the clinic, can be used as a prognostic tool to identify these patients.
Youssra Salhi +14 more
wiley +1 more source
Manifold learning in statistical tasks
Учёные записки Казанского университета: Серия Физико-математические науки, 2018 Many tasks of data analysis deal with high-dimensional data, and curse of dimensionality is an obstacle to the use of many methods for their solving.
A.V. Bernstein
doaj