Results 51 to 60 of about 28,509 (255)

Liquid biopsy‐based diagnostic evaluation of hypermethylated CpG sites for ovarian cancer diagnosis

Molecular Oncology, EarlyView.
This schematic outlines the workflow from biomarker identification to duplex MethyLight assay validation for epithelial ovarian cancer diagnosis using cfDNA‐based liquid biopsy. Initial screening of hypermethylated CpG candidates (cg02957270, cg10061138 cg00480298, COL2A1) was performed in tissue using ARMS‐PCR, COBRA, qPCR and image analysis. Selected
Deepa Bisht, Sameer Gupta, Amrita Chaurasia, Manisha Sachan   +3 more
wiley   +1 more source

Manifold learning based on kernel density estimation

Учёные записки Казанского университета: Серия Физико-математические науки, 2018
The problem of unknown high-dimensional density estimation has been considered. It has been suggested that the support of its measure is a low-dimensional data manifold. This problem arises in many data mining tasks.
A.P. Kuleshov, A.V. Bernstein, Yu.A. Yanovich   +2 more
doaj  

Review on graph learning for dimensionality reduction of hyperspectral image

Geo-spatial Information Science, 2020
Graph learning is an effective manner to analyze the intrinsic properties of data. It has been widely used in the fields of dimensionality reduction and classification for data. In this paper, we focus on the graph learning-based dimensionality reduction
Liangpei Zhang, Fulin Luo
doaj   +1 more source

An Optimization Technique for Linear Manifold Learning-Based Dimensionality Reduction: Evaluations on Hyperspectral Images

Applied Sciences, 2021
Manifold learning tries to find low-dimensional manifolds on high-dimensional data. It is useful to omit redundant data from input. Linear manifold learning algorithms have applicability for out-of-sample data, in which they are fast and practical ...
Ümit Öztürk, Atınç Yılmaz
doaj   +1 more source

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

Molecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source

Diversity Multi-View Clustering With Subspace and NMF-Based Manifold Learning

IEEE Access, 2023
Since the complementarity information among multiple views has been exploited to improve the clustering effect significantly, multi-view clustering has become a hot topic, and many multi-view clustering methods have emerged.
Jiaman Ding, Xiaojiang Fang, Lianyin Jia, Ying Jiang, Runxin Li   +4 more
doaj   +1 more source

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

Recovering manifold representations via unsupervised meta-learning

Frontiers in Computer Science
Manifold representation learning holds great promise for theoretical understanding and characterization of deep neural networks' behaviors through the lens of geometries.
Yunye Gong, Jiachen Yao, Ruyi Lian, Xiao Lin, Chao Chen, Ajay Divakaran, Yi Yao   +6 more
doaj   +1 more source

Dictionary-based Manifold Learning

CoRR, 2023
We propose a paradigm for interpretable Manifold Learning for scientific data analysis, whereby we parametrize a manifold with $d$ smooth functions from a scientist-provided dictionary of meaningful, domain-related functions. When such a parametrization exists, we provide an algorithm for finding it based on sparse non-linear regression in the manifold
Hanyu Zhang, Samson J. Koelle, Marina Meila   +2 more
openaire   +2 more sources

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source