Results 61 to 70 of about 1,216,046 (262)
Stable ant‐antlion optimiser for feature selection on high‐dimensional data
High‐dimensional data exists widely in the real world, such as gene, magnetic resonance imaging (MRI), text, web data and so on. Feature selection is an effective and powerful method that is often adopted to reduce dimensions of high‐dimensional data for
Mengmeng Li +5 more
doaj +1 more source
Epigenetic reprogramming of lineage switching in cancer
Cancer cells rarely commit to a single identity. Epigenetic mechanisms and tumor microenvironment cues push epithelial cells toward flexible, hybrid states that can shift into mesenchymal, neuroendocrine, or stem‐like fates, driving metastasis, drug resistance, and tumor heterogeneity. Targeting the epigenetic regulators behind these transitions, using
Ezgi Boyvatlı +4 more
wiley +1 more source
Probabilistic classifiers with high-dimensional data [PDF]
For medical classification problems, it is often desirable to have a probability associated with each class. Probabilistic classifiers have received relatively little attention for small n large p classification problems despite of their importance in medical decision making.
Kyung In, Kim, Richard, Simon
openaire +2 more sources
A network approach for low dimensional signatures from high throughput data
One of the main objectives of high-throughput genomics studies is to obtain a low-dimensional set of observables—a signature—for sample classification purposes (diagnosis, prognosis, stratification).
Nico Curti +4 more
doaj +1 more source
This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
Fitting High-Dimensional Copulae to Data [PDF]
This paper make an overview of the copula theory from a practical side. We consider different methods of copula estimation and different Goodness-of-Fit tests for model selection. In the GoF section we apply Kolmogorov-Smirnov and Cramer-von-Mises type tests and calculate power of these tests under different assumptions.
openaire +4 more sources
This paper provides a brief introduction to high-dimensional data, a form of ‘Big Data’, and gives an overview of several data analysis concepts and techniques that could be used to explore and analyse such data. An example that involves genomics data from several Sri Lankan and United Kingdom oral cancer patients is used to illustrate the methods.
Dhammika Amaratunga, Javier Cabrera
openaire +2 more sources
K-means clustering based filter feature selection on high dimensional data
With hundreds or thousands of features in high dimensional data, computational workload is challenging. In classification process, features which do not contribute significantly to prediction of classes, add to the computational workload.
Dewi Pramudi Ismi +2 more
doaj +1 more source
Obesity raises blood levels of PAI‐1, a protein linked to metabolic dysfunction‐associated steatotic liver disease in people with obesity. In female mice fed a high‐fat diet, partially lowering PAI‐1 led to smaller subcutaneous fat cells and lower liver cholesterol, without changing body weight or insulin sensitivity.
Claudia E. Ramirez Bustamante +10 more
wiley +1 more source
Emerging experimental and computational methods for studying redox‐regulated structural transitions
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source

