Results 61 to 70 of about 53,985 (263)
Molecular Oncology, EarlyView.Nanosecond infrared laser (NIRL) low‐volume sampling combined with shotgun lipidomics uncovers distinct lipidome alterations in oropharyngeal squamous cell carcinoma (OPSCC) of the palatine tonsil. Several lipid species consistently differentiate tumor from healthy tissue, highlighting their potential as diagnostic markers.
Leonard Kerkhoff +11 more
wiley +1 more source
Sasakian Statistical Manifolds with Semi-Symmetric Metric Connection
Universal Journal of Mathematics and Applications, 2018 In the present paper, firstly we express the relation between the semi-symmetric metric connection $\tilde{\nabla}$ and the torsion-free connection $\nabla$ and obtain the relation between the curvature tensors $\tilde{R}$ of $\tilde{\nabla}$ and $R$ of $
Ahmet Kazan, Sema Kazan
doaj +1 more source
Generalization of the maximum entropy principle for curved statistical manifolds
Physical Review Research, 2021 The maximum entropy principle (MEP) is one of the most prominent methods to investigate and model complex systems. Despite its popularity, the standard form of the MEP can only generate Boltzmann-Gibbs distributions, which are ill-suited for many ...
Pablo A. Morales, Fernando E. Rosas
doaj +1 more source
, 2007 A new information-geometric approach to chaotic dynamics on curved statistical manifolds based on Entropic Dynamics (ED) is proposed. It is shown that the hyperbolicity of a non-maximally symmetric 6N-dimensional statistical manifold M_{s} underlying an ...
A. Caticha +29 more
core +2 more sources
Molecular Oncology, EarlyView.We show that the majority of the 18 analyzed recurrent cancer‐associated ERBB4 mutations are transforming. The most potent mutations are activating, co‐operate with other ERBB receptors, and are sensitive to pan‐ERBB inhibitors. Activating ERBB4 mutations also promote therapy resistance in EGFR‐mutant lung cancer.
Veera K. Ojala +15 more
wiley +1 more source
Deep Domain Adaptation Using Cascaded Learning Networks and Metric Learning
IEEE Access, 2023 How can we bridge efficiently distribution difference between the source and target domains in an isomorphic latent feature space by using metric learning. This study introduces metric learning on manifolds which combine a cascaded learning network and a
Zhiyong Zeng, Dawei Li, Xiujuan Yang
doaj +1 more source
, 2014 We consider the statistical analysis of trajectories on Riemannian manifolds that are observed under arbitrary temporal evolutions. Past methods rely on cross-sectional analysis, with the given temporal registration, and consequently may lose the mean ...
Klassen, Eric +3 more
core +1 more source
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
پژوهشهای ریاضی, 2021 In this paper, in the first part, the affine geometry is assumed as the main framework. Then we have a spacious explanation of necessary introduction in rather different subjects.
Azam Etemad Dehkordy
doaj
Learning gradients on manifolds
, 2010 A common belief in high-dimensional data analysis is that data are concentrated on a low-dimensional manifold. This motivates simultaneous dimension reduction and regression on manifolds.
Mukherjee, Sayan +2 more
core +1 more source