Results 81 to 90 of about 17,677 (287)

A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data

Frontiers in Genetics, 2023
Early diagnosis and treatment of glaucoma are challenging. The discovery of glaucoma biomarkers based on gene expression data could potentially provide new insights for early diagnosis, monitoring, and treatment options of glaucoma.
Xiaoqin Huang, Akhilesh K. Bajpai, Jian Sun, Fuyi Xu, Fuyi Xu, Lu Lu, Lu Lu, Siamak Yousefi, Siamak Yousefi   +8 more
doaj   +1 more source

Use of Cluster Analysis for Identifying Metafounders. [PDF]

J Anim Breed Genet
ABSTRACT In the metafounder approach, the relationship matrix of metafounders, Γ is used to transfer information on relationships between pedigree founders into the numerator relationship matrix A, creating matrix AΓ. Commonly metafounders are defined based on the available information of the animal (e.g., country, sex, breed) similar to unknown parent
Anglhuber C, Edel C, Pimentel ECG, Emmerling R, Götz KU, Thaller G.   +5 more
europepmc   +2 more sources

Enhanced Topic Modeling for Textual Data Supervisor: Professor Tomaso Erseghe tomaso.erseghe@unipd.it

, 2023
openIn this thesis, we present an innovative approach for topic modeling and text classification using a combination of Non-Negative Matrix Factorization (NMF), Variational Autoencoder (VAE), and Bidirectional Long Short-Term Memory (Bi-LSTM) models. Our
JAVIDFAR, MASOUD
core  

Single‐Cell RNA Editing Identifies T Cell ADAR1 as a Key Regulator of Immune Exhaustion and Anti‐PD‐1 Resistance in Colorectal Cancer

Advanced Science, EarlyView.
Single‐cell RNA editing analysis identifies ADAR1 as a regulator of dysfunctional T cell states in colorectal cancer. Elevated ADAR1 activity promotes T cell exhaustion and impairs antitumor immunity partly through TGF‐β‐SMAD signaling, contributing to anti‐PD‐1 resistance and highlighting T cell ADAR1 as a potential therapeutic target and biomarker ...
Da Kang, Song‐Zuo Xie, Yong‐Zhou Luo, Xin‐Pei Deng, Xi‐Rong Tan, Ze‐Geng Chen, Ling‐Xing Zeng, Gong Chen, Pei‐Rong Ding, Zhi‐Zhong Pan, Rong‐Xin Zhang   +10 more
wiley   +1 more source

A framework for regularized non-negative matrix factorization, with application to the analysis of gene expression data.

PLoS ONE, 2012
Non-negative matrix factorization (NMF) condenses high-dimensional data into lower-dimensional models subject to the requirement that data can only be added, never subtracted.
Leo Taslaman, Björn Nilsson
doaj   +1 more source

Accurate image derived input function in [18F]SynVesT-1 mouse studies using isoflurane and ketamine/xylazine anesthesia

EJNMMI Physics, 2023
Background Kinetic modeling in positron emission tomography (PET) requires measurement of the tracer plasma activity in the absence of a suitable reference region.
Alan Miranda, Daniele Bertoglio, Steven Staelens, Jeroen Verhaeghe   +3 more
doaj   +1 more source

Data-Driven Characterization of Knee Structures Using Non-Negative Matrix Factorization of 3D Multi-Echo UTE MRI. [PDF]

NMR Biomed
Non‐negative matrix factorization (NMF) can derive tissue features in a data‐driven manner without relying on biophysical model assumptions. First‐time application of NMF to 3D multi‐echo UTE knee MRI revealed four reproducible components associated with tissues of fast and slow transverse relaxation, water–fat mixture (chemical shift), and fat tissue.
Smekens C, Van Dyck P, Fuchs PS, Sijbers J, Janssens T, Jeurissen B.   +5 more
europepmc   +2 more sources

Clustering with NMF.

, 2022
(A) High gamma responses averaged across electrodes in the 2 clusters provided by the unsupervised NMF. Shaded regions indicate SEM over trials. (B) Spatial distribution on cortex of electrodes in the 2 clusters displayed on the left hemisphere of a ...
Adeen Flinker (185852), Werner Doyle (12041857), Orrin Devinsky (356636), Muge Ozker (12041854)   +3 more
core   +1 more source

Advancing the Design of High‐Efficiency Printable Hole‐Conductor‐Free Mesoscopic Perovskite Solar Cells Through Machine Learning

Advanced Science, EarlyView.
Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng, Jingzi Zhang, Xu Zhu, Yuelin Wang, Antai Yang, Kailong Hu, Chengquan Zhong, Jiakai Liu, Menghan Dun, Xi Lin   +9 more
wiley   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source