Results 251 to 260 of about 5,853,511 (292)

Single‐Cell Profiling Across Immune Tissues and Organs Reveals Immunosenescence Signatures in Male Rhesus Monkeys

Advanced Science, EarlyView.
Single‐cell profiling across bone marrow, spleen, mesenteric lymph, and blood in rhesus monkeys reveals organ Immunosenescence. GZMB rises with age, particularly in cytotoxic and terminally exhausted CD8+ T cells, and BHLHE40 emerges as a key transcription factor enriched across multiple CD8+ subsets, regulating pro‐inflammatory and exhaustion‐related ...
Shengnan Wang, Zhengna Zhu, Hongju Yang, Yaping Yan, Luyao Ran, Naixue Yang, Yichao Wang, Li Wu, Bing Bai, Weizhi Ji, Wei Si   +10 more
wiley   +1 more source

scPER: A Rigorous Computational Approach to Determine Cellular Subtypes in Tumors Aligned With Cancer Phenotypes From Total RNA Sequencing

Advanced Science, EarlyView.
scPER presents an adversarial‐autoencoder framework that deconvolves bulk total RNA‐seq to quantify tumor‐microenvironment cell types and uncover phenotype‐linked subclusters. Across diverse benchmarks, scPER improves accuracy over existing tools.
Bingrui Li, Xiaobo Zhou, Raghu Kalluri
wiley   +1 more source

Active Force Dynamics in Red Blood Cells Under Non‐Invasive Optical Tweezers

Advanced Science, EarlyView.
A non‐invasive method combines low‐power optical tweezers with high‐speed microscopy to simultaneously monitor local membrane forces and displacements in single human red blood cells. This dual‐channel approach reveals a mechano‐dynamic signature that correlates the cell's metabolic state with its mechanical activity. This energetic framework serves as
Arnau Dorn, Clara Luque‐Rioja, Macarena Calero, Diego Herráez‐Aguilar, Francisco Monroy, Niccolò Caselli   +5 more
wiley   +1 more source

A Closed‐Loop Hybrid Discovery System of Type I Photosensitizers for Hypoxic Tumor Therapy

Advanced Science, EarlyView.
The work developed a closed‐loop hybrid discovery system to rationally design and predict high‐performance Type I PSs for hypoxic tumor therapy. 664 Potential candidates are identified from a dataset through a support vector machine (SVM) classification model, and two candidates are experimentally verified as Type I PSs, which highlighted the potential
Xia Ling, Yixin Zhu, Min Li, Zongliang Xie, Lei Cao, Wentao Song, Dandan Wang, Duo Mao, Xiaonan Wang, Bin Liu   +9 more
wiley   +1 more source

Manifold Learning in Medical Imaging

, 2019
openaire   +4 more sources

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Enhance explainability of manifold learning

Neurocomputing, 2022
Henry Han, Wentian Li, Jiacun Wang, Guimin Qin, Xi Qin   +4 more
semanticscholar   +2 more sources

Manifold learning: what, how, and why

Annual Review of Statistics and Its Application, 2023
Manifold learning (ML), also known as nonlinear dimension reduction, is a set of methods to find the low-dimensional structure of data. Dimension reduction for large, high-dimensional data is not merely a way to reduce the data; the new representations ...
M. Meilă, Hanyu Zhang
semanticscholar   +1 more source

Canonical normalizing flows for manifold learning

Neural Information Processing Systems, 2023
Manifold learning flows are a class of generative modelling techniques that assume a low-dimensional manifold description of the data. The embedding of such a manifold into the high-dimensional space of the data is achieved via learnable invertible ...
Kyriakos Flouris, E. Konukoglu
semanticscholar   +1 more source

Combination of Manifold Learning and Deep Learning Algorithms for Mid-Term Electrical Load Forecasting

IEEE Transactions on Neural Networks and Learning Systems, 2021
Mid-term load forecasting (MTLF) is of great significance for power system planning, operation, and power trading. However, the mid-term electrical load is affected by the coupling of multiple factors and demonstrates complex characteristics, which leads
Jinghua Li, Shanyang Wei, Wei Dai
semanticscholar   +1 more source