[HTML][HTML] AI-enabled organoids: construction, analysis, and application

L Bai, Y Wu, G Li, W Zhang, H Zhang, J Su - Bioactive Materials, 2024 - Elsevier
Organoids, miniature and simplified in vitro model systems that mimic the structure and
function of organs, have attracted considerable interest due to their promising applications in …

Machine learning in cardiology: Clinical application and basic research

J Komuro, D Kusumoto, H Hashimoto, S Yuasa - Journal of cardiology, 2023 - Elsevier
Machine learning is a subfield of artificial intelligence. The quality and versatility of machine
learning have been rapidly improving and playing a critical role in many aspects of social …

[HTML][HTML] NRTPredictor: identifying rice root cell state in single-cell RNA-seq via ensemble learning

H Wang, YN Lin, S Yan, JP Hong, JR Tan, YQ Chen… - Plant Methods, 2023 - Springer
Background Single-cell RNA sequencing (scRNA-seq) measurements of gene expression
show great promise for studying the cellular heterogeneity of rice roots. How precisely …

[HTML][HTML] Transcriptional regulation of the postnatal cardiac conduction system heterogeneity

Y Oh, R Abid, S Dababneh, M Bakr, T Aslani… - Nature …, 2024 - nature.com
The cardiac conduction system (CCS) is a network of specialized cardiomyocytes that
coordinates electrical impulse generation and propagation for synchronized heart …

[HTML][HTML] Exploring the advances of single-cell RNA sequencing in thyroid cancer: a narrative review

JK Tan, WA Awuah, S Roy, T Ferreira, A Ahluwalia… - Medical Oncology, 2023 - Springer
Thyroid cancer, a prevalent form of endocrine malignancy, has witnessed a substantial
increase in occurrence in recent decades. To gain a comprehensive understanding of …

Uncertainty-aware single-cell annotation with a hierarchical reject option

L Theunissen, T Mortier, Y Saeys… - Bioinformatics, 2024 - academic.oup.com
Motivation Automatic cell type annotation methods assign cell type labels to new datasets by
extracting relationships from a reference RNA-seq dataset. However, due to the limited …

Artificial intelligence in cell annotation for high-resolution RNA sequencing data

N Hou, X Lin, L Lin, X Zeng, Z Zhong, X Wang… - TrAC Trends in …, 2024 - Elsevier
Abstract Characterization of cell heterogeneity in gene expression is a “hot” but complex
issue in the fields of biology and medicine. Therefore, high-resolution RNA sequencing …

scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution

Z Chen, Y Miao, Z Tan, Q Hu, Y Wu, X Li, W Guo… - …, 2024 - academic.oup.com
Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular
compositions in the tumor microenvironment (TME). As previous studies have defined many …

[HTML][HTML] Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets

AR Patil, J Schug, C Liu, D Lahori, HC Descamps… - Cell Reports …, 2024 - cell.com
Summary Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by
immune cells. Despite progress in immunotherapies that could delay T1D onset, early …

[HTML][HTML] Computational methods summarizing mutational patterns in cancer: promise and limitations for clinical applications

A Patterson, A Elbasir, B Tian, N Auslander - Cancers, 2023 - mdpi.com
Simple Summary Cancer is a complex disease that develops over time through accumulated
mutations in DNA that transform normal cells into a cancerous state. To fully capture the …