Results 301 to 310 of about 407,505 (399)

HiST: Histological Images Reconstruct Tumor Spatial Transcriptomics via MultiScale Fusion Deep Learning

Advanced Science, EarlyView.
HiST, a multiscale deep learning framework, reconstructs spatially resolved gene expression profiles directly from histological images. It accurately identifies tumor regions, captures intratumoral heterogeneity, and predicts patient prognosis and immunotherapy response.
Wei Li, Dong Zhang, Eryu Peng, Shijun Shen, Hamid Alinejad‐Rokny, Yao Liu, Junke Zheng, Cizhong Jiang, Youqiong Ye   +8 more
wiley   +1 more source

Smart spatial omics (S2-omics) optimizes region of interest selection to capture molecular heterogeneity in diverse tissues. [PDF]

Nat Cell Biol
Yuan M, Jin K, Yan H, Schroeder A, Luo C, Yao S, Dumoulin B, Levinsohn J, Luo T, Clemenceau JR, Jang I, Kim M, Liu Y, Deng M, Furth EE, Wilson P, Nayak A, Lubo I, Solis Soto LM, Wang L, Park JH, Susztak K, Hwang TH, Li M.   +23 more
europepmc   +1 more source

Structural Variation and 3D Genome‐Driven DNA/RNA Methylation Divergence Contributing to Cotton Fiber Domestication

Advanced Science, EarlyView.
These findings elucidated the crucial role of the “SVs‐3D genome remodeling‐epigenetic modifications‐gene expression” cascade regulatory network in cotton fiber domestication, offering both a theoretical foundation and genetic resources for molecular design breeding in fiber crops.
Lei Shao, Shangkun Jin, Haojie Jiang, Tianyu Pan, Zesheng Rui, Xiaowen Shi, Ting Zhao, Zhanfeng Si, Xueying Guan, Yan Hu, Tianzhen Zhang, Lei Fang   +11 more
wiley   +1 more source

IGF‐1 Deficiency Serves as an Integrated Biomarker Pathogenic Driver and Predictor in Poor Ovarian Response

Advanced Science, EarlyView.
IGF‐1 deficiency underlies poor ovarian response (POR), as reduced levels in follicular fluid and granulosa cells impair antral follicle formation and compromise reproductive outcomes. Including IGF‐1 as a biomarker significantly enhances the accuracy of models predicting both PORrisk and pregnancy success.
Zhu Hu, Yuanyuan Yu, Guanyou Huang, Jinnan Li, Chao Yang, Aizhuan Long, Jia Tang, Tengxiang Chen, Shuyun Zhao, Tuo Zhang   +9 more
wiley   +1 more source

Multi-omics strategies for biomarker discovery and application in personalized oncology. [PDF]

Mol Biomed
Jiang Z, Zhang H, Gao Y, Sun Y.
europepmc   +1 more source

A Trypsin‐Like Serine Protease ZmNAL1a Fine‐Tunes Maize Floral Transition and Flowering Time

Advanced Science, EarlyView.
This study identifies a trypsin‐like serine protease, ZmNAL1a, that moves from leaves to the shoot apical meristem. ZmNAL1a promotes the floral transition by degrading TOPLESS‐like corepressor REL2, which thereby enhances the expression of key flowering genes through elevating histone acetylation and relieving REL2–ZmEREBP147‐mediated transcriptional ...
Nan Li, Qiang Ning, Zhen Li, Qian Zhang, Peilu Zhu, Jimin Zhan, Yunfu Li, Zhen Li, Liang Dong, Qing Xiong, Jiahao Liao, Jie Liu, David Jackson, Munenori Kitagawa, Zuxin Zhang, Lei Liu   +15 more
wiley   +1 more source

Multi-omics reveal critical differentiation target for Parkinson's Disease-vulnerable midbrain dopaminergic neurons

Garcia Swinburn, Roberto, Lyu, Guochang, Arenas, Ernest   +2 more
openalex   +1 more source

Omics ORPD

A set of omics data as ...
openaire   +1 more source

GlycoChat Uncovers Glycan–Lectin Circuits in the Tumor Microenvironment of Pancreatic Cancer

Advanced Science, EarlyView.
Aberrant glycosylation drives cancer progression, yet its role in the tumor microenvironment remains unclear. We developed GlycoChat to map glycan–lectin circuits at single‐cell resolution. We discovered that cancer cells induce immunosuppressive macrophage differentiation and impair phagocytosis through interactions with CLEC10A and SIGLEC3 ...
Dinh Xuan Tuan Anh, Sunanda Keisham, Arun Burramsetty, Lalhaba Oinam, Koichiro Kumano, Akihiro Kuno, Osamu Shimomura, Tatsuya Oda, Hiroaki Tateno   +8 more
wiley   +1 more source

Value-based health care frameworks for the health technology assessments of "omics" technologies: an international survey. [PDF]

Int J Technol Assess Health Care
Osti T, Taha A, Reviriego-Rodrigo E, Pastorino R, Boccia S, Gutierrez-Ibarluzea I.   +5 more
europepmc   +1 more source