Results 181 to 190 of about 831,782 (302)

Towards a Compositional Framework for Describing Human Phenotypes

Advanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu, Yunchao Ling, Xinyue Hu, Wei Chen, Rong Zhou, Xinhao Zhuang, Yanfeng Jiang, Jialu Zhao, Xingdong Chen, Jingchun Luo, Li Jin, Guoqing Zhang   +11 more
wiley   +1 more source

Semantic Topological Multi-Scale Part Network for Fine-Grained Visual Classification. [PDF]

J Imaging
Liu X, Zhi M, Yin Y, Sa R.
europepmc   +1 more source

MAPA: A Semantic Network Framework for Functional Module Discovery and Interpretation in Multi‐Omics Data

Advanced Science, EarlyView.
MAPA transforms complex multi‐omics data into biologically coherent functional modules by integrating pathway information with molecular interaction networks. Retrieval‐augmented large language models then generate structured, literature‐informed interpretations.
Yifei Ge, Feifan Zhang, Yijiang Liu, Chao Jiang, Peng Gao, Nguan Soon Tan, Sai Zhang, Yuchen Shen, Qianyi Zhou, Xin Zhou, Xiao Wang, Fangqing Zhao, Chuchu Wang, Xiaotao Shen   +13 more
wiley   +1 more source

What is so hard about abstract words, anyways? A neuromechanistic explanation using brain-constrained neural network models. [PDF]

Cogn Neurodyn
Dobler FR, Stroppa L, Pulvermüller F.
europepmc   +1 more source

Predicting Enzyme Turnover Numbers and Enabling Rational Enzyme Evolution

Advanced Science, EarlyView.
MCKcat, a deep learning framework combining multi‐scale convolution and cross‐attention, accurately predicts enzyme turnover number (kcat) by fusing sequence and reaction representations. It couples with rational design in a two‐step strategy for Bacillus aryabhattai laccase engineering, achieving a 75% positive rate with synergistically enhanced ...
Fengya Ge, Xiangyang Ma, Jiyan Li, Mengxiang Wang, Fuping Lu, Yihan Liu, Lin Wang   +6 more
wiley   +1 more source

Characterizing LLM scientific concept generation: A multi-dimensional measurement study. [PDF]

PLoS One
Ahmadpour J.
europepmc   +1 more source

Disentangling Heterogeneous Molecular Networks for Multi‐Omics‐Driven Cancer Driver Discovery

Advanced Science, EarlyView.
DRIVE integrates PPI topology and pan‐cancer multi‐omics profiles through dual‐view graph disentanglement, contrastive representation learning, and joint optimization. Across six PPI networks, DRIVE outperforms ten baselines and remains robust to structural and annotation perturbations.
Xinjing Gong, Ji Li, Mu Su, Peishen Yu, Te Ma, Ruiyang Zhai, Chenye Zhang, Mengyan Zhang, Yan Zhang   +8 more
wiley   +1 more source

CSDPCDA: A miRNA-Mediated Cross-Semantic Regulatory Network Framework for Predicting circRNA-Disease Associations. [PDF]

Int J Mol Sci
Wang X, Zhao M, Zhao Y, Xiang S, Wang C, Wang G.   +5 more
europepmc   +1 more source

DUET‐seq: An Open‐Source Droplet Platform for High‐Fidelity Joint Chromatin and Transcriptome Profiling Reveals Temporal Regulatory Decoupling in Single Cells

Advanced Science, EarlyView.
DUET‐seq is an open‐source droplet platform that jointly profiles chromatin accessibility and gene expression from the same nucleus. Dissolvable dual‐linker hydrogel beads and a one‐step intra‐droplet RT‐PCR co‐index both modalities in under 12 h at roughly $0.04 per cell.
Dong Cheng, Zijun Meng, Lan Wei, Pingjing Yang, Fanfan Zhang, Zhiyi Luo, Ting Lai, Chunli Li, Mengyao Zhao, Mengqin Xu, Jiaqi Wang, Linjun Li, Huarong Chen, Jin Li, Ailong Huang, Youquan Bu, Liuyang Zhao   +16 more
wiley   +1 more source

Online physician recommendation with dynamic capacity and semantic similarity: A primal-dual optimization framework. [PDF]

PLoS One
Qiu Y, Chen Y, Xie Y, Li M, Yan J, Liu H.   +5 more
europepmc   +1 more source