Results 61 to 70 of about 8,174 (200)

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

The theory of differentiation in linear topological spaces

, 1967
V. I. Averbukh, O. Smolyanov
semanticscholar   +2 more sources

Mechanical Caging of Nucleic Acids Enabled by Light‐Activated Synthetic Molecular Motors

Angewandte Chemie, EarlyView.
A synthetic light‐driven molecular motor imposes mechanical constraints on nucleic acids, enabling “mechanical caging” as a new mode to regulate DNA structure and function through mechanical input rather than chemical masking. ABSTRACT Control over nucleic acid activity is central to biotechnology and therapeutic development.
Yuchen Ma, Erika McCarthy, N. Sanjeeva Murthy, Cameron McGovern, Zhenyu Han, Şölen Ekesan, Subhajit Nandi, Advik Sirimarapu, Wilma K. Olson, Darrin M. York, Yuwei Gu   +10 more
wiley   +2 more sources

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

[O─I─O]+ Halogen‐Bonded Complexes of Pyridine N‐Oxides

Angewandte Chemie, EarlyView.
The missing puzzle of 3‐center‐4‐electron halogen‐bonded complexes viz. [O─I─O]+ of pyridine N‐oxides are structurally characterized by x‐ray diffraction. Monodentate N‐oxide O‐atom acts as the halogen bond acceptor. Their solution complexations are characterized by 15N NMR spectroscopy.
Rakesh Puttreddy, Sergi Burguera, Antonio Frontera, Kari Rissanen   +3 more
wiley   +2 more sources

Implantation‐On‐Chip: An AI‐Based Platform for Monitoring the Embryo Trophoblast–Endometrial Stroma Cross Talk With Xenobiotics Interference

Advanced Intelligent Systems, EarlyView.
We present a novel AI‐integrated implantation‐on‐chip platform that enables mimicking and monitoring the maternal–fetal interactions at the early phases of human embryo implantation with high spatiotemporal resolution. The complexity of the trophoblast invasion process was addressed by conducting the analysis at global (rate of invasion) and local ...
Joanna Filippi, Valentina Lacconi, Arianna Mencattini, Micol Massimiani, Dolores Lobresca, Gaia Posanzini, Alessia Riccardi, Paola Casti, Michele D’Orazio, Gianni Antonelli, Giorgia Curci, Luisa Campagnolo, Eugenio Martinelli   +12 more
wiley   +1 more source

A Comprehensive 19F NMR Framework for Fragment‐Based Drug Discovery: The Validated Screening Library OpenFL600 and Efficient Affinity Ranking by CSAR

Angewandte Chemie, EarlyView.
NMR screening is a powerful method for hit detection in drug‐discovery. We designed and validated the OpenFL600 19F$^{19}{\rm F}$ NMR library to probe diverse targets, including RNA, GPCRs, kinases, and proteases. This library yields target‐specific ligands without generating promiscuous binders.
Simon H. Rüdisser, Gabriela Stadler, Giacomo Padroni, Daria Barbash, Marco M. Ruckstuhl, Nils Lorz, Christina Jordan, Sarah Skibinski, Timo T. Stühlinger, Sarah E. Kratzwald, Katharina M. Siess, Sven Brüschweiler, Gerald Platzer, Antoine Cléry, Robert Konrat, Frédéric H.‐.T. Allain, Alvar D. Gossert   +16 more
wiley   +2 more sources

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source

Cellular Material Network: A General Machine Learning Architecture for Predicting Mechanical Properties of Cellular Materials

Advanced Intelligent Systems, EarlyView.
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou, Qiang Gao, Liuchao Jin, Guoquan Xie, Kang Zhang, Wei‐Hsin Liao   +5 more
wiley   +1 more source