Results 151 to 160 of about 15,959 (250)

Machine Learning Prediction of Laccase‐Catalyzed Oxidation of Aromatic Compounds Using Curated Enzyme‐Specific Datasets

Journal of Computational Chemistry, Volume 47, Issue 7, March 15, 2026.
We curate laccase‐substrate datasets and train five classifiers, from regularized logistic regression to tree‐based models and ChemBERTa, to predict whether a substrate will be oxidized. Feature importance and attention maps projected onto molecular substructures make the predictions interpretable and useful for pre‐screening before the bench ...
Yulia Kulagina, Christian Goldhahn, Ramon Weishaupt, Mark Schubert   +3 more
wiley   +1 more source

Adaptive Sliding Mode Control Incorporating Improved Integral Compensation Mechanism for Vehicle Platoon with Input Delays. [PDF]

Sensors (Basel)
Ding Y, Wang Y, Li X.
europepmc   +1 more source

Thickness‐Dependent Skyrmion Evolution in Fe3GeTe2 During Magnetization Reversal

Advanced Functional Materials, Volume 36, Issue 18, 2 March 2026.
Thickness‐ and field‐dependent magnetic domain behavior in 2D van der Waals Fe3GeTe2 is studied using Lorentz TEM and micromagnetic simulations. A patch‐like domain phase evolves from skyrmions during magnetization reversal, and step edges between thickness regions act as pinning sites.
Jennifer Garland, John Fullerton, PeiYu Cai, Rabindra Basnet, Santosh Karki Chhetri, Jin Hu, Elton J. G. Santos, Yue Li, Charudatta Phatak, Amanda Petford‐Long   +9 more
wiley   +1 more source

Bioinformatics Approach to mTOR Signaling Pathway-Associated Genes and Cancer Etiopathogenesis. [PDF]

Genes (Basel)
Ozdilli K, Oztan G, Kıvanç D, Oğuz R, Oguz F, Ciftci HS.   +5 more
europepmc   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, Volume 38, Issue 18, 25 March 2026.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source

Improving protein interaction prediction in GenPPi: a novel interaction sampling approach preserving network topology. [PDF]

BMC Bioinformatics
Silva A, Marquez C, Godoy I, Silva L, Prado M, Beppler M, Avila N, Travençolo B, Santos AR.   +8 more
europepmc   +1 more source

Multi‐View Biomedical Foundation Models for Molecule‐Target and Property Prediction

Advanced Science, Volume 13, Issue 14, 9 March 2026.
Molecular foundation models can provide accurate predictions for a large set of downstream tasks. We develop MMELON, an approach that integrates pre‐trained graph, image, and text foundation models and validate our multi‐view model on over 120 tasks, including GPCR binding.
Parthasarathy Suryanarayanan, Yunguang Qiu, Shreyans Sethi, Diwakar Mahajan, Hongyang Li, Yuxin Yang, Elif Eyigoz, Aldo Guzmán‐Sáenz, Daniel E. Platt, Timothy H. Rumbell, Kenney Ng, Sanjoy Dey, Myson Burch, Bum Chul Kwon, Pablo Meyer, Feixiong Cheng, Jianying Hu, Joseph A. Morrone   +17 more
wiley   +1 more source

GRAFT: a graph-aware fusion transformer for cancer driver gene prediction. [PDF]

Brief Bioinform
Cho SP, Cho YR.
europepmc   +1 more source

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, Volume 8, Issue 3, March 2026.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source

Chain ends excite polymer cooperative motion. [PDF]

Sci Adv
Xu Q, Wu Z, Randazzo K, Xu WS, Zhang B, Priestley RD, Zuo B.   +6 more
europepmc   +1 more source