Results 181 to 190 of about 3,209,467 (239)

<i>metaKEGG</i>: A comprehensive algorithm package to visualize multi-omics pathway enrichment. [PDF]

Biochem Biophys Rep
Lazaratos M, Haacke N, Gaugel J, Ulz M, Bleimehl T, Täger J, Schürmann A, Vogel H.   +7 more
europepmc   +1 more source

Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter

Advanced Intelligent Discovery, EarlyView.
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon, Dmitri Gavrilov, Peggy O’Day, Ajith Pattammattel   +3 more
wiley   +1 more source

Machine Learning for Structural Steels: Materials Design, Property Prediction, Durability, and Future Directions. [PDF]

Materials (Basel)
Wei G, Li M, Cui B, Xiu W, Sarman AM.
europepmc   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

FAIR by design (TRACE): A Trusted Research Access & Collaboration Environment. [PDF]

BMC Med Inform Decis Mak
Müller M, Geisler BP, Shamas S, Bomhard NV, Hoster E, Pfirrmann M, Mansmann U.   +6 more
europepmc   +1 more source

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

Heartbeat: a multimodal dataset of fetal echocardiography and clinical metadata for early detection of congenital heart disease. [PDF]

Front Cardiovasc Med
Rodríguez S, Pérez A, Echeverry LM, Castillo Á, Ramírez NA, Escobar M, Guarín Monroy S, Vega D, Rodríguez N, Castro-Páez C, Navarro J, Domínguez MT, Laverde N, Sarmiento LA, Afanador D, D'silva Londoño L, Torres Narváez E, Fandiño MJ, Madrid AJ, Quintero JC, Rodríguez N, Briceño JC, Arbeláez P.   +22 more
europepmc   +1 more source

Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation

Advanced Intelligent Discovery, EarlyView.
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei, Sadman Sadeed Omee, Rongzhi Dong, Nihang Fu, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Meiling Xu, Ming Hu, Chris Wolverton, Jianjun Hu   +9 more
wiley   +1 more source

Interspecies Exchange of Mobile Genetic Elements During a Plant Disease Outbreak. [PDF]

Genome Biol Evol
Evseeva D, Pecrix Y, Kucka M, Weiler C, Franzl C, Vlková-Žlebková M, Colombi E, Chan YF, Poussier S, Wicker E, McCann HC.   +10 more
europepmc   +1 more source

SuperResNET: Model‐Free Single‐Molecule Network Analysis Software Achieves Molecular Resolution of Nup96

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li, Ismail M. Khater, Christian Hallgrimson, Ben Cardoen, Timothy H. Wong, Ghassan Hamarneh, Ivan R. Nabi   +6 more
wiley   +1 more source