Results 61 to 70 of about 4,014,888 (255)

From omics to AI—mapping the pathogenic pathways in type 2 diabetes

FEBS Letters, EarlyView.
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan, Lu Qi, Pierre Zalloua   +2 more
wiley   +1 more source

The myelin water imaging transcriptome: myelin water fraction regionally varies with oligodendrocyte-specific gene expression

Molecular Brain
Identifying sensitive and specific measures that can quantify myelin are instrumental in characterizing microstructural changes in neurological conditions. Neuroimaging transcriptomics is emerging as a valuable technique in this regard, offering insights
Jaimie J. Lee, Paulina S. Scheuren, Hanwen Liu, Ryan W. J. Loke, Cornelia Laule, Catrina M. Loucks, John L.K. Kramer   +6 more
doaj   +1 more source

Identification of tissue-specific and common methylation quantitative trait loci in healthy individuals using MAGAR

Epigenetics & Chromatin, 2021
Background Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease.
Michael Scherer, Gilles Gasparoni, Souad Rahmouni, Tatiana Shashkova, Marion Arnoux, Edouard Louis, Arina Nostaeva, Diana Avalos, Emmanouil T. Dermitzakis, Yurii S. Aulchenko, Thomas Lengauer, Paul A. Lyons, Michel Georges, Jörn Walter   +13 more
doaj   +1 more source

Statistical process control for data without inherent order [PDF]

, 2012
Background The XmR chart is a powerful analytical tool in statistical process control (SPC) for detecting special causes of variation in a measure of quality. In this analysis a statistic called the average moving range is used as a measure of dispersion
Alan J Poots, Thomas Woodcock
core   +3 more sources

Thermostable neutral metalloprotease from Geobacillus sp. EA1 does not share thermolysin's preference for substrates with leucine at the P1′ position

FEBS Letters, EarlyView.
Knowing how proteases recognise preferred substrates facilitates matching proteases to applications. The S1′ pocket of protease EA1 directs cleavage to the N‐terminal side of hydrophobic residues, particularly leucine. The S1′ pocket of thermolysin differs from EA's at only one position (leucine in place of phenylalanine), which decreases cleavage ...
Grant R. Broomfield, Torsten Kleffmann, David J. Saul, Sigurd M. Wilbanks   +3 more
wiley   +1 more source

Optimizing fire station locations for the Istanbul metropolitan municipality [PDF]

, 2013
Copyright @ 2013 INFORMSThe Istanbul Metropolitan Municipality (IMM) seeks to determine locations for additional fire stations to build in Istanbul; its objective is to make residences and historic sites reachable by emergency vehicles within five ...
Burçin Bozkaya, Catay B, Connally E, Doeksen G, Emel Aktaş, Füsun Ülengin, Garey MR, George MV, Goldberg JB, Nemhauser GL, ReVelle C, Tayman J, Valinski D, Williams HP, Özay Özaydın, Şule Önsel   +15 more
core   +1 more source

Ergothioneine supplementation improves pup phenotype and survival in a murine model of spinal muscular atrophy

FEBS Letters, EarlyView.
Spinal muscular atrophy (SMA) is a genetic disease affecting motor neurons. Individuals with SMA experience mitochondrial dysfunction and oxidative stress. The aim of the study was to investigate the effect of an antioxidant and neuroprotective substance, ergothioneine (ERGO), on an SMNΔ7 mouse model of SMA.
Francesca Cadile, Daniela Ratto, Giorgia Rastelli, Ottavia Eleonora Ferraro, Caterina Temporini, Sunil Kumar, Simona Boncompagni, Paola Rossi, Monica Canepari   +8 more
wiley   +1 more source

Rationally Design Thermoelectric Materials Based on Ingenious Machine Learning Methods

Advanced Electronic Materials
Data quality, feature interpretability, and model generalization are critical and challenging for applying machine learning (ML) in the design of high‐efficiency materials.
Yuqing Sun, Xiaorui Chen, Jianzhi Gao, Wenliang Zhu, Minghu Pan   +4 more
doaj   +1 more source

Percolation limited magnetic order in Eu1-xCaxB6 [PDF]

, 2018
.: We report the results of measurements of the low-temperature specific heat Cp(T) and the ac susceptibility χac(T) in low applied magnetic fields for a series of samples of Eu1-xCaxB6.
Bianchi, A. D., Felder, E., Fisk, Z., Ott, H. R., Streule, S., Weller, M., Wigger, G. A.   +6 more
core  

Provably correct Java implementations of Spi Calculus security protocols specifications [PDF]

, 2010
Spi Calculus is an untyped high level modeling language for security protocols, used for formal protocols specification and verification. In this paper, a type system for the Spi Calculus and a translation function are formally defined, in order to ...
Abadi, Abadi, Abadi, Alfredo Pironti, Bajaj, Bajaj, Bierman, Dolev, Durante, Igarashi, Milner, Nadalin, Pierce, Pironti, Riccardo Sisto, Sammapun, Schellhorn   +16 more
core   +1 more source