Results 201 to 210 of about 32,202 (267)

The persistent advantage of model‐based phylogenetic methods for single‐trait prediction

Methods in Ecology and Evolution, EarlyView.
Abstract Reliable predictions of biological traits support a wide range of applications, from bioprospecting to informing conservation priorities. Given the complexity and diversity of trait evolution, robust methods for trait prediction are essential for drawing meaningful evolutionary inferences from phylogenetic data.
Adam Richard‐Bollans, Daniele Silvestro   +1 more
wiley   +1 more source

New insights on the cavitation development and the role of bubbles in Micro-Venturi channels. [PDF]

Ultrason Sonochem
Maleki M, Priyadarshi A, Cleaves J, Toyran E, Kosar A, Tzanakis I, Ghorbani M.   +6 more
europepmc   +1 more source

A tutorial on Bayesian model averaging for exponential random graph models

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract The use of exponential random graph models (ERGMs) is becoming prevalent in psychology due to their ability to explain and predict the formation of edges between vertices in a network. Valid inference with ERGMs requires correctly specifying endogenous and exogenous effects as network statistics, guided by theory, to represent the network ...
Ihnwhi Heo, Jan‐Willem Simons, Haiyan Liu   +2 more
wiley   +1 more source

2dSpAn-Auto: an automated tool for analysis of two-dimensional dendritic spine images. [PDF]

BMC Bioinformatics
Paul S, Pramanick R, Das N, Baczynska E, Bedrood Z, Chakraborti T, Basu S, Wlodarczyk J.   +7 more
europepmc   +1 more source

Tau‐targeting active immunotherapy slows progression and reduces pathology in mouse models of tauopathy

Brain Pathology, EarlyView.
The efficacy of the novel anti‐tau active immunotherapy, p5555kb, was tested using two mouse models of tau pathology. p5555kb inoculation increased the survival rate and reduced tau pathology in tau‐overexpressing P301L mice and decreased tau seeding in the brains of C57BL/6 mice injected with human‐purified Alzheimer's disease tau.
Christopher M. Brown, Jeanne K. Brooks, Louise Kelly, Madeline M. Vroom, Matthew Longo, Jean‐Cosme Dodart, Roxana Carare, Justin D. Boyd   +7 more
wiley   +1 more source

The Vibrational Signature of Alzheimer's Disease: A Computational Approach Based on Sonification, Laser Projection, and Computer Vision Analysis. [PDF]

Biomimetics (Basel)
Pérez-Elvira R, Oltra-Cucarella J, Agudo Juan M, Polo-Ferrero L, Juárez-Vela R, Bosch-Bayard J, Quintana Díaz M, de la Cruz J, Salgado Ruíz A.   +8 more
europepmc   +1 more source

Label Noise in Pathological Segmentation Is Overlooked, Leading to Potential Overestimation of Artificial Intelligence

Cancer Science, EarlyView.
This study evaluated how artificial label noise affects cancer pathology segmentation models, demonstrating that boundary‐dependent noise leads to overestimation of performance metrics, while random noise mixtures further harm generalization. Our results highlight the need for standardized noise‐quantification and mitigation methods and for developing ...
Kenji Harada, Yuichiro Nomura, Daisuke Komura, Shumpei Ishikawa, Shingo Sakashita   +4 more
wiley   +1 more source

EnsembleRegNet: Interpretable deep learning for transcriptional network inference from single-cell RNA-seq. [PDF]

Comput Biol Chem
Alawad DM, Katebi A, Hoque MT.
europepmc   +1 more source

Graph Neural Network‐Based Multi‐Scale Whole Slide Image Fusion for pT Staging of Muscle‐Invasive Bladder Cancer

Cancer Science, EarlyView.
Accurate pT staging in muscle‐invasive bladder cancer is essential for treatment and prognosis, but current methods rely on time‐consuming and variable microscopic evaluation. We developed a graph neural network–based model that integrates multi‐scale whole‐slide images to automate pT staging, achieving excellent performance with an AUC of 0.911 and ...
Qian Li, Qing Feng Chen, Nan Qing Liao
wiley   +1 more source

Multi-Source Porosity Image Normalization (NMI) in Selective Laser Melting for Reliable Reuse of Heterogeneous Microstructural Data. [PDF]

Materials (Basel)
Guo S, Zhang X, Ma F, Lu A, Huang Y.
europepmc   +1 more source