Results 191 to 200 of about 736,304 (285)

Informing the Borrowing Process for Dose-Finding Trials by Estimating the Similarity Between Population-Specific Dose-Toxicity Curves. [PDF]

Pharm Stat
Zocholl D, Götte H, Habermehl C, Günhan BK.   +3 more
europepmc   +1 more source

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

Advanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang, Bowen Fu, Chuanchao Zhang, Xiaoping Liu   +3 more
wiley   +1 more source

A tutorial on Bayesian hypothesis testing of correlation coefficients using the BFpack-module in JASP. [PDF]

Behav Res Methods
Mulder J, Pfadt J, Wagenmakers EJ.
europepmc   +1 more source

Genetic Control of Tissue Remodeling by a Non‐Coding SNP in ITGA8 Explains Carotenoid‐Based Color Polymorphism in Marine Mollusks

Advanced Science, EarlyView.
In this study, the orange‐muscle giant abalone (Haliotis gigantea) is used as a model to identify a non‐coding SNP that disrupts the interaction between ITGA8 pre‐mRNA and the splicing factor ILF2, leading to altered ITGA8 splicing. These splicing changes promote carotenoid accumulation in abalone muscle through the regulation of tissue remodeling ...
Xiaohui Wei, Wenzhu Peng, Zekun Huang, Bingye Yang, Yiyu Wu, Minzhen Han, Yi Wang, Bingling Peng, Guosheng Hu, Jiawei Hong, Guijia Liu, Linwei Nie, Yang Gan, Miaoqin Huang, Xuan Luo, Weiwei You, Wen Liu, Caihuan Ke   +17 more
wiley   +1 more source

Tools and benchmarks evolve: what is their impact on parameter tuning in SBSE experiments? [PDF]

Empir Softw Eng
Golmohammadi A, Zhang M, Arcuri A.
europepmc   +1 more source

Analysis of Multiscale Condensation Phenomena Using a Zero‐Shot Computer Vision Framework

Advanced Science, EarlyView.
A zero‐shot computer vision framework quantifies multiscale condensation dynamics by automatically segmenting droplets and extracting physical parameters without labeled data. The workflow integrates data mining and statistical analysis to reveal droplet growth, coalescence statistics, and sweeping behaviors, enabling label‐free measurement of heat ...
Donghyeong Lee, Seokwan Roh, Jaewoo Jeong, Kuk‐Jin Yoon, Jungchul Lee, Youngsuk Nam   +5 more
wiley   +1 more source

High‐Conductivity Electrolytes Screened Using Fragment‐ and Composition‐Aware Deep Learning

Advanced Science, EarlyView.
We present a new deep learning framework that hierarchically links molecular and functional unit attributions to predict electrolyte conductivity. By integrating molecular composition, ratios, and physicochemical descriptors, it achieves accurate, interpretable predictions and large‐scale virtual screening, offering chemically meaningful insights for ...
Xiangwen Wang, Muyang Chen, Gengyi Bao, Yan Lai, Jinghe Cao, Xinhua Liu, Rui Tan   +6 more
wiley   +1 more source

Systematic evaluation of de novo mutation calling tools using whole genome sequencing data. [PDF]

Brief Bioinform
Shah A, Monger S, Troup M, Ip EKK, Giannoulatou E.   +4 more
europepmc   +1 more source

Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model

Advanced Science, EarlyView.
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen, Jingrui Zhong, Xiaochun Zhang, Jingke Chen, Lin Guo, Xiaoliang Xiong, Xiaonan Zhang, Xiangyu Liu, Bailong Xiao, Boxue Tian   +9 more
wiley   +1 more source

Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification. [PDF]

Proc Conf Empir Methods Nat Lang Process
Kruse M, Afshar M, Khatwani S, Mayampurath A, Chen G, Gao Y.   +5 more
europepmc   +1 more source