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MEGA-GO: Functions prediction of diverse protein sequence length using Multi-scalE Graph Adaptive neural network.
Bioinformatics
January 2025
Guangdong Provincial Key Laboratory IRADS, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai, China.
Motivation: The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models have emerged as a promising solution to expedite the annotation process. However, despite making significant progress in protein research, graph neural networks face challenges in capturing long-range structural correlations and identifying critical residues in protein graphs.
View Article and Find Full Text PDFUsing feedback in pooled experiments augmented with imputation for high genotyping accuracy at reduced cost.
G3 (Bethesda)
January 2025
Division of Scientific Computing, Department of Information Technolokgy, Uppsala University, SE-751 05 Uppsala, Sweden.
Conducting genomic selection in plant breeding programs can substantially speed up the development of new varieties. Genomic selection provides more reliable insights when it is based on dense marker data, in which the rare variants can be particularly informative. Despite the availability of new technologies, the cost of large-scale genotyping remains a major limitation to the implementation of genomic selection.
View Article and Find Full Text PDFNoninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.
Transl Vis Sci Technol
January 2025
School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.
Purpose: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.
Methods: The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels.
Folate and Vitamin B12 Status among Non-Pregnant, Non-Lactating Women of Reproductive Age and Predicted Risk for Neural Tube Defects, Morogoro Region, Tanzania.
Matern Child Health J
January 2025
Tanzania Field Epidemiology and Laboratory Training Program, Tanzania Ministry of Health, Dodoma, Tanzania.
Introduction: Population risk for neural tube defects (NTDs) can be determined using red blood cell (RBC) folate. However, a paucity of biomarker and surveillance data among non-lactating, non-pregnant women of reproductive age (NPWRA) from Africa limits accurate assessment. Our study assessed folate and vitamin B12 status among non-lactating NPWRA and predicted population risk of NTDs in Tanzania.
View Article and Find Full Text PDFAssessing uncertainties in modeling the risk of geogenic groundwater contamination.
Environ Sci Pollut Res Int
January 2025
Department of Civil and Architectural Engineering, Sultan Qaboos University, Muscat, Oman.
Assessing groundwater contamination risk is a critical aspect of preventing and managing groundwater pollution. There was a research gap in the investigation of uncertainties in modeling groundwater contamination risks in aquifers. This study addresses this gap using Bayesian Model Averaging (BMA), with a novel focus on risk exposures from geogenic contaminants, such as lead (Pb).
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