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Phosphates

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A deep learning framework to predict binding preference of RNA constituents on protein surface.

Nature communications
Protein-RNA interaction plays important roles in post-transcriptional regulation. However, the task of predicting these interactions given a protein structure is difficult. Here we show that, by leveraging a deep learning model NucleicNet, attributes...

Development of a quantitative systems pharmacology model of chronic kidney disease: metabolic bone disorder.

American journal of physiology. Renal physiology
Chronic kidney disease mineral bone disorder (CKD-MBD) is a virtually universal complication of kidney diseases, starting early in the course of disease and resulting in devastating clinical consequences ranging from bone fragility to accelerated ath...

Application of the deep learning algorithm in nutrition research - using serum pyridoxal 5'-phosphate as an example.

Nutrition journal
BACKGROUND: Multivariable linear regression (MLR) models were previously used to predict serum pyridoxal 5'-phosphate (PLP) concentration, the active coenzyme form of vitamin B6, but with low predictability. We developed a deep learning algorithm (DL...

Sustainable utilization of FeO-modified activated lignite for aqueous phosphate removal and ANN modeling.

Environmental research
Lignites are widely available and cost-effective in many countries. Sustainable methods for their utilization drive innovation, potentially advancing environmental sustainability and resource efficiency. In the present study, FeO (∼25.1 nm) supported...

Supporting data-enhanced hybrid ordinary differential equation model for phosphate dynamics in municipal wastewater treatment.

Bioresource technology
A parallel hybrid ordinary differential equation (ODE) integrating the Activated Sludge Model No. 2d (ASM2d) and an artificial neural network (ANN) was developed to simulate biological phosphorus removal (BPR) with high accuracy and interpretability....

Prediction for the recycle of phosphate tailings in enhanced gravity field based on machine learning and interpretable analysis.

Waste management (New York, N.Y.)
Recleaning phosphate tailings using the low-cost enhanced gravity separation method is beneficial for maximizing the recovery of phosphorus element. A machine learning framework was constructed to predict the target variables of the yield, grade, and...

Design optimization of bimetal-modified biochar for enhanced phosphate removal performance in livestock wastewater using machine learning.

Bioresource technology
Mg-modified biochar shows high adsorption performance under weakly acidic and neutral water conditions. However, its phosphate removal efficiency markedly decreases in naturally alkaline wastewater, such as that released in livestock farming (anaerob...

Phosphate-solubilizing fungus (PSF) - mediated phosphorous solubilization and validation through Artificial intelligence computation.

World journal of microbiology & biotechnology
Phosphate-solubilizing fungus (PSF) strain alaromyces funiculosus was investigated for phosphorus solubilization, utilizing a range of pH levels and phosphate sources, followed by data confirmation through artificial intelligence modeling. T. funicul...

Sustainable separation of molybdenum from mixed mineral acids generated as semiconductor industry waste streams using tributyl phosphate (TBP) by effects of hybrid machine learning models.

Journal of environmental management
This study explores the separation and optimization of molybdenum (Mo) from mixed mineral acids derived from semiconductor industry waste streams with tributyl phosphate (TBP) by implementing machine learning (ML) models. Considerable experimental te...

Development of a Machine Learning Algorithm to Predict Abnormalities in Serum Phosphate in a Large Oncology Cohort.

JCO clinical cancer informatics
PURPOSE: Serum phosphate is commonly measured in oncology patients because of the relationship between oncologic conditions and treatments with abnormal phosphate. All patients attending our institution, a large specialist oncology center, have a sta...