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Here, we build a machine learning model to generate genome-wide gene essentiality predictions for C. albicans and expand the largest functional genomics resource in this pathogen (the GRACE collection) by 866 genes. Using this model and chemogenomic analyses, we define the function of three ...
This comprehensive study significantly advances our understanding of the dynamic nature of gene expression inC. albicans. The identification of genes with enhanced potential as antifungal drug targets underpins their value for future interventions. The highlighted genes, includingTPS2, TPS1, RIM21, PRA1...
In winter it was the greatest 33 place in the world. One 34 all I wanted to do was go skating. I had been waiting for weeks 35 the water was frozen solid. Mom had one rule: “Never ice-skate alone.” But I couldn’t 36 any longer that afternoon. So I 37 my skates under my ...
The use of large-scale drug testing data for predictions poses a practical challenge, since systematic ex vivo drug testing in primary patient cells is currently not feasible in many solid tumor types21. To address these limitations, we present a machine learning model, scTherapy, which ...
More and more patients receive various types of implants, such as catheters, valves, hips, that are all suitable substrates for these fungal cells to attach to and to form a biofilm. The extracellular matrix produced by biofilm cells is known to sequester antifungal drugs resulting in tolerance...
There are areas in the world that seem custom designed to make life as uncomfortable or even unsurvivable for humanity as possible. With fire, ice, poison, extreme weather conditions, or just sheer inhospitability, these locations may be stunning to look at, but to say that they're not exa...
eMethods eFigure 1: Patient Flow Diagram eFigure 2: Calibration Plots eTable: Model Performance in the Total Cohort for Each Model Type eReferences Supplement 2. Data Sharing Statement 1. Khorana AA, Tullio K, Elson P, et al. Time to initial cancer treatment in the United State...
by BPN-15477 treatment, and validated several using minigenes or patient cells. These studies suggest that the integration of genomic information, clinical annotation of disease-associated variants, and deep learning techniques have significant potential to predict therapeutic targeting for precision ...
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