Titre : Protéines de filaments intermédiaires

Protéines de filaments intermédiaires : Questions médicales fréquentes

Termes MeSH sélectionnés :

Quantitative Structure-Activity Relationship
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Sources (10000 au total)

Quantitative Structure Retention-Relationship Modeling: Towards an Innovative General-Purpose Strategy.

Reversed-Phase Liquid Chromatography (RPLC) is a common liquid chromatographic mode used for the control of pharmaceutical compounds during their drug life cycle. Nevertheless, determining the optimal...

Modeling of Anticancer Sulfonamide Derivatives Lipophilicity by Chemometric and Quantitative Structure-Retention Relationships Approaches.

Sulfonamides are a classic group of chemotherapeutic drugs with a broad spectrum of pharmacological action, including anticancer activity. In this work, reversed-phase high-performance liquid chromato...

Exploring quantitative structure-property relationship models for environmental fate assessment of petroleum hydrocarbons.

The rate and extent of biodegradation of petroleum hydrocarbons in the different aquatic environments is an important element to address. The major avenue for removing petroleum hydrocarbons from the ...

"Data fusion" quantitative read-across structure-activity-activity relationships (q-RASAARs) for the prediction of toxicities of binary and ternary antibiotic mixtures toward three bacterial species.

Antibiotics are often found in the environment as pollutants. They are usually found as mixtures in the environment and may produce toxicity against different ecological species due to joint exposure ...

A data reusability assessment in the nanosafety domain based on the NSDRA framework followed by an exploratory quantitative structure activity relationships (QSAR) modeling targeting cellular viability.

The current effort towards the digital transformation across multiple scientific domains requires data that is Findable, Accessible, Interoperable and Reusable (FAIR). In addition to the FAIR data, wh... To address this challenge, we utilized 34 datasets from the nanosafety domain by exploiting the NanoSafety Data Reusability Assessment (NSDRA) framework, which allowed the annotation and assessment of... Universal regression and classification QSARs reached an 0.86 R... This study reveals that the digitalization of nanosafety knowledge in a reproducible manner has a long way towards its successful pragmatic implementation. The workflow carried out in the study shows ...

Density Functional Theory and Machine Learning-Based Quantitative Structure-Activity Relationship Models Enabling Prediction of Contaminant Degradation Performance with Heterogeneous Peroxymonosulfate Treatments.

Heterogeneous peroxymonosulfate (PMS) treatment is recognized as an effective advanced oxidation process (AOP) for the treatment of organic contaminants. Quantitative structure-activity relationship (...

Systematic computational toxicity analysis of the ozonolytic degraded compounds of azo dyes: Quantitative structure-activity relationship (QSAR) and adverse outcome pathway (AOP) based approach.

The present study identifies and analyses the degraded products of three azo dyes (Reactive Orange 16, Reactive Red 120, and Direct Red 80) and proffers their in silico toxicity predictions. In our pr...