AIMC Topic: Biological Assay
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Disease variant prediction with deep generative models of evolutionary data.
Nature
Oct 27, 2021
Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences. In principle, computational...
Prediction of Micronucleus Assay Outcome Using In Vivo Activity Data and Molecular Structure Features.
Applied biochemistry and biotechnology
Oct 20, 2021
In vivo micronucleus assay is the widely used genotoxic test to determine the extent of chromosomal aberrations caused by the chemicals in human beings, which plays a significant role in the drug discovery paradigm. To reduce the uncertainties of the...
ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities.
Journal of chemical information and modeling
Jun 21, 2021
Computational methods such as machine learning approaches have a strong track record of success in predicting the outcomes of in vitro assays. In contrast, their ability to predict in vivo endpoints is more limited due to the high number of parameter...
Machine Learning Strategies When Transitioning between Biological Assays.
Journal of chemical information and modeling
Jun 21, 2021
Machine learning is widely used in drug development to predict activity in biological assays based on chemical structure. However, the process of transitioning from one experimental setup to another for the same biological endpoint has not been exten...
A Novel Method to Gently Mix and Uniformly Suspend Particulates for Automated Assays.
SLAS technology
May 6, 2021
The SpinVessel system provides a methodology using pulsed radial flow to gently mix and uniformly suspend particulates (cells, magnetic beads, silica beads, and microcarrier beads) for automated assays. SpinVessels are well suited for aliquoting on r...
Multi-label classification and label dependence in in silico toxicity prediction.
Toxicology in vitro : an international journal published in association with BIBRA
Apr 9, 2021
Most computational predictive models are specifically trained for a single toxicity endpoint and lack the ability to learn dependencies between endpoints, such as those targeting similar biological pathways. In this study, we compare the performance ...
Highly Sensitive Detection of Chemically Modified Thio-Organophosphates by an Enzymatic Biosensing Device: An Automated Robotic Approach.
Sensors (Basel, Switzerland)
Mar 2, 2020
Pesticides represent some of the most common man-made chemicals in the world. Despite their unquestionable utility in the agricultural field and in the prevention of pest infestation in public areas of cities, pesticides and their biotransformation p...
A multicolor multiplex lateral flow assay for high-sensitivity analyte detection using persistent luminescent nanophosphors.
Analytical methods : advancing methods and applications
Dec 10, 2019
Incorporating two persistent luminescent nanophosphors (PLNPs), green-emitting SrAlO:Eu,Dy (SAO) and blue-emitting (SrBa)MgSiO:Eu,Dy (SBMSO), in a single lateral flow assay (LFA) establishes a luminescence-based, multiplex point-of-need test capable ...
All-Assay-Max2 pQSAR: Activity Predictions as Accurate as Four-Concentration ICs for 8558 Novartis Assays.
Journal of chemical information and modeling
Sep 26, 2019
Profile-quantitative structure-activity relationship (pQSAR) is a massively multitask, two-step machine learning method with unprecedented scope, accuracy, and applicability domain. In step one, a "profile" of conventional single-assay random forest ...
Metasurface-Based Molecular Biosensing Aided by Artificial Intelligence.
Angewandte Chemie (International ed. in English)
Aug 8, 2019
Molecular spectroscopy provides unique information on the internal structure of biological materials by detecting the characteristic vibrational signatures of their constituent chemical bonds at infrared frequencies. Nanophotonic antennas and metasur...
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