AI Medical Compendium Journal:
SLAS discovery : advancing life sciences R & D

Showing 1 to 10 of 16 articles

Outline and background for the EU-OS solubility prediction challenge.

SLAS discovery : advancing life sciences R & D
In June 2022, EU-OS came to the decision to make public a solubility data set of 100+K compounds obtained from several of the EU-OS proprietary screening compound collections. Leveraging on the interest of SLAS for screening scientific development it...

The openOCHEM consensus model is the best-performing open-source predictive model in the First EUOS/SLAS joint compound solubility challenge.

SLAS discovery : advancing life sciences R & D
The EUOS/SLAS challenge aimed to facilitate the development of reliable algorithms to predict the aqueous solubility of small molecules using experimental data from 100 K compounds. In total, hundred teams took part in the challenge to predict low, m...

Virtual plates: Getting the best out of high content screens.

SLAS discovery : advancing life sciences R & D
High content screening (HCS) is becoming widely adopted as a high throughput screening modality, using hundred-of-thousands compounds library. The use of machine learning and artificial intelligence in image analysis is amplifying this trend. Another...

Graph neural networks for the identification of novel inhibitors of a small RNA.

SLAS discovery : advancing life sciences R & D
MicroRNAs (miRNAs) play a crucial role in post-transcriptional gene regulation and have been implicated in various diseases, including cancers and lung disease. In recent years, Graph Neural Networks (GNNs) have emerged as powerful tools for analyzin...

FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines.

SLAS discovery : advancing life sciences R & D
The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potent...

DeepTI: A deep learning-based framework decoding tumor-immune interactions for precision immunotherapy in oncology.

SLAS discovery : advancing life sciences R & D
BACKGROUND: Increasing evidence suggests the immunomodulatory potential of genes in oncology. But the identification of immune attributes of genes is costly and time-consuming, which leads to an urgent demand to develop a prediction model.

Deep Learning Image Analysis of High-Throughput Toxicology Assay Images.

SLAS discovery : advancing life sciences R & D
High-throughput chemical screening approaches often employ microscopy to capture photomicrographs from multi-well cell culture plates, generating thousands of images that require time-consuming human analysis. To automate this subjective and time-con...

Evaluating Very Deep Convolutional Neural Networks for Nucleus Segmentation from Brightfield Cell Microscopy Images.

SLAS discovery : advancing life sciences R & D
Advances in microscopy have increased output data volumes, and powerful image analysis methods are required to match. In particular, finding and characterizing nuclei from microscopy images, a core cytometry task, remains difficult to automate. While...

Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening.

SLAS discovery : advancing life sciences R & D
There has been an increase in the use of machine learning and artificial intelligence (AI) for the analysis of image-based cellular screens. The accuracy of these analyses, however, is greatly dependent on the quality of the training sets used for bu...