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Cell Line

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Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

PLoS computational biology
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...

Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization Patterns.

Biomolecules
Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful metho...

Integration of human cell lines gene expression and chemical properties of drugs for Drug Induced Liver Injury prediction.

Biology direct
MOTIVATION: Drug-induced liver injury (DILI) is one of the primary problems in drug development. Early prediction of DILI can bring a significant reduction in the cost of clinical trials. In this work we examined whether occurrence of DILI can be pre...

Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data.

PLoS computational biology
The analysis of single-cell genomics data presents several statistical challenges, and extensive efforts have been made to produce methods for the analysis of this data that impute missing values, address sampling issues and quantify and correct for ...

Classification of the mechanism of toxicity as applied to human cell line ECV304.

Computer methods in biomechanics and biomedical engineering
The objective of this study was to identify the pattern of cytotoxicity testing of the human cell line ECV304 using three techniques of an ensemble learning algorithm (bagging, boosting and stacking). The study of cell morphology of ECV304 cell line ...

Repurposing potential of FDA-approved and investigational drugs for COVID-19 targeting SARS-CoV-2 spike and main protease and validation by machine learning algorithm.

Chemical biology & drug design
The present study aimed to assess the repurposing potential of existing antiviral drug candidates (FDA-approved and investigational) against SARS-CoV-2 target proteins that facilitates viral entry and replication into the host body. To evaluate molec...

Artificial intelligence in the early stages of drug discovery.

Archives of biochemistry and biophysics
Although the use of computational methods within the pharmaceutical industry is well established, there is an urgent need for new approaches that can improve and optimize the pipeline of drug discovery and development. In spite of the fact that there...

Deep Learning Benchmarks on L1000 Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics
Gene expression data can offer deep, physiological insights beyond the static coding of the genome alone. We believe that realizing this potential requires specialized, high-capacity machine learning methods capable of using underlying biological str...

Simultaneously Detecting Monoamine Oxidase A and B in Disease Cell/Tissue Samples Using Paper-Based Devices.

ACS applied bio materials
As enzymes in the outer membrane of the mitochondrion, monoamine oxidases (MAOs) can catalyze the oxidative deamination of monoamines in the human body. According to different substrates, MAOs can be divided into MAO-A and MAO-B. The imbalance of the...

Prediction of enhancer-promoter interactions using the cross-cell type information and domain adversarial neural network.

BMC bioinformatics
BACKGROUND: Enhancer-promoter interactions (EPIs) play key roles in transcriptional regulation and disease progression. Although several computational methods have been developed to predict such interactions, their performances are not satisfactory w...