AIMC Topic: Cell Line

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Deep learning techniques and mathematical modeling allow 3D analysis of mitotic spindle dynamics.

The Journal of cell biology Mar 2, 2023
Time-lapse microscopy movies have transformed the study of subcellular dynamics. However, manual analysis of movies can introduce bias and variability, obscuring important insights. While automation can overcome such limitations, spatial and temporal...
Deep Learning Imaging, Three-Dimensional Fluorescent Dyes Cytoplasm Spindle Apparatus Models, Theoretical Cell Line
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A deep learning workflow for quantification of micronuclei in DNA damage studies in cultured cancer cell lines: A proof of principle investigation.

Computer methods and programs in biomedicine Feb 26, 2023
The cytokinesis block micronucleus assay is widely used for measuring/scoring/counting micronuclei, a marker of genome instability in cultured and primary cells. Though a gold standard method, this is a laborious and time-consuming process with perso...
Workflow Micronucleus Tests Neoplasms Deep Learning Cell Line DNA Damage Humans
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DeepSide: A Deep Learning Approach for Drug Side Effect Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2023
Drug failures due to unforeseen adverse effects at clinical trials pose health risks for the participants and lead to substantial financial losses. Side effect prediction algorithms have the potential to guide the drug design process. LINCS L1000 dat...
Neural Networks, Computer Algorithms Humans Drug-Related Side Effects and Adverse Reactions Deep Learning Cell Line
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Prediction of radiosensitivity and radiocurability using a novel supervised artificial neural network.

BMC cancer Dec 1, 2022
BACKGROUND: Radiotherapy has been widely used to treat various cancers, but its efficacy depends on the individual involved. Traditional gene-based machine-learning models have been widely used to predict radiosensitivity. However, there is still a l...
Algorithms Cell Line Neural Networks, Computer Machine Learning Radiation Tolerance Humans
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Perioperative Red Cell Line Trend following Robot-Assisted Radical Prostatectomy for Prostate Cancer.

Medicina (Kaunas, Lithuania) Oct 25, 2022
Background and Objective: Blood loss represents a long-standing concern of radical prostatectomy (RP). This study aimed to assess how red line cell values changed following robot-assisted radical prostatectomy (RARP) for prostate cancer (PCa). Materi...
Robotic Surgical Procedures Erythrocytes Prostatectomy Robotics Prostatic Neoplasms Treatment Outcome Cell Line Humans Male
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Deep learning for de-convolution of Smad2 versus Smad3 binding sites.

BMC genomics Jul 20, 2022
BACKGROUND: The transforming growth factor beta-1 (TGF β-1) cytokine exerts both pro-tumor and anti-tumor effects in carcinogenesis. An increasing body of literature suggests that TGF β-1 signaling outcome is partially dependent on the regulatory tar...
Deep Learning Binding Sites Smad2 Protein Transforming Growth Factor beta Signal Transduction Smad3 Protein Cell Line
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EPI-Mind: Identifying Enhancer-Promoter Interactions Based on Transformer Mechanism.

Interdisciplinary sciences, computational life sciences May 28, 2022
MOTIVATION: Enhancer-Promoter Interactions (EPIs) is an essential step in the gene regulation process. However, the detection of EPIs by traditional wet experimental techniques is time-consuming and expensive. Thus, computational methods would be ver...
Gene Expression Regulation Promoter Regions, Genetic Regulatory Sequences, Nucleic Acid Neural Networks, Computer Cell Line
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Integrating Molecular Graph Data of Drugs and Multiple -Omic Data of Cell Lines for Drug Response Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Apr 1, 2022
Previous studies have either learned drug's features from their string or numeric representations, which are not natural forms of drugs, or only used genomic data of cell lines for the drug response prediction problem. Here, we proposed a deep learni...
Genomics Cell Line Neural Networks, Computer
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A pan-CRISPR analysis of mammalian cell specificity identifies ultra-compact sgRNA subsets for genome-scale experiments.

Nature communications Feb 2, 2022
A genetic knockout can be lethal to one human cell type while increasing growth rate in another. This context specificity confounds genetic analysis and prevents reproducible genome engineering. Genome-wide CRISPR compendia across most common human c...
CRISPR-Cas Systems Clustered Regularly Interspaced Short Palindromic Repeats Genomics Cell Line Synthetic Lethal Mutations Gene Knockout Techniques Humans Genetic Engineering Machine Learning Animals
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Machine Learning Models for Predicting Cytotoxicity of Nanomaterials.

Chemical research in toxicology Jan 14, 2022
The wide application of nanomaterials in consumer and medical products has raised concerns about their potential adverse effects on human health. Thus, more and more biological assessments regarding the toxicity of nanomaterials have been performed. ...
Humans Cell Line Machine Learning Nanostructures Cell Survival
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