AIMC Topic: Cell Line

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Advance of microfluidic flow cytometry enabling high-throughput characterization of single-cell electrical and structural properties.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Oct 10, 2023
This paper reported a micro flow cytometer capable of high-throughput characterization of single-cell electrical and structural features based on constrictional microchannels and deep neural networks. When single cells traveled through microchannels ...
Neural Networks, Computer Microfluidics Electric Impedance Cell Line Flow Cytometry
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Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning.

Scientific reports Sep 27, 2023
There is a consensus about the strong correlation between the elasticity of cells and tissue and their normal, dysplastic, and cancerous states. However, developments in cell mechanics have not seen significant progress in clinical applications. In t...
Cell Line Acoustics Phonons Deep Learning Consensus Neoplasms
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COSMOS: a platform for real-time morphology-based, label-free cell sorting using deep learning.

Communications biology Sep 22, 2023
Cells are the singular building blocks of life, and a comprehensive understanding of morphology, among other properties, is crucial to the assessment of underlying heterogeneity. We developed Computational Sorting and Mapping of Single Cells (COSMOS)...
Cell Movement Cell Line Artificial Intelligence Deep Learning Coloring Agents Cell Separation Humans
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Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio.

Journal of biophotonics Sep 19, 2023
Ensuring the correct use of cell lines is crucial to obtaining reliable experimental results and avoiding unnecessary waste of resources. Raman spectroscopy has been confirmed to be able to identify cell lines, but the collection time is usually 10-3...
Signal-To-Noise Ratio Spectrum Analysis, Raman Cell Line Neural Networks, Computer Deep Learning
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An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data.

BMC bioinformatics Sep 18, 2023
BACKGROUND: The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes. Recently, there have been numerous computational methods developed t...
Humans Animals Genes, Essential Metagenomics Deep Learning Genomics Mice Cell Line
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Discovering the mechanism of action of drugs with a sparse explainable network.

EBioMedicine Aug 24, 2023
BACKGROUND: Although Deep Neural Networks (DDNs) have been successful in predicting the efficacy of cancer drugs, the lack of explainability in their decision-making process is a significant challenge. Previous research proposed mimicking the Gene On...
Mutation Gene Ontology Cell Line Drug Repositioning Humans Artificial Intelligence
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A subcomponent-guided deep learning method for interpretable cancer drug response prediction.

PLoS computational biology Aug 21, 2023
Accurate prediction of cancer drug response (CDR) is a longstanding challenge in modern oncology that underpins personalized treatment. Current computational methods implement CDR prediction by modeling responses between entire drugs and cell lines, ...
Drug Design Antineoplastic Agents Deep Learning Cell Line Humans Neoplasms
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Unraveling the Molecular Puzzle: Exploring Gene Networks across Diverse EMT Status of Cell Lines.

International journal of molecular sciences Aug 14, 2023
Understanding complex disease mechanisms requires a comprehensive understanding of the gene regulatory networks, as complex diseases are often characterized by the dysregulation and dysfunction of molecular networks, rather than abnormalities in sing...
Computational Biology Artificial Intelligence Cell Line Gene Regulatory Networks Epithelial-Mesenchymal Transition
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Hybrid AI models allow label-free identification and classification of pancreatic tumor repopulating cell population.

Biochemical and biophysical research communications Aug 9, 2023
Human pancreatic cancer cell lines harbor a small population of tumor repopulating cells (TRCs). Soft 3D fibrin gel allows efficient selection and growth of these tumorigenic TRCs. However, rapid and high-throughput identification and classification ...
Machine Learning Cell Line Pancreatic Neoplasms Support Vector Machine Humans Pancreas Neural Networks, Computer Carcinogenesis
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An artificial intelligence-based model for cell killing prediction: development, validation and explainability analysis of the ANAKIN model.

Physics in medicine and biology Apr 10, 2023
The present work develops ANAKIN: an. ANAKIN is trained and tested over 513 cell survival experiments with different types of radiation contained in the publicly available PIDE database. We show how ANAKIN accurately predicts several relevant biologi...
Radiobiology Cell Line Artificial Intelligence Relative Biological Effectiveness Cell Death
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