AIMC Topic: Cell Line, Tumor

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A Convolutional Deep Clustering Framework for Gene Expression Time Series.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
The functional or regulatory processes within the cell are explicitly governed by the expression levels of a subset of its genes. Gene expression time series captures activities of individual genes over time and aids revealing underlying cellular dyn...
Computational Biology Cluster Analysis Transcriptome Deep Learning Time Factors Cell Line, Tumor Humans Gene Expression Profiling
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Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Nature cell biology Dec 7, 2021
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose us...
3T3 Cells Humans HEK293 Cells Subcellular Fractions Mice Animals Cell Membrane Deep Learning Electron Microscope Tomography Cell Nucleus Mitochondria Cell Line, Tumor Optical Imaging COS Cells Actins Chlorocebus aethiops Single-Cell Analysis Refractometry Lipid Droplets HeLa Cells Imaging, Three-Dimensional Cell Nucleolus
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Cancer-Cell Deep-Learning Classification by Integrating Quantitative-Phase Spatial and Temporal Fluctuations.

Cells Nov 29, 2021
We present a new classification approach for live cells, integrating together the spatial and temporal fluctuation maps and the quantitative optical thickness map of the cell, as acquired by common-path quantitative-phase dynamic imaging and processe...
Deep Learning Time Factors Cell Line, Tumor Models, Theoretical Humans Algorithms Neoplasms
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A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy.

Bioorganic & medicinal chemistry Nov 27, 2021
Colorectal cancer (CRC) is the third most detected cancer and the second foremost cause of cancer deaths in the world. Intervention targeting p53 provides potential therapeutic strategies, but thus far no p53-based therapy has been successfully trans...
Structure-Activity Relationship Molecular Structure Tumor Suppressor Protein p53 Dihydroergotoxine Drug Discovery Humans Dose-Response Relationship, Drug Antineoplastic Agents Machine Learning Cell Survival Cell Line, Tumor Colorectal Neoplasms Drug Screening Assays, Antitumor Cell Proliferation Molecular Docking Simulation
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Multiview confocal super-resolution microscopy.

Nature Nov 26, 2021
Confocal microscopy remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-d...
Humans Imaginal Discs Single-Cell Analysis Organ Specificity Animals Mice Drosophila melanogaster Deep Learning Microscopy, Confocal Caenorhabditis elegans Cell Line, Tumor Myoblasts Tissue Fixation
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Spatial and temporal dynamics of RhoA activities of single breast tumor cells in a 3D environment revealed by a machine learning-assisted FRET technique.

Experimental cell research Nov 20, 2021
One of the hallmarks of cancer cells is their exceptional ability to migrate within the extracellular matrix (ECM) for gaining access to the circulatory system, a critical step of cancer metastasis. RhoA, a small GTPase, is known to be a key molecula...
Collagen Breast Neoplasms Cell Shape Animals Cell Polarity Rats Humans Time Factors Cell Movement Machine Learning Cell Line, Tumor rhoA GTP-Binding Protein Female Fluorescence Resonance Energy Transfer
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DeepPhospho accelerates DIA phosphoproteome profiling through in silico library generation.

Nature communications Nov 18, 2021
Phosphoproteomics integrating data-independent acquisition (DIA) enables deep phosphoproteome profiling with improved quantification reproducibility and accuracy compared to data-dependent acquisition (DDA)-based phosphoproteomics. DIA data mining he...
Tandem Mass Spectrometry Data Mining Phosphopeptides Deep Learning Cell Line, Tumor Peptide Library Computational Biology Proteomics Proteome Chromatography, Liquid Phosphoproteins Humans Algorithms Computer Simulation Reproducibility of Results
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Cell-morphodynamic phenotype classification with application to cancer metastasis using cell magnetorotation and machine-learning.

PloS one Nov 17, 2021
We define cell morphodynamics as the cell's time dependent morphology. It could be called the cell's shape shifting ability. To measure it we use a biomarker free, dynamic histology method, which is based on multiplexed Cell Magneto-Rotation and Mach...
Cell Line, Tumor Humans Epithelial-Mesenchymal Transition Machine Learning Neoplasm Metastasis Phenotype Cell Shape
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Establishment of a 13 genes-based molecular prediction score model to discriminate the neurotoxic potential of food relevant-chemicals.

Toxicology letters Nov 5, 2021
Although many neurotoxicity prediction studies of food additives have been developed, they are applicable in a qualitative way. We aimed to develop a novel prediction score that is described quantitatively and precisely. We examined cell viability, r...
Neural Networks, Computer Machine Learning Reproducibility of Results Risk Factors Humans Calcium Central Nervous System Diseases Gene Expression Regulation Food Additives Cell Line, Tumor Food Contamination Reactive Oxygen Species Cell Survival Neural Stem Cells
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Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging.

NMR in biomedicine Oct 19, 2021
Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often...
Humans Magnetic Resonance Imaging Animals Neural Networks, Computer Deep Learning Female Cell Line, Tumor Breast Neoplasms Mice
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