AIMC Topic: Cell Line, Tumor

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Automated evaluation of tumor spheroid behavior in 3D culture using deep learning-based recognition.

Biomaterials
Three-dimensional in vitro tumor models provide more physiologically relevant responses to drugs than 2D models, but the lack of proper evaluation indices and the laborious quantitation of tumor behavior in 3D have limited the use of 3D tumor models ...

Deep generative neural network for accurate drug response imputation.

Nature communications
Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outc...

A machine learning-based gene signature of response to the novel alkylating agent LP-184 distinguishes its potential tumor indications.

BMC bioinformatics
BACKGROUND: Non-targeted cytotoxics with anticancer activity are often developed through preclinical stages using response criteria observed in cell lines and xenografts. A panel of the NCI-60 cell lines is frequently the first line to define tumor t...

Systematic characterization of mutations altering protein degradation in human cancers.

Molecular cell
The ubiquitin-proteasome system (UPS) is the primary route for selective protein degradation in human cells. The UPS is an attractive target for novel cancer therapies, but the precise UPS genes and substrates important for cancer growth are incomple...

Identifying metastatic ability of prostate cancer cell lines using native fluorescence spectroscopy and machine learning methods.

Scientific reports
Metastasis is the leading cause of mortalities in cancer patients due to the spreading of cancer cells to various organs. Detecting cancer and identifying its metastatic potential at the early stage is important. This may be achieved based on the qua...

Machine-Learning Provides Patient-Specific Prediction of Metastatic Risk Based on Innovative, Mechanobiology Assay.

Annals of biomedical engineering
Cancer mortality is mostly related to metastasis. Metastasis is currently prognosed via histopathology, disease-statistics, or genetics; those are potentially inaccurate, not rapidly available and require known markers. We had developed a rapid (~ 2 ...

MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors.

Genome biology
Although genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present Methyla...

Phytochemical, antibacterial, antioxidant and cytoxicity investigation of .

Zeitschrift fur Naturforschung. C, Journal of biosciences
The phytochemical investigation of led to the isolation of 18 known compounds of which were four flavones, three anthraquinones, one phenyl propanoic derivative, five triterpenoids, four steroids and a mixture of glucose. Luteolin () and soranjidiol...

Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments.

Nature communications
Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy's utility. Recently, it has been shown t...

Super resolution microscopy and deep learning identify Zika virus reorganization of the endoplasmic reticulum.

Scientific reports
The endoplasmic reticulum (ER) is a complex subcellular organelle composed of diverse structures such as tubules, sheets and tubular matrices. Flaviviruses such as Zika virus (ZIKV) induce reorganization of ER membranes to facilitate viral replicatio...