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Cell Proliferation

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DeepciRGO: functional prediction of circular RNAs through hierarchical deep neural networks using heterogeneous network features.

BMC bioinformatics
BACKGROUND: Circular RNAs (circRNAs) are special noncoding RNA molecules with closed loop structures. Compared with the traditional linear RNA, circRNA is more stable and not easily degraded. Many studies have shown that circRNAs are involved in the ...

Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.

Scientific reports
Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomar...

Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Göttingen Minipigs.

Toxicologic pathology
Quantitative assessment of proliferation can be an important endpoint in toxicologic pathology. Traditionally, cell proliferation is quantified by labor-intensive manual counting of positive and negative cells after immunohistochemical staining for p...

Hypothesis-free deep survival learning applied to the tumour microenvironment in gastric cancer.

The journal of pathology. Clinical research
The biological complexity reflected in histology images requires advanced approaches for unbiased prognostication. Machine learning and particularly deep learning methods are increasingly applied in the field of digital pathology. In this study, we p...

Intelligent image-based deformation-assisted cell sorting with molecular specificity.

Nature methods
Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on...

An Automated Segmentation Pipeline for Intratumoural Regions in Animal Xenografts Using Machine Learning and Saturation Transfer MRI.

Scientific reports
Saturation transfer MRI can be useful in the characterization of different tumour types. It is sensitive to tumour metabolism, microstructure, and microenvironment. This study aimed to use saturation transfer to differentiate between intratumoural re...

Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions.

BioMed research international
Breast cancer is the most diagnosed cancer among women around the world. The development of computer-aided diagnosis tools is essential to help pathologists to accurately interpret and discriminate between malignant and benign tumors. This paper prop...

Single-cell dispensing and 'real-time' cell classification using convolutional neural networks for higher efficiency in single-cell cloning.

Scientific reports
Single-cell dispensing for automated cell isolation of individual cells has gained increased attention in the biopharmaceutical industry, mainly for production of clonal cell lines. Here, machine learning for classification of cell images is applied ...

Propofol affects the growth and metastasis of pancreatic cancer via ADAM8.

Pharmacological reports : PR
BACKGROUND: Anesthesia is a major component of surgery and recently considered an important regulator of cell phenotypes. Here we aimed to investigate propofol, an anesthesia drug, in suppressing pancreatic cancer (PDAC), focusing on A disintegrin an...