AI Medical Compendium Topic

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Cell Movement

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Network Analysis of Integrin Adhesion Complexes.

Methods in molecular biology (Clifton, N.J.)
Cell-surface adhesion receptors mediate interactions with the extracellular matrix (ECM) to control many fundamental aspects of cell behavior, including cell migration, survival, and proliferation. Integrin adhesion receptors recruit structural and s...

Deep Convolutional and Recurrent Neural Networks for Cell Motility Discrimination and Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Cells in culture display diverse motility behaviors that may reflect differences in cell state and function, providing motivation to discriminate between different motility behaviors. Current methods to do so rely upon manual feature engineering. How...

Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation.

Nature communications
The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell...

Detection of cellular micromotion by advanced signal processing.

Scientific reports
Cellular micromotion-a tiny movement of cell membranes on the nm-µm scale-has been proposed as a pathway for inter-cellular signal transduction and as a label-free proxy signal to neural activity. Here we harness several recent approaches of signal p...

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 ...

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

Pharmacological research
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...

The anti-ageing effects of a natural peptide discovered by artificial intelligence.

International journal of cosmetic science
OBJECTIVE: As skin ages, impaired extracellular matrix (ECM) protein synthesis and increased action of degradative enzymes manifest as atrophy, wrinkling and laxity. There is mounting evidence for the functional role of exogenous peptides across many...

Deep learning guided image-based droplet sorting for on-demand selection and analysis of single cells and 3D cell cultures.

Lab on a chip
Uncovering the heterogeneity of cellular populations and multicellular constructs is a long-standing goal in fields ranging from antimicrobial resistance to cancer research. Emerging technology platforms such as droplet microfluidics hold the promise...

Identification of Synthetic Activators of Cancer Cell Migration by Hybrid Deep Learning.

Chembiochem : a European journal of chemical biology
Deep convolutional neural networks (CNNs) are a method of choice for image recognition. Herein a hybrid CNN approach is presented for molecular pattern recognition in drug discovery. Using self-organizing map images of molecular pharmacophores as inp...

Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Robust and reproducible profiling of cell lines is essential for phenotypic screening assays. The goals of this study were to determine robust and reproducible optical phase signatures of cell lines for classification with machine learning and to cor...