AIMC Topic: Cell Physiological Phenomena

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Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

BMC bioinformatics Jun 6, 2015
BACKGROUND: People with an autistic spectrum disorder (ASD) display a variety of characteristic behavioral traits, including impaired social interaction, communication difficulties and repetitive behavior. This complex neurodevelopment disorder is kn...
Neural Cell Adhesion Molecules Synaptic Potentials Cell Adhesion Molecules, Neuronal Models, Molecular Synapses High-Throughput Nucleotide Sequencing Rats Nerve Tissue Proteins Social Behavior Calcium-Binding Proteins Cell Physiological Phenomena Membrane Potentials Gene Ontology Animals Genomics Phenotype Genome Mice Humans Autistic Disorder
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flowCL: ontology-based cell population labelling in flow cytometry.

Bioinformatics (Oxford, England) Dec 6, 2014
MOTIVATION: Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrat...
Leukocyte Common Antigens Flow Cytometry Software Gene Ontology Receptors, CCR7 Algorithms Immunophenotyping Cell Physiological Phenomena Humans
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MPI-VGAE: protein-metabolite enzymatic reaction link learning by variational graph autoencoders.

Briefings in bioinformatics Jul 20, 2023
Enzymatic reactions are crucial to explore the mechanistic function of metabolites and proteins in cellular processes and to understand the etiology of diseases. The increasing number of interconnected metabolic reactions allows the development of in...
Metabolic Networks and Pathways Cell Physiological Phenomena Molecular Docking Simulation Machine Learning
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A Preliminary Study on Retro-reconstruction of Cell Fission Dynamic Process using Convolutional LSTM Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Cell morphological analysis has great impact towards our understanding of cell biology. It is however technically challenging to acquire the complete process of cell cycles under microscope inspection. Using convolutional long short-term memory (Conv...
Neural Networks, Computer Cell Physiological Phenomena
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Which image-based phenotypes are most promising for using AI to understand cellular functions and why?

Cell systems May 19, 2021
Cell Physiological Phenomena Phenotype Artificial Intelligence
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Evaluation of Stein-O'Brien et al.: To See a World in a Grain of Sand-How to Reveal a Common Latent Space through Multiple Platform Omics Data.

Cell systems Jun 26, 2019
One snapshot of the peer review process for "Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species" (Stein-O'Brien et al., 2019).
Cell Physiological Phenomena Cells Machine Learning
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Conceptual Challenges of the Systemic Approach in Understanding Cell Differentiation.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2018
The cells of a multicellular organism are derived from a single zygote and genetically identical. Yet, they are phenotypically very different. This difference is the result of a process commonly called cell differentiation. How the phenotypic diversi...
Humans Phenotype Regeneration Biological Ontologies Cell Differentiation Animals Biochemical Phenomena Cell Physiological Phenomena
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Integrated pillar scatterers for speeding up classification of cell holograms.

Optics express Nov 27, 2017
The computational power required to classify cell holograms is a major limit to the throughput of label-free cell sorting based on digital holographic microscopy. In this work, a simple integrated photonic stage comprising a collection of silica pill...
Cell Physiological Phenomena Machine Learning Holography Algorithms
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