AIMC Topic: HEK293 Cells

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Deep learning large-scale drug discovery and repurposing.

Nature computational science Aug 21, 2024
Large-scale drug discovery and repurposing is challenging. Identifying the mechanism of action (MOA) is crucial, yet current approaches are costly and low-throughput. Here we present an approach for MOA identification by profiling changes in mitochon...
Drug Discovery Deep Learning Image Processing, Computer-Assisted Biological Products Humans Mitochondria HEK293 Cells Cells Time-Lapse Imaging Cell Line Drug Repositioning Pharmaceutical Preparations
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Synergistic Polymer Blending Informs Efficient Terpolymer Design and Machine Learning Discerns Performance Trends for pDNA Delivery.

Bioconjugate chemistry Jun 26, 2024
Cationic polymers offer an alternative to viral vectors in nucleic acid delivery. However, the development of polymer vehicles capable of high transfection efficiency and minimal toxicity has remained elusive, and continued exploration of the vast de...
Humans Machine Learning Transfection HEK293 Cells Plasmids Cell Survival Gene Transfer Techniques DNA Polymers
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Optimizing 5'UTRs for mRNA-delivered gene editing using deep learning.

Nature communications Jun 20, 2024
mRNA therapeutics are revolutionizing the pharmaceutical industry, but methods to optimize the primary sequence for increased expression are still lacking. Here, we design 5'UTRs for efficient mRNA translation using deep learning. We perform polysome...
5' Untranslated Regions Polyribosomes Humans Deep Learning RNA, Messenger Cell Line HEK293 Cells Gene Editing Protein Biosynthesis
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BiLSTM- and CNN-Based m6A Modification Prediction Model for circRNAs.

Molecules (Basel, Switzerland) May 21, 2024
m6A methylation, a ubiquitous modification on circRNAs, exerts a profound influence on RNA function, intracellular behavior, and diverse biological processes, including disease development. While prediction algorithms exist for mRNA m6A modifications...
Neural Networks, Computer Algorithms Computational Biology Methylation HEK293 Cells Adenosine RNA, Circular Humans
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Quantitative profiling N1-methyladenosine (m1A) RNA methylation from Oxford nanopore direct RNA sequencing data.

Methods (San Diego, Calif.) May 18, 2024
With the recent advanced direct RNA sequencing technique that proposed by the Oxford Nanopore Technologies, RNA modifications can be detected and profiled in a simple and straightforward manner. Majority nanopore-based modification studies were devot...
Sequence Analysis, RNA Workflow RNA Methylation Humans Machine Learning Algorithms Nanopore Sequencing RNA Methylation HEK293 Cells Adenosine RNA Processing, Post-Transcriptional
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Nm-Nano: a machine learning framework for transcriptome-wide single-molecule mapping of 2´-O-methylation (Nm) sites in nanopore direct RNA sequencing datasets.

RNA biology May 17, 2024
2´-O-methylation (Nm) is one of the most abundant modifications found in both mRNAs and noncoding RNAs. It contributes to many biological processes, such as the normal functioning of tRNA, the protection of mRNA against degradation by the decapping a...
RNA Processing, Post-Transcriptional Nanopore Sequencing Computational Biology RNA, Messenger Humans HeLa Cells Sequence Analysis, RNA Machine Learning Methylation Software HEK293 Cells Transcriptome Nanopores
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Deep hybrid modeling of a HEK293 process: Combining long short-term memory networks with first principles equations.

Biotechnology and bioengineering Feb 11, 2024
The combination of physical equations with deep learning is becoming a promising methodology for bioprocess digitalization. In this paper, we investigate for the first time the combination of long short-term memory (LSTM) networks with first principl...
Neural Networks, Computer Kidney HEK293 Cells Humans
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Numerical learning of deep features from drug-exposed cell images to calculate IC50 without staining.

Scientific reports Apr 22, 2022
To facilitate rapid determination of cellular viability caused by the inhibitory effect of drugs, numerical deep learning algorithms was used for unlabeled cell culture images captured by a light microscope as input. In this study, A549, HEK293, and ...
Humans Neural Networks, Computer Doxorubicin Algorithms Inhibitory Concentration 50 Image Processing, Computer-Assisted HEK293 Cells Staining and Labeling
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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...
COS Cells Deep Learning Lipid Droplets Cell Line, Tumor HeLa Cells Single-Cell Analysis Mice Refractometry 3T3 Cells Humans Mitochondria HEK293 Cells Cell Nucleolus Imaging, Three-Dimensional Animals Actins Chlorocebus aethiops Cell Nucleus Subcellular Fractions Electron Microscope Tomography Cell Membrane Optical Imaging
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Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

International journal of molecular sciences Oct 26, 2021
Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulat...
Receptors, Odorant In Vitro Techniques User-Computer Interface Support Vector Machine Bayes Theorem Humans Drug Evaluation, Preclinical Male Machine Learning Ligands Molecular Docking Simulation Female HEK293 Cells Drug Design Drug Discovery
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