AIMC Topic: Cell Line

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Cellular level robotic surgery: Nanodissection of intermediate filaments in live keratinocytes.

Nanomedicine : nanotechnology, biology, and medicine Sep 6, 2014
We present the nanosurgery on the cytoskeleton of live cells using AFM based nanorobotics to achieve adhesiolysis and mimic the effect of pathophysiological modulation of intercellular adhesion. Nanosurgery successfully severs the intermediate filame...
Stress, Mechanical Cations Nanomedicine Microscopy, Atomic Force Desmosomes Cell Line Surgery, Computer-Assisted Cell Adhesion Robotics Autoimmune Diseases Humans Cytoskeleton Nanostructures Keratinocytes Apoptosis Intermediate Filaments
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Robotic adherent cell injection for characterizing cell-cell communication.

IEEE transactions on bio-medical engineering Jul 24, 2014
Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells (e.g., cancer cells and cardiomyocytes) due to their smaller size, highly irregular morphology, small t...
Myocytes, Cardiac Cell Adhesion Equipment Failure Analysis Man-Machine Systems Cell Separation Equipment Design Cell Communication Animals Cell Line Micromanipulation Cell Transplantation Mice Robotics Microinjections
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MIRACN: a residual convolutional neural network for predicting cell line specific functional regulatory variants.

Briefings in bioinformatics Mar 4, 2025
In post-genome-wide association study era, interpretation of noncoding variants remains a significant challenge due to their complexity and the limited understanding of their functions. Here, we developed MIRACN, a novel residual convolutional neural...
Humans Neural Networks, Computer Computational Biology Cell Line Genetic Variation Convolutional Neural Networks Genome-Wide Association Study
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Improving drug response prediction via integrating gene relationships with deep learning.

Briefings in bioinformatics Mar 27, 2024
Predicting the drug response of cancer cell lines is crucial for advancing personalized cancer treatment, yet remains challenging due to tumor heterogeneity and individual diversity. In this study, we present a deep learning-based framework named Dee...
Deep Learning Cell Line Neural Networks, Computer Humans Neoplasms
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Unveiling human origins of replication using deep learning: accurate prediction and comprehensive analysis.

Briefings in bioinformatics Nov 22, 2023
Accurate identification of replication origins (ORIs) is crucial for a comprehensive investigation into the progression of human cell growth and cancer therapy. Here, we proposed a computational approach Ori-FinderH, which can efficiently and precise...
Deep Learning Cell Line Humans
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DeepICSH: a complex deep learning framework for identifying cell-specific silencers and their strength from the human genome.

Briefings in bioinformatics Sep 20, 2023
Silencers are noncoding DNA sequence fragments located on the genome that suppress gene expression. The variation of silencers in specific cells is closely related to gene expression and cancer development. Computational approaches that exclusively r...
Humans Deep Learning Multiomics Genome, Human Epigenesis, Genetic Cell Line
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MSDRP: a deep learning model based on multisource data for predicting drug response.

Bioinformatics (Oxford, England) Sep 2, 2023
MOTIVATION: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning a...
Algorithms Deep Learning Humans Machine Learning Cell Line Drug-Related Side Effects and Adverse Reactions
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Automatic recognition of protein subcellular location patterns in single cells from immunofluorescence images based on deep learning.

Briefings in bioinformatics Jan 19, 2023
With the improvement of single-cell measurement techniques, there is a growing awareness that individual differences exist among cells, and protein expression distribution can vary across cells in the same tissue or cell line. Pinpointing the protein...
Algorithms Deep Learning Proteins Cell Line Fluorescent Antibody Technique Humans
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A systematic assessment of deep learning methods for drug response prediction: from in vitro to clinical applications.

Briefings in bioinformatics Jan 19, 2023
Drug response prediction is an important problem in personalized cancer therapy. Among various newly developed models, significant improvement in prediction performance has been reported using deep learning methods. However, systematic comparisons of...
Cell Line Humans Deep Learning
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DeepCellEss: cell line-specific essential protein prediction with attention-based interpretable deep learning.

Bioinformatics (Oxford, England) Jan 1, 2023
MOTIVATION: Protein essentiality is usually accepted to be a conditional trait and strongly affected by cellular environments. However, existing computational methods often do not take such characteristics into account, preferring to incorporate all ...
Deep Learning Computational Biology Proteins Amino Acid Sequence Cell Line Software
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