AIMC Topic: Gene Knockdown Techniques

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Comparing robotic and manual injection methods in zebrafish embryos for high-throughput RNA silencing using CRISPR-RfxCas13d.

BioTechniques Feb 29, 2024
In this study, the authors compared the efficiency of automated robotic and manual injection methods for the CRISPR-RfxCas13d (CasRx) system for mRNA knockdown and Cas9-mediated DNA targeting in zebrafish embryos. They targeted the no tail () gene as...
Animals RNA, Messenger Embryo, Nonmammalian Gene Knockdown Techniques Microinjections RNA Interference Robotics CRISPR-Cas Systems Zebrafish Zebrafish Proteins
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Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.

STAR protocols Oct 23, 2021
MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a mach...
Humans Machine Learning Transcriptome Algorithms Cell Culture Techniques Gene Regulatory Networks Cells, Cultured Gene Knockdown Techniques MicroRNAs Gene Expression Profiling Workflow Islets of Langerhans
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DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment.

PLoS computational biology Oct 5, 2021
Drug treatment induces cell type specific transcriptional programs, and as the number of combinations of drugs and cell types grows, the cost for exhaustive screens measuring the transcriptional drug response becomes intractable. We developed DeepCel...
Gene Knockdown Techniques PC-3 Cells Humans Computational Biology Antineoplastic Agents Unsupervised Machine Learning Transcriptome MCF-7 Cells Deep Learning
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Accurate cancer phenotype prediction with AKLIMATE, a stacked kernel learner integrating multimodal genomic data and pathway knowledge.

PLoS computational biology Apr 16, 2021
Advancements in sequencing have led to the proliferation of multi-omic profiles of human cells under different conditions and perturbations. In addition, many databases have amassed information about pathways and gene "signatures"-patterns of gene ex...
Humans Machine Learning Phenotype Survival Analysis Gene Knockdown Techniques Neoplasms Cell Line, Tumor Genomics RNA, Small Interfering
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Shape-to-graph mapping method for efficient characterization and classification of complex geometries in biological images.

PLoS computational biology Sep 3, 2020
With the ever-increasing quality and quantity of imaging data in biomedical research comes the demand for computational methodologies that enable efficient and reliable automated extraction of the quantitative information contained within these image...
Gene Knockdown Techniques Human Umbilical Vein Endothelial Cells Cytological Techniques Pattern Recognition, Automated Humans Machine Learning Algorithms Cell Line, Tumor Image Processing, Computer-Assisted Computational Biology Decision Trees
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A deep learning framework to predict binding preference of RNA constituents on protein surface.

Nature communications Oct 30, 2019
Protein-RNA interaction plays important roles in post-transcriptional regulation. However, the task of predicting these interactions given a protein structure is difficult. Here we show that, by leveraging a deep learning model NucleicNet, attributes...
Ribonuclease III Protein Binding Argonaute Proteins Mice Cytosine Guanine Humans Ribose RNA-Binding Proteins RNA, Small Interfering Gene Knockdown Techniques Animals Area Under Curve RNA Adenine Deep Learning Phosphates ROC Curve Uracil
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Min3: Predict microRNA target gene using an improved binding-site representation method and support vector machine.

Journal of bioinformatics and computational biology Oct 1, 2019
MicroRNAs are single-stranded noncoding RNAs known to down-regulate target genes at the protein or mRNA level. Computational prediction of targets is essential for elucidating the detailed functions of microRNA. However, prediction specificity and se...
RNA, Messenger Models, Genetic Support Vector Machine Databases, Genetic MicroRNAs HeLa Cells Gene Knockdown Techniques Humans Software Computational Biology Binding Sites Gene Knockout Techniques 3' Untranslated Regions
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Model-based unsupervised learning informs metformin-induced cell-migration inhibition through an AMPK-independent mechanism in breast cancer.

Oncotarget Apr 18, 2017
We demonstrate that model-based unsupervised learning can uniquely discriminate single-cell subpopulations by their gene expression distributions, which in turn allow us to identify specific genes for focused functional studies. This method was appli...
cdc42 GTP-Binding Protein AMP-Activated Protein Kinases Metformin Gene Knockdown Techniques Humans Cell Line, Tumor Signal Transduction Female Cell Movement Computational Biology Breast Neoplasms Cluster Analysis Gene Expression Profiling Gene Expression Regulation, Neoplastic Unsupervised Machine Learning
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A Dual Targeting Drug Delivery System for Penetrating Blood-Brain Barrier and Selectively Delivering siRNA to Neurons for Alzheimer's Disease Treatment.

Current pharmaceutical biotechnology Jan 1, 2017
BACKGROUND: Alzheimer's disease (AD) is one of most serious threats to human beings, however, the treatment is hindered by blood-brain barrier and poor intra-brain cell selectivity.
Molecular Targeted Therapy PC12 Cells Drug Carriers Animals Gene Knockdown Techniques Alzheimer Disease RNA, Small Interfering Humans Nanoparticles Neurons Permeability Blood-Brain Barrier Rats Amyloid Precursor Protein Secretases Mice, Nude Drug Delivery Systems Aspartic Acid Endopeptidases
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