AIMC Topic: HEK293 Cells

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Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell Dec 16, 2020
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which ha...
Kinetics Amino Acid Sequence Wakefulness Sleep Animals Directed Molecular Evolution Protein Binding Humans Serotonin Mice Machine Learning Photons Mice, Inbred C57BL Algorithms Amygdala Brain Serotonin Plasma Membrane Transport Proteins Linear Models HEK293 Cells Behavior, Animal Binding Sites
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MealTime-MS: A Machine Learning-Guided Real-Time Mass Spectrometry Analysis for Protein Identification and Efficient Dynamic Exclusion.

Journal of the American Society for Mass Spectrometry Jun 17, 2020
Mass spectrometry-based proteomics technologies are prime methods for the high-throughput identification of proteins in complex biological samples. Nevertheless, there are still technical limitations that hinder the ability of mass spectrometry to id...
Proteins Supervised Machine Learning Tandem Mass Spectrometry HEK293 Cells Humans Algorithms Proteomics
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CRISPRpred(SEQ): a sequence-based method for sgRNA on target activity prediction using traditional machine learning.

BMC bioinformatics Jun 1, 2020
BACKGROUND: The latest works on CRISPR genome editing tools mainly employs deep learning techniques. However, deep learning models lack explainability and they are harder to reproduce. We were motivated to build an accurate genome editing tool using ...
Humans HEK293 Cells Base Sequence Gene Editing RNA, Guide, CRISPR-Cas Systems ROC Curve Databases, Genetic Machine Learning Area Under Curve CRISPR-Cas Systems Algorithms Reproducibility of Results Deep Learning
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Revealing cytotoxic substructures in molecules using deep learning.

Journal of computer-aided molecular design Apr 16, 2020
In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical a...
Models, Biological Cytotoxins HEK293 Cells Toxicology Drug Discovery Deep Learning Hep G2 Cells Cell Survival Small Molecule Libraries Humans Neural Networks, Computer Software Computer-Aided Design Drug Design
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Synthesis and biological characterization of MnZnEuDyFeO nanoparticles by sonochemical approach.

Materials science & engineering. C, Materials for biological applications Dec 6, 2019
Metallic nanoparticles (NPs) possess unique properties which makes them attractive candidates for various applications especially in field of experimental medicine and drug delivery. Many approaches were developed to synthesize divers and customized ...
HEK293 Cells Escherichia coli Ultrasonic Waves Humans Staphylococcus aureus Anti-Bacterial Agents Metal Nanoparticles Neoplasms HCT116 Cells Antineoplastic Agents
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Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics.

Nature methods Oct 14, 2019
We engineered light-gated channelrhodopsins (ChRs) whose current strength and light sensitivity enable minimally invasive neuronal circuit interrogation. Current ChR tools applied to the mammalian brain require intracranial surgery for transgene deli...
Protein Engineering Optogenetics Channelrhodopsins Animals Mice Mice, Inbred C57BL HEK293 Cells Humans Machine Learning
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Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Nature communications Sep 19, 2019
Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowledge governing guide RNA (gRNA) activity. Here, we perform a genome-scale screen to measure gRNA acti...
INDEL Mutation CRISPR-Cas Systems RNA, Guide, CRISPR-Cas Systems Internet HeLa Cells Animals HEK293 Cells Humans Base Sequence Deep Learning Gene Editing Cell Line, Tumor Clustered Regularly Interspaced Short Palindromic Repeats Promoter Regions, Genetic Mice Endonucleases
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A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation.

Cell Jun 6, 2019
Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequence alone. We trained our model (APARENT, APA REgression NeT) on isoform expression data from over ...
RNA, Messenger Models, Genetic Databases, Genetic Gene Expression Synthetic Biology HEK293 Cells Base Sequence Mutagenesis Humans Transcriptome Deep Learning Polyadenylation RNA-Seq 3' Untranslated Regions RNA Cleavage
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Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

Nature methods May 27, 2019
In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impair...
HEK293 Cells Saccharomyces cerevisiae Drosophila melanogaster Caenorhabditis elegans Humans Neural Networks, Computer Proteome Software Databases, Protein Animals Peptide Fragments Deep Learning Tandem Mass Spectrometry Peptide Library
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PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices.

Journal of neural engineering Apr 10, 2019
OBJECTIVE: Intracellular patch-clamp electrophysiology, one of the most ubiquitous, high-fidelity techniques in biophysics, remains laborious and low-throughput. While previous efforts have succeeded at automating some steps of the technique, here we...
Electrophysiological Phenomena Brain Humans Patch-Clamp Techniques Mice, Inbred C57BL Cells, Cultured Animals Robotics Male HEK293 Cells Mice Organ Culture Techniques
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