AIMC Topic: RNA-Seq

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PACIFIC: a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses.

Scientific reports Feb 5, 2021
Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated method to identify viral co-infections in patient RNA-seq data. We developed PACIFIC, a deep-learning alg...
SARS-CoV-2 Sensitivity and Specificity Deep Learning RNA-Seq Humans Neural Networks, Computer COVID-19 RNA Virus Infections Coinfection Coronaviridae COVID-19 Testing Metapneumovirus Orthomyxoviridae Rhinovirus RNA Viruses
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Verifying explainability of a deep learning tissue classifier trained on RNA-seq data.

Scientific reports Jan 29, 2021
For complex machine learning (ML) algorithms to gain widespread acceptance in decision making, we must be able to identify the features driving the predictions. Explainability models allow transparency of ML algorithms, however their reliability with...
Genotype Organ Specificity Algorithms Deep Learning RNA-Seq Humans Neural Networks, Computer Machine Learning
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Machine Learning Analysis of Longevity-Associated Gene Expression Landscapes in Mammals.

International journal of molecular sciences Jan 22, 2021
One of the important questions in aging research is how differences in transcriptomics are associated with the longevity of various species. Unfortunately, at the level of individual genes, the links between expression in different organs and maximum...
Bayes Theorem Gene Expression Mammals Linear Models Models, Genetic Liver Regression Analysis Tissue Distribution Longevity Algorithms Brain Animals Aging Gene Expression Profiling Transcriptome RNA-Seq Computational Biology Humans Machine Learning
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Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data.

PLoS computational biology Jan 7, 2021
The analysis of single-cell genomics data presents several statistical challenges, and extensive efforts have been made to produce methods for the analysis of this data that impute missing values, address sampling issues and quantify and correct for ...
Animals Single-Cell Analysis RNA-Seq Mice Humans Algorithms Supervised Machine Learning Saccharomyces cerevisiae Genomics Databases, Genetic Cell Line
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Integrated meta-analysis and machine learning approach identifies acyl-CoA thioesterase with other novel genes responsible for biofilm development in Staphylococcus aureus.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases Jan 1, 2021
Biofilm forming Staphylococcus aureus is a major threat to the health-care industry. It is important to understand the differences between planktonic and biofilm growth forms in the pathogen since conventional treatments targeting the planktonic form...
Gene Expression Regulation, Bacterial Humans Transcriptome Supervised Machine Learning Algorithms Biofilms Staphylococcal Infections RNA-Seq Datasets as Topic Staphylococcus aureus Microarray Analysis
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Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease.

Science (New York, N.Y.) Dec 10, 2020
Mapping the gene-regulatory networks dysregulated in human disease would allow the design of network-correcting therapies that treat the core disease mechanism. However, small molecules are traditionally screened for their effects on one to several o...
Algorithms Animals Drug Discovery RNA-Seq Small Molecule Libraries Gene Regulatory Networks Drug Evaluation, Preclinical Calcinosis Humans Mice Thiazoles Aortic Valve Stenosis Aortic Valve Disease Machine Learning Induced Pluripotent Stem Cells Gene Expression Regulation Disease Models, Animal Aortic Valve Receptor, Notch1 Nitriles Mice, Inbred C57BL Haploinsufficiency
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Diagnosis of thyroid neoplasm using support vector machine algorithms based on platelet RNA-seq.

Endocrine Nov 12, 2020
OBJECTIVE: To assess the capacity of support vector machine (SVM) algorithms that are developed based on platelet RNA-seq data in identifying thyroid neoplasm patients and differentiating patients with thyroid adenomas, papillary thyroid cancer and m...
Algorithms Thyroid Neoplasms Humans RNA-Seq Blood Platelets Support Vector Machine
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Cancer classification based on chromatin accessibility profiles with deep adversarial learning model.

PLoS computational biology Nov 9, 2020
Given the complexity and diversity of the cancer genomics profiles, it is challenging to identify distinct clusters from different cancer types. Numerous analyses have been conducted for this propose. Still, the methods they used always do not direct...
Oncogenes Chromatin Immunoprecipitation Sequencing Normal Distribution Databases, Nucleic Acid Chromatin RNA-Seq Humans Genomics Neoplasms Computational Biology Deep Learning Multigene Family
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Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning.

Cells Aug 21, 2020
High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity and phenotypic variation between cells. Some methods have been proposed to detect the related genes ...
Single-Cell Analysis Humans RNA-Seq High-Throughput Nucleotide Sequencing Machine Learning Gene Expression Profiling
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A deep learning model to predict RNA-Seq expression of tumours from whole slide images.

Nature communications Aug 3, 2020
Deep learning methods for digital pathology analysis are an effective way to address multiple clinical questions, from diagnosis to prediction of treatment outcomes. These methods have also been used to predict gene mutations from pathology images, b...
Algorithms Models, Genetic Neoplasms Microsatellite Instability Humans RNA-Seq Gene Expression Profiling Image Processing, Computer-Assisted Deep Learning Computational Biology Gene Expression Regulation, Neoplastic
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