AIMC Topic: Transcriptome

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Machine learning-based classification and diagnosis of clinical cardiomyopathies.

Physiological genomics Aug 3, 2020
Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common types of cardiomyopathies leading to heart failure. Accurate diagnostic classification of different types of cardiomyopathies is critical for precision medicine in clinical...
Humans Artificial Intelligence Databases, Genetic Heart Failure Myocardial Ischemia Cardiomyopathies Machine Learning Transcriptome Computational Biology
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Repurpose Open Data to Discover Therapeutics for COVID-19 Using Deep Learning.

Journal of proteome research Jul 24, 2020
There have been more than 2.2 million confirmed cases and over 120 000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone. How...
Deep Learning Antiviral Agents Proteome Betacoronavirus Pneumonia, Viral Drug Repositioning COVID-19 Coronavirus Infections SARS-CoV-2 Transcriptome Humans Pandemics
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Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics.

Cell systems Jul 24, 2020
Cancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer pro...
Female Male Neoplasms Proteomics Proteins Transcriptome Genomics Humans Machine Learning Phosphoproteins Crowdsourcing
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Cell type prioritization in single-cell data.

Nature biotechnology Jul 20, 2020
We present Augur, a method to prioritize the cell types most responsive to biological perturbations in single-cell data. Augur employs a machine-learning framework to quantify the separability of perturbed and unperturbed cells within a high-dimensio...
Chromatin Mice Computational Biology Sequence Analysis, RNA Animals Walking Gene Expression Profiling Nerve Net Transcriptome Rats Single-Cell Analysis Databases, Genetic Machine Learning
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Exploration of the mechanism of traditional Chinese medicine by AI approach using unsupervised machine learning for cellular functional similarity of compounds in heterogeneous networks, XiaoErFuPi granules as an example.

Pharmacological research Jul 17, 2020
'Polypharmacology' is usually used to describe the network-wide effect of a single compound, but traditional Chinese medicine (TCM) has a polypharmacological effect naturally based on the 'multi-components, multi-targets and multi-pathways' principle...
Unsupervised Machine Learning Structure-Activity Relationship Molecular Structure Drugs, Chinese Herbal Medicine, Chinese Traditional Rats, Sprague-Dawley Cluster Analysis Polypharmacology Dyspepsia Protein Interaction Maps Gene Regulatory Networks Systems Biology Proteome Signal Transduction Duodenum Proteomics Male Gene Expression Profiling Transcriptome Humans Animals
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A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth.

Proceedings of the National Academy of Sciences of the United States of America Jul 16, 2020
Metabolic modeling and machine learning are key components in the emerging next generation of systems and synthetic biology tools, targeting the genotype-phenotype-environment relationship. Rather than being used in isolation, it is becoming clear th...
Transcriptome Systems Biology Models, Biological Saccharomyces cerevisiae Machine Learning Metabolic Flux Analysis
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DISC: a highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.

Genome biology Jul 10, 2020
Dropouts distort gene expression and misclassify cell types in single-cell transcriptome. Although imputation may improve gene expression and downstream analysis to some degree, it also inevitably introduces false signals. We develop DISC, a novel de...
Single-Cell Analysis Sequence Analysis, RNA Software Transcriptome Deep Learning
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Metatranscriptomics reveals the gene functions and metabolic properties of the major microbial community during Chinese Sichuan Paocai fermentation.

Food microbiology Jul 3, 2020
Chinese Sichuan Paocai (CSP) is one of the world's best-known fermented vegetables with a large presence in the Chinese market. The dynamic microbial community is the main contributor to Paocai fermentation. However, little is known about the ecologi...
Microbiota Enterobacteriaceae Fermentation Fermented Foods Metagenomics Transcriptome Lactobacillaceae Brassica Vegetables China Food Microbiology
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Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis.

Neuron Jun 29, 2020
A major obstacle to treating Alzheimer's disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerability, a key characteristic of the disease. Here, we present a framework integrating high-quality neu...
Transcriptome Humans Alzheimer Disease Gene Regulatory Networks Machine Learning Animals Mice Aging Neurons Gene Expression Profiling
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Integrating spatial gene expression and breast tumour morphology via deep learning.

Nature biomedical engineering Jun 22, 2020
Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial resolution, making it possible to systematically link the morphology of cellular neighbourhoods and spatially localized gene expression. Here, we report the develop...
Image Processing, Computer-Assisted Gene Expression Profiling Transcriptome Deep Learning Female Humans Breast Neoplasms Algorithms Reproducibility of Results Biomarkers, Tumor
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