AIMC Topic: Transcriptome

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Ultra-gentle soft robotic fingers induce minimal transcriptomic response in a fragile marine animal.

Current biology : CB Feb 24, 2020
Tessler et al. demonstrate that a 'soft' robot causes less stress to a jellyfish while handling compared to a traditional 'hard' robot.
Stress, Physiological Specimen Handling Scyphozoa Marine Biology Animals Transcriptome Robotics
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Omics Data and Artificial Intelligence: New Challenges for Gene Therapy.

Current gene therapy Jan 1, 2020
Humans Artificial Intelligence Metabolome Genetic Therapy Algorithms Genome Metagenome Transcriptome Proteome
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A Machine Learning Approach to Identify a Circulating MicroRNA Signature for Alzheimer Disease.

The journal of applied laboratory medicine Jan 1, 2020
BACKGROUND: Accurate diagnosis of Alzheimer disease (AD) involving less invasive molecular procedures and at reasonable cost is an unmet medical need. We identified a serum miRNA signature for AD that is less invasive than a measure in cerebrospinal ...
Cognitive Dysfunction Autopsy Alzheimer Disease Early Diagnosis Humans Male Machine Learning Female Gene Expression Profiling Brain Transcriptome Circulating MicroRNA Reproducibility of Results Aged Sensitivity and Specificity
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A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography.

European heart journal Nov 14, 2019
BACKGROUND: Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). Howeve...
Risk Assessment Gene Expression Profiling Transcriptome Case-Control Studies Aged Male Middle Aged Plaque, Atherosclerotic Computed Tomography Angiography Follow-Up Studies Adipose Tissue Coronary Artery Disease Genetic Markers Humans Machine Learning Algorithms Phenotype Female
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Uncovering the mouse olfactory long non-coding transcriptome with a novel machine-learning model.

DNA research : an international journal for rapid publication of reports on genes and genomes Aug 1, 2019
Very little is known about long non-coding RNAs (lncRNAs) in the mammalian olfactory sensory epithelia. Deciphering the non-coding transcriptome in olfaction is relevant because these RNAs have been shown to play a role in chromatin modification and ...
Olfactory Receptor Neurons Vomeronasal Organ Male Transcriptome Mice Machine Learning RNA, Long Noncoding Female Animals
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Convolutional neural network approach to lung cancer classification integrating protein interaction network and gene expression profiles.

Journal of bioinformatics and computational biology Jun 1, 2019
Deep learning technologies are permeating every field from image and speech recognition to computational and systems biology. However, the application of convolutional neural networks (CCNs) to "omics" data poses some difficulties, such as the proces...
Algorithms Reproducibility of Results Transcriptome Humans Protein Interaction Maps Lung Neoplasms Neural Networks, Computer Support Vector Machine Machine Learning Cluster Analysis Random Allocation
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SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles.

Nucleic acids research May 7, 2019
Characterization of individual cell types is fundamental to the study of multicellular samples. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task....
Single-Cell Analysis Mice Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Cluster Analysis Pancreatic Neoplasms Supervised Machine Learning Software Animals Gene Expression Profiling Transcriptome Humans RNA, Small Cytoplasmic High-Throughput Nucleotide Sequencing Datasets as Topic Cell Lineage
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WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach.

Nucleic acids research Apr 23, 2019
N 6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotes, and plays a pivotal role in various biological processes, such as splicing, RNA degradation and RNA-protein interaction. We report here a prediction fram...
Methylation Adenosine Humans Machine Learning Transcriptome Epigenesis, Genetic Protein Interaction Maps Internet Sequence Analysis, RNA RNA High-Throughput Nucleotide Sequencing
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Predicting drug synergy for precision medicine using network biology and machine learning.

Journal of bioinformatics and computational biology Apr 1, 2019
Identification of effective drug combinations for patients is an expensive and time-consuming procedure, especially for experiments. To accelerate the synergistic drug discovery process, we present a new classification model to identify more effecti...
Gene Ontology Databases, Pharmaceutical Machine Learning Humans Protein Interaction Maps Precision Medicine Computational Biology Reproducibility of Results Drug Synergism Transcriptome
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Deep learning in omics: a survey and guideline.

Briefings in functional genomics Feb 14, 2019
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fortunately,...
Proteomics Deep Learning Guidelines as Topic Surveys and Questionnaires Humans Genomics Algorithms Computational Biology Transcriptome
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