AI Medical Compendium Topic

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Promoter Regions, Genetic

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CFA: An explainable deep learning model for annotating the transcriptional roles of cis-regulatory modules based on epigenetic codes.

Computers in biology and medicine
Metazoa gene expression is controlled by modular DNA segments called cis-regulatory modules (CRMs). CRMs can convey promoter/enhancer/insulator roles, generating additional regulation layers in transcription. Experiments for understanding CRM roles a...

Ensemble learning based assessment of the role of transcription factors in gene expression.

Computers in biology and medicine
Cancer cells are formed when the associated, active genes fail to function the way they are meant to function. Multiple genes collectively control cell growth by activating a proper set of genes. Regulation of gene expression is controlled through th...

DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data.

BMC bioinformatics
BACKGROUND: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE suffers from transcriptional an...

Explainable artificial intelligence as a reliable annotator of archaeal promoter regions.

Scientific reports
Archaea are a vast and unexplored cellular domain that thrive in a high diversity of environments, having central roles in processes mediating global carbon and nutrient fluxes. For these organisms to balance their metabolism, the appropriate regulat...

DeepPHiC: predicting promoter-centered chromatin interactions using a novel deep learning approach.

Bioinformatics (Oxford, England)
MOTIVATION: Promoter-centered chromatin interactions, which include promoter-enhancer (PE) and promoter-promoter (PP) interactions, are important to decipher gene regulation and disease mechanisms. The development of next-generation sequencing techno...

Designing artificial synthetic promoters for accurate, smart, and versatile gene expression in plants.

Plant communications
With the development of high-throughput biology techniques and artificial intelligence, it has become increasingly feasible to design and construct artificial biological parts, modules, circuits, and even whole systems. To overcome the limitations of...

A deep learning based two-layer predictor to identify enhancers and their strength.

Methods (San Diego, Calif.)
The enhancer is a DNA sequence that can increase the activity of promoters and thus speed up the frequency of gene transcription. The enhancer plays an essential role in activating gene expression. Currently, gene sequencing technology has been devel...

Deep Learning Prediction of Promoter Mutation Status in Thyroid Cancer Using Histologic Images.

Medicina (Kaunas, Lithuania)
objectives: Telomerase reverse transcriptase () promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated with aggressive biologic behavior. Predicting promoter mutation is thus necessary for the prognostic strati...

Designer genes courtesy of artificial intelligence.

Genes & development
The core promoter determines not only where gene transcription initiates but also the transcriptional activity in both basal and enhancer-induced conditions. Multiple short sequence elements within the core promoter have been identified in different ...

Design of synthetic promoters for cyanobacteria with generative deep-learning model.

Nucleic acids research
Deep generative models, which can approximate complex data distribution from large datasets, are widely used in biological dataset analysis. In particular, they can identify and unravel hidden traits encoded within a complicated nucleotide sequence, ...