AIMC Topic: Promoter Regions, Genetic

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Prediction of MGMT methylation status in glioblastoma patients based on radiomics feature extracted from intratumoral and peritumoral MRI imaging.

Scientific reports
Assessing MGMT promoter methylation is crucial for determining appropriate glioblastoma therapy. Previous studies have focused on intratumoral regions, overlooking the peritumoral area. This study aimed to develop a radiomic model using MRI-derived f...

Learning the sequence code of protein expression in human immune cells.

Science advances
Accurate protein expression in human immune cells is essential for appropriate cellular function. The mechanisms that define protein abundance are complex and are executed on transcriptional, posttranscriptional, and posttranslational levels. Here, w...

Deep learning deciphers the related role of master regulators and G-quadruplexes in tissue specification.

Scientific reports
G-quadruplexes (GQs) are non-canonical DNA structures encoded by G-flipons with potential roles in gene regulation and chromatin structure. Here, we explore the role of G-flipons in tissue specification. We present a deep learning-based framework for...

Rapid diagnosis of TERT promoter mutation using Terahertz absorption spectroscopy in glioblastoma.

Scientific reports
Glioblastoma (GBM) is a highly aggressive brain tumor with poor outcomes and limited treatment options. The telomerase reverse transcriptase (TERT) promoter mutation, one of the key biomarkers in GBM, is linked to tumor progression and prognosis. Thi...

A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites.

PloS one
BACKGROUND: Predicting protein-DNA binding sites in vivo is a challenging but urgent task in many fields such as drug design and development. Most promoters contain many transcription factor (TF) binding sites, yet only a few have been identified thr...

High-resolution dynamic imaging of chromatin DNA communication using Oligo-LiveFISH.

Cell
Three-dimensional (3D) genome dynamics are crucial for cellular functions and disease. However, real-time, live-cell DNA visualization remains challenging, as existing methods are often confined to repetitive regions, suffer from low resolution, or r...

A predictive model for MGMT promoter methylation status in glioblastoma based on terahertz spectral data.

Analytical biochemistry
O-methylguanine-DNA methyltransferase (MGMT) promoter methylation is a crucial biomarker in glioblastoma (GBM) that influences response to temozolomide. Traditional detection methods, such as gene sequencing, are time-consuming and limited to postope...

Combining diffusion and transformer models for enhanced promoter synthesis and strength prediction in deep learning.

mSystems
UNLABELLED: In the field of synthetic biology, the engineering of synthetic promoters that outperform their natural counterparts is of paramount importance, which can optimize the expression of exogenous genes, enhance the efficiency of metabolic pat...

Identification of a novel hypermethylation marker, ZSCAN18, and construction of a diagnostic model in cervical cancer.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Cervical cancer (CC), a common female malignancy, has been linked to alterations in DNA methylation. This study employed an integrated "dry-wet lab" strategy combining bioinformatics, machine learning, and experimental validation to identify...

HybProm: An attention-assisted hybrid CNN-BiLSTM model for the interpretable prediction of DNA promoter.

Methods (San Diego, Calif.)
Promoter prediction is essential for analyzing gene structures, understanding regulatory networks, transcription mechanisms, and precisely controlling gene expression. Recently, computational and deep learning methods for promoter prediction have gai...