AIMC Topic: Transcription Factors
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PPRTGI: A Personalized PageRank Graph Neural Network for TF-Target Gene Interaction Detection.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2024
Transcription factors (TFs) regulation is required for the vast majority of biological processes in living organisms. Some diseases may be caused by improper transcriptional regulation. Identifying the target genes of TFs is thus critical for underst...
Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.
NPJ systems biology and applications
May 30, 2024
Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor's (TF) binding strength, affect enhancer's chromatin activity or interaction, and eventually chang...
Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning.
Journal of chemical information and modeling
May 9, 2024
Transcription factors (TFs) are important regulatory elements for vital cellular activities, and the identification of transcription factor binding sites (TFBS) can help to explore gene regulatory mechanisms. Research studies have proved that cfDNA (...
Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.
BioEssays : news and reviews in molecular, cellular and developmental biology
May 8, 2024
Understanding the influence of cis-regulatory elements on gene regulation poses numerous challenges given complexities stemming from variations in transcription factor (TF) binding, chromatin accessibility, structural constraints, and cell-type diffe...
Predicting Transcription Factor Binding Sites with Deep Learning.
International journal of molecular sciences
May 3, 2024
Prediction of binding sites for transcription factors is important to understand how the latter regulate gene expression and how this regulation can be modulated for therapeutic purposes. A consistent number of references address this issue with diff...
DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes.
Scientific reports
Apr 21, 2024
Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. ...
Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.
Molecules (Basel, Switzerland)
Apr 19, 2024
Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calcula...
ASPTF: A computational tool to predict abiotic stress-responsive transcription factors in plants by employing machine learning algorithms.
Biochimica et biophysica acta. General subjects
Mar 14, 2024
BACKGROUND: Abiotic stresses pose serious threat to the growth and yield of crop plants. Several studies suggest that in plants, transcription factors (TFs) are important regulators of gene expression, especially when it comes to coping with abiotic ...
DARDN: A Deep-Learning Approach for CTCF Binding Sequence Classification and Oncogenic Regulatory Feature Discovery.
Genes
Jan 23, 2024
Characterization of gene regulatory mechanisms in cancer is a key task in cancer genomics. CCCTC-binding factor (CTCF), a DNA binding protein, exhibits specific binding patterns in the genome of cancer cells and has a non-canonical function to facili...
Hold out the genome: a roadmap to solving the cis-regulatory code.
Nature
Dec 13, 2023
Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven ...
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