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Transcription Factors

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BERT-TFBS: a novel BERT-based model for predicting transcription factor binding sites by transfer learning.

Briefings in bioinformatics 38701417
Transcription factors (TFs) are proteins essential for regulating genetic transcriptions by binding to transcription factor binding sites (TFBSs) in DNA sequences. Accurate predictions of TFBSs can contribute to the design and construction of metabol...
Algorithms Binding Sites Computational Biology Deep Learning Humans Neural Networks, Computer Protein Binding Transcription Factors
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Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.

Molecules (Basel, Switzerland) 38675678
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...
Azepines Binding Sites Bromodomain Containing Proteins Cell Cycle Proteins Deep Learning Humans Molecular Docking Simulation Molecular Dynamics Simulation Nuclear Proteins Protein Binding Thermodynamics Transcription Factors Triazoles
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DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes.

Scientific reports 38644393
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 Sites Computational Biology Deep Learning Eukaryota Eukaryotic Cells Genome Neural Networks, Computer Prokaryotic Cells Transcription Factors
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Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.

NPJ systems biology and applications 38816426
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...
Chromatin Computational Biology Enhancer Elements, Genetic Gene Expression Profiling Genome-Wide Association Study Humans Machine Learning Pharmacogenetics Transcription Factors Transcriptome
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Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning.

Journal of chemical information and modeling 38798191
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 (...
Binding Sites Cell-Free Nucleic Acids Deep Learning DNA Humans Transcription Factors
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Predicting Transcription Factor Binding Sites with Deep Learning.

International journal of molecular sciences 38732207
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...
Binding Sites Cell Line Chromatin Immunoprecipitation Sequencing Computational Biology Deep Learning HeLa Cells Humans Protein Binding Transcription Factors
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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 38715516
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...
Animals Computational Biology CRISPR-Cas Systems Gene Expression Regulation Gene Regulatory Networks Humans Machine Learning Regulatory Elements, Transcriptional Transcription Factors
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Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network.

Biophysical reports 38848994
The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational prin...
Escherichia coli Gene Regulatory Networks Machine Learning Neural Networks, Computer Nonlinear Dynamics Transcription Factors
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The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model.

Nucleic acids research 38813828
Gene expression is temporally and spatially regulated by the interaction of transcription factors (TFs) and cis-regulatory elements (CREs). The uneven distribution of TF binding sites across the genome poses challenges in understanding how this distr...
Animals Binding Sites Cattle Chickens Chromatin Embryonic Development Evolution, Molecular Gene Expression Regulation, Developmental Humans Machine Learning Mice Oryzias Promoter Regions, Genetic Transcription Factors
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Transcription Factor Binding Site Prediction Using CnNet Approach.

IEEE/ACM transactions on computational biology and bioinformatics 38848239
Controlling the gene expression is the most important development in a living organism, which makes it easier to find different kinds of diseases and their causes. It's very difficult to know what factors control the gene expression. Transcription Fa...
Algorithms Binding Sites Computational Biology Deep Learning Humans Neural Networks, Computer Sequence Analysis, DNA Transcription Factors
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