AIMC Topic: Transcription Factors

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bHLHDB: A next generation database of basic helix loop helix transcription factors based on deep learning model.

Journal of bioinformatics and computational biology Jul 25, 2022
The basic helix loop helix (bHLH) superfamily is a large and diverse protein family that plays a role in various vital functions in nearly all animals and plants. The bHLH proteins form one of the largest families of transcription factors found in pl...
Animals Phylogeny Basic Helix-Loop-Helix Transcription Factors Plants Amino Acid Sequence Deep Learning Transcription Factors
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Deep learning-based transcription factor activity for stratification of breast cancer patients.

Biochimica et biophysica acta. Gene regulatory mechanisms Jun 8, 2022
Transcription factors directly bind to DNA and regulate the expression of the gene, causing epigenetic modification of the DNA. They often mediate epigenetic parameters of transcriptional and posttranscriptional mechanisms, and their expression activ...
Algorithms Female Breast Neoplasms Humans Transcription Factors Deep Learning Genomics
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Characterizing collaborative transcription regulation with a graph-based deep learning approach.

PLoS computational biology Jun 6, 2022
Human epigenome and transcription activities have been characterized by a number of sequence-based deep learning approaches which only utilize the DNA sequences. However, transcription factors interact with each other, and their collaborative regulat...
Binding Sites Chromatin Deep Learning Protein Binding DNA Gene Expression Regulation Humans Transcription Factors
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Prediction of protein-ligand binding affinity from sequencing data with interpretable machine learning.

Nature biotechnology May 23, 2022
Protein-ligand interactions are increasingly profiled at high throughput using affinity selection and massively parallel sequencing. However, these assays do not provide the biophysical parameters that most rigorously quantify molecular interactions....
Ligands Binding Sites Transcription Factors DNA Chromatin Immunoprecipitation Machine Learning Protein Binding
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Prediction of the transcription factor binding sites with meta-learning.

Methods (San Diego, Calif.) Apr 21, 2022
With the accumulation of ChIP-seq data, convolution neural network (CNN)-based methods have been proposed for predicting transcription factor binding sites (TFBSs). However, biological experimental data are noisy, and are often treated as ground trut...
Protein Binding Transcription Factors Binding Sites Chromatin Immunoprecipitation Sequencing Neural Networks, Computer
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FCNGRU: Locating Transcription Factor Binding Sites by Combing Fully Convolutional Neural Network With Gated Recurrent Unit.

IEEE journal of biomedical and health informatics Apr 14, 2022
Deciphering the relationship between transcription factors (TFs) and DNA sequences is very helpful for computational inference of gene regulation and a comprehensive understanding of gene regulation mechanisms. Transcription factor binding sites (TFB...
Nucleotides Binding Sites Transcription Factors DNA Protein Binding Computational Biology Humans Neural Networks, Computer
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Chromatin interaction-aware gene regulatory modeling with graph attention networks.

Genome research Apr 8, 2022
Linking distal enhancers to genes and modeling their impact on target gene expression are longstanding unresolved problems in regulatory genomics and critical for interpreting noncoding genetic variation. Here, we present a new deep learning approach...
Binding Sites Regulatory Sequences, Nucleic Acid Chromatin Transcription Factors Neural Networks, Computer Gene Expression Regulation Gene Regulatory Networks
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DeepCAGE: Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility.

Genomics, proteomics & bioinformatics Mar 12, 2022
Although computational approaches have been complementing high-throughput biological experiments for the identification of functional regions in the human genome, it remains a great challenge to systematically decipher interactions between transcript...
Genome, Human Humans Deep Learning Chromatin Assembly and Disassembly Binding Sites Regulatory Sequences, Nucleic Acid Protein Binding Chromatin Transcription Factors
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Base-resolution prediction of transcription factor binding signals by a deep learning framework.

PLoS computational biology Mar 9, 2022
Transcription factors (TFs) play an important role in regulating gene expression, thus the identification of the sites bound by them has become a fundamental step for molecular and cellular biology. In this paper, we developed a deep learning framewo...
Chromatin Immunoprecipitation Sequencing Deep Learning Transcription Factors Protein Binding Binding Sites
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Domain-adaptive neural networks improve cross-species prediction of transcription factor binding.

Genome research Jan 18, 2022
The intrinsic DNA sequence preferences and cell type-specific cooperative partners of transcription factors (TFs) are typically highly conserved. Hence, despite the rapid evolutionary turnover of individual TF binding sites, predictive sequence model...
Binding Sites Chromatin Immunoprecipitation Sequencing Computational Biology Neural Networks, Computer Transcription Factors Protein Binding
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