AIMC Topic: Transcription Factors

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McEnhancer: predicting gene expression via semi-supervised assignment of enhancers to target genes.

Genome biology Oct 26, 2017
Transcriptional enhancers regulate spatio-temporal gene expression. While genomic assays can identify putative enhancers en masse, assigning target genes is a complex challenge. We devised a machine learning approach, McEnhancer, which links target g...
Animals Genes, Reporter Transcription Factors Gene Expression Regulation, Developmental Histone Code Deoxyribonuclease I Sequence Analysis, DNA Promoter Regions, Genetic Machine Learning Embryonic Development Drosophila melanogaster Nucleotide Motifs Enhancer Elements, Genetic
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The folded k-spectrum kernel: A machine learning approach to detecting transcription factor binding sites with gapped nucleotide dependencies.

PloS one Oct 5, 2017
Understanding the molecular machinery involved in transcriptional regulation is central to improving our knowledge of an organism's development, disease, and evolution. The building blocks of this complex molecular machinery are an organism's genomic...
Binding Sites Transcription Factors Support Vector Machine Nucleotides Machine Learning
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EMQIT: a machine learning approach for energy based PWM matrix quality improvement.

Biology direct Aug 1, 2017
BACKGROUND: Transcription factor binding affinities to DNA play a key role for the gene regulation. Learning the specificity of the mechanisms of binding TFs to DNA is important both to experimentalists and theoreticians. With the development of high...
Binding Sites Position-Specific Scoring Matrices Software ROC Curve Computational Biology Machine Learning Models, Genetic Transcription Factors Models, Molecular Datasets as Topic Gene Expression Regulation
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Machine-Learning-Assisted Approach for Discovering Novel Inhibitors Targeting Bromodomain-Containing Protein 4.

Journal of chemical information and modeling Jul 10, 2017
Bromodomain-containing protein 4 (BRD4) is implicated in the pathogenesis of a number of different cancers, inflammatory diseases and heart failure. Much effort has been dedicated toward discovering novel scaffold BRD4 inhibitors (BRD4is) with differ...
Molecular Docking Simulation Drug Discovery Nuclear Proteins Transcription Factors Humans Machine Learning Molecular Targeted Therapy Cell Line Protein Conformation Structure-Activity Relationship Cell Cycle Proteins Drug Evaluation, Preclinical
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TIGERi: modeling and visualizing the responses to perturbation of a transcription factor network.

BMC bioinformatics May 31, 2017
BACKGROUND: Transcription factor (TF) networks play a key role in controlling the transfer of genetic information from gene to mRNA. Much progress has been made on understanding and reverse-engineering TF network topologies using a range of experimen...
Gene Regulatory Networks Mice Transcription Factors Mice, Knockout Machine Learning Animals Transcriptome Binding Sites Mitogen-Activated Protein Kinase 14
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Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.

Scientific reports Apr 25, 2017
Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differ...
Transcription Factors Machine Learning Female Support Vector Machine Aged Epithelial Cells Tumor Suppressor Proteins Breast Neoplasms Carcinoma, Intraductal, Noninfiltrating Immunohistochemistry Hyperplasia Humans Cellular Microenvironment
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Identification of transcription factors that may reprogram lung adenocarcinoma.

Artificial intelligence in medicine Apr 1, 2017
BACKGROUND: Lung adenocarcinoma is one of most threatening disease to human health. Although many efforts have been devoted to its genetic study, few researches have been focused on the transcription factors which regulate tumor initiation and progre...
Signal Transduction Transcription Factors Adenocarcinoma Databases, Genetic Cell Transformation, Neoplastic Lung Neoplasms Transcription, Genetic Computational Biology Adenocarcinoma of Lung Epigenesis, Genetic Humans Gene Expression Regulation, Neoplastic Artificial Intelligence Gene Regulatory Networks
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Imputation for transcription factor binding predictions based on deep learning.

PLoS computational biology Feb 24, 2017
Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard....
Reproducibility of Results Sensitivity and Specificity Protein Binding Transcription Factors Hep G2 Cells High-Throughput Nucleotide Sequencing K562 Cells Binding Sites Humans Neural Networks, Computer Machine Learning Protein Interaction Mapping Chromatin Immunoprecipitation
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A high-order representation and classification method for transcription factor binding sites recognition in Escherichia coli.

Artificial intelligence in medicine Dec 1, 2016
BACKGROUND: Identifying transcription factors binding sites (TFBSs) plays an important role in understanding gene regulatory processes. The underlying mechanism of the specific binding for transcription factors (TFs) is still poorly understood. Previ...
Computational Biology Humans Algorithms Transcription Factors Protein Binding Escherichia coli Binding Sites
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Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

Nucleic acids research Nov 29, 2016
The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF b...
CD4-Positive T-Lymphocytes Hepatocytes Humans Chromatin Gene Expression Regulation Cell Line Cell Line, Tumor Machine Learning Chromatin Assembly and Disassembly Organ Specificity Principal Component Analysis K562 Cells Protein Binding Algorithms Human Embryonic Stem Cells DNA Histones Transcription Factors Binding Sites Hep G2 Cells Primary Cell Culture
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