AIMC Topic: Transcription Factors

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Machine learning uncovers cell identity regulator by histone code.

Nature communications Jun 1, 2020
Conversion between cell types, e.g., by induced expression of master transcription factors, holds great promise for cellular therapy. Our ability to manipulate cell identity is constrained by incomplete information on cell identity genes (CIGs) and t...
RNA-Seq Gene Regulatory Networks Epigenesis, Genetic Transcription Factors Machine Learning Algorithms Phenotype Cells Pluripotent Stem Cells Histone Code Chromatin Immunoprecipitation Sequencing Databases, Genetic Human Umbilical Vein Endothelial Cells Regenerative Medicine Gene Expression Regulation Humans
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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Biochimica et biophysica acta. Molecular basis of disease Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Carcinoma, Squamous Cell Gene Expression Profiling Transcriptome Lung Neoplasms Humans Machine Learning Adenosine Triphosphatases Terminology as Topic Membrane Transport Proteins Monte Carlo Method Serpins Adenocarcinoma of Lung Cystatin A Diagnosis, Differential Cadherins Datasets as Topic Tumor Suppressor Proteins Computational Biology Gene Expression Regulation, Neoplastic Transcription Factors
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Identification of Methylated Gene Biomarkers in Patients with Alzheimer's Disease Based on Machine Learning.

BioMed research international Mar 26, 2020
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder and characterized by the cognitive impairments. It is essential to identify potential gene biomarkers for AD pathology.
Humans Patients Carrier Proteins Gene Expression Regulation, Neoplastic Peptide Hydrolases Machine Learning Transcription Factors Cyclin-Dependent Kinase Inhibitor p57 Mitochondrial Proteins DNA Methylation DNA-Binding Proteins Protein Tyrosine Phosphatases Microfilament Proteins Genetic Markers Alzheimer Disease
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Mb-level CpG and TFBS islands visualized by AI and their roles in the nuclear organization of the human genome.

Genes & genetic systems Mar 12, 2020
Unsupervised machine learning that can discover novel knowledge from big sequence data without prior knowledge or particular models is highly desirable for current genome study. We previously established a batch-learning self-organizing map (BLSOM) f...
CpG Islands Genome, Human Binding Sites Centromere Protein Binding Transcription Factors Oligonucleotides Chromosomes, Human Heterochromatin Humans Artificial Intelligence
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A generative model for constructing nucleic acid sequences binding to a protein.

BMC genomics Dec 27, 2019
BACKGROUND: Interactions between protein and nucleic acid molecules are essential to a variety of cellular processes. A large amount of interaction data generated by high-throughput technologies have triggered the development of several computational...
Neural Networks, Computer Algorithms Aptamers, Nucleotide Protein Binding Transcription Factors Proteins DNA Base Sequence Humans Nucleic Acid Conformation
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Representation learning of genomic sequence motifs with convolutional neural networks.

PLoS computational biology Dec 19, 2019
Although convolutional neural networks (CNNs) have been applied to a variety of computational genomics problems, there remains a large gap in our understanding of how they build representations of regulatory genomic sequences. Here we perform systema...
Transcription Factors Databases, Genetic DNA Genome, Human Binding Sites Computer Simulation Amino Acid Motifs Humans Neural Networks, Computer Deep Learning Genomics Computational Biology
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BindSpace decodes transcription factor binding signals by large-scale sequence embedding.

Nature methods Aug 12, 2019
The decoding of transcription factor (TF) binding signals in genomic DNA is a fundamental problem. Here we present a prediction model called BindSpace that learns to embed DNA sequences and TF labels into the same space. By training on binding data f...
DNA Binding Sites Chromatin Immunoprecipitation Protein Binding Computational Biology Transcription Factors Humans Machine Learning Algorithms
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Inferring Gene Regulatory Networks of Metabolic Enzymes Using Gradient Boosted Trees.

IEEE journal of biomedical and health informatics Jul 30, 2019
Metabolic reprogramming is a hallmark of cancer. In cancer cells, transcription factors (TFs) govern metabolic reprogramming through abnormally increasing or decreasing the transcription rate of metabolic enzymes, which provides cancer cells growth a...
Transcription Factors Gene Expression Profiling Humans Enzymes Transcriptome Machine Learning Gene Regulatory Networks Algorithms Lung Neoplasms
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Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response.

BMC biology Jul 30, 2019
BACKGROUND: Identification of functional non-coding variants and their mechanistic interpretation is a major challenge of modern genomics, especially for precision medicine. Transcription factor (TF) binding profiles and epigenomic landscapes in refe...
Models, Genetic Humans Transcription Factors Female Machine Learning Gene Expression Regulation Male Protein Binding Polymorphism, Single Nucleotide
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Visualizing complex feature interactions and feature sharing in genomic deep neural networks.

BMC bioinformatics Jul 19, 2019
BACKGROUND: Visualization tools for deep learning models typically focus on discovering key input features without considering how such low level features are combined in intermediate layers to make decisions. Moreover, many of these methods examine ...
Neural Networks, Computer Histone Code Transcription Factors Databases, Genetic Algorithms Base Sequence Deep Learning Histones Genomics
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