AIMC Topic: Transcription Factors

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HOX cluster and their cofactors showed an altered expression pattern in eutopic and ectopic endometriosis tissues.

Reproductive biology and endocrinology : RB&E Sep 1, 2021
Endometriosis is major gynecological disease that affects over 10% of women worldwide and 30%-50% of these women have pelvic pain, abnormal uterine bleeding and infertility. The cause of endometriosis is unknown and there is no definite cure mainly b...
Gene Regulatory Networks Signal Transduction Transcription Factors Young Adult Gene Ontology Adult Humans Homeodomain Proteins Gene Expression Profiling Female Genes, Homeobox Endometrium Endometriosis Multigene Family
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Gene Ontology representation for transcription factor functions.

Biochimica et biophysica acta. Gene regulatory mechanisms Aug 28, 2021
Transcription plays a central role in defining the identity and functionalities of cells, as well as in their responses to changes in the cellular environment. The Gene Ontology (GO) provides a rigorously defined set of concepts that describe the fun...
Transcription Factors Databases, Genetic Gene Expression Regulation Computational Biology Molecular Sequence Annotation Gene Ontology
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Discovering differential genome sequence activity with interpretable and efficient deep learning.

PLoS computational biology Aug 9, 2021
Discovering sequence features that differentially direct cells to alternate fates is key to understanding both cellular development and the consequences of disease related mutations. We introduce Expected Pattern Effect and Differential Expected Patt...
Transcription Factors Sequence Analysis, DNA High-Throughput Nucleotide Sequencing Genome, Human Humans Neural Networks, Computer Deep Learning
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Deep learning-based prediction of TFBSs in plants.

Trends in plant science Jul 24, 2021
Binding Sites Deep Learning Protein Binding Computational Biology Transcription Factors
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Prioritizing and characterizing functionally relevant genes across human tissues.

PLoS computational biology Jul 16, 2021
Knowledge of genes that are critical to a tissue's function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model-FUGUE-combini...
Transcription Factors Multigene Family Genome, Human Genetic Association Studies Computational Biology Models, Genetic Tissue Distribution Gene Expression Regulation, Developmental Male Neoplasms Transcriptome Genome-Wide Association Study Protein Interaction Maps Gene Regulatory Networks Machine Learning Software Humans Female
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DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence.

International journal of molecular sciences May 24, 2021
Predicting in vivo protein-DNA binding sites is a challenging but pressing task in a variety of fields like drug design and development. Most promoters contain a number of transcription factor (TF) binding sites, but only a small minority has been id...
Humans Software Deep Learning K562 Cells DNA Computational Biology Binding Sites DNA-Binding Proteins Transcription Factors Promoter Regions, Genetic Cell Line
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Machine learning predicts nucleosome binding modes of transcription factors.

BMC bioinformatics Mar 30, 2021
BACKGROUND: Most transcription factors (TFs) compete with nucleosomes to gain access to their cognate binding sites. Recent studies have identified several TF-nucleosome interaction modes including end binding (EB), oriented binding, periodic binding...
Machine Learning Protein Binding Nucleosomes Transcription Factors Amino Acid Sequence Binding Sites
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Epigenetic Target Fishing with Accurate Machine Learning Models.

Journal of medicinal chemistry Mar 26, 2021
Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represe...
Databases, Chemical Proof of Concept Study Histone Deacetylases Transcription Factors Structure-Activity Relationship Molecular Structure Machine Learning Organic Chemicals Drug Discovery Epigenomics
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An Integrative Framework for Combining Sequence and Epigenomic Data to Predict Transcription Factor Binding Sites Using Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Knowing the transcription factor binding sites (TFBSs) is essential for modeling the underlying binding mechanisms and follow-up cellular functions. Convolutional neural networks (CNNs) have outperformed methods in predicting TFBSs from the primary D...
Binding Sites Computational Biology Deep Learning Histone Code Epigenesis, Genetic Protein Binding Chromatin Immunoprecipitation Sequencing Transcription Factors
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DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks.

BMC bioinformatics Feb 1, 2021
BACKGROUND: Due to the complexity of the biological systems, the prediction of the potential DNA binding sites for transcription factors remains a difficult problem in computational biology. Genomic DNA sequences and experimental results from paralle...
Chromatin Transcription Factors Binding Sites Neural Networks, Computer Protein Binding Computational Biology
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