AIMC Topic: Epigenomics

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Single-Cell Techniques and Deep Learning in Predicting Drug Response.

Trends in pharmacological sciences Nov 2, 2020
Rapidly developing single-cell sequencing analyses produce more comprehensive profiles of the genomic, transcriptomic, and epigenomic heterogeneity of tumor subpopulations than do traditional bulk sequencing analyses. Moreover, single-cell techniques...
Computational Biology Epigenomics Pharmaceutical Preparations Pharmacology Deep Learning Genomics
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Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications.

Methods (San Diego, Calif.) Sep 14, 2020
Epigenetics is mainly comprised of features that regulate genomic interactions thereby playing a crucial role in a vast array of biological processes. Epigenetic mechanisms such as DNA methylation and histone modifications influence gene expression b...
Epigenesis, Genetic Epigenomics DNA Methylation High-Throughput Nucleotide Sequencing Data Analysis Humans Animals Machine Learning Mice Histone Code
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Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Methods (San Diego, Calif.) Aug 5, 2020
Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovarian cancer patients can facilitate the therapeutics evaluation and treatment decision making. Multi-...
Gene Expression Regulation, Neoplastic Female Humans Breast Neoplasms Epigenomics Genomics DNA Copy Number Variations Neural Networks, Computer DNA Methylation Computational Biology Machine Learning Ovarian Neoplasms
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Cross-species regulatory sequence activity prediction.

PLoS computational biology Jul 20, 2020
Machine learning algorithms trained to predict the regulatory activity of nucleic acid sequences have revealed principles of gene regulation and guided genetic variation analysis. While the human genome has been extensively annotated and studied, mod...
Models, Genetic Databases, Genetic Sequence Analysis, DNA Models, Statistical Genomics Computational Biology Epigenomics Gene Expression Regulation Genome, Human Species Specificity Quantitative Trait Loci Mutation Hepatocytes Genetic Variation Humans Neural Networks, Computer Machine Learning Animals Mice Software Algorithms
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CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection.

Scientific reports May 13, 2020
ChIP-seq is one of the core experimental resources available to understand genome-wide epigenetic interactions and identify the functional elements associated with diseases. The analysis of ChIP-seq data is important but poses a difficult computation...
Databases, Nucleic Acid Transcription Initiation Site Chromatin Immunoprecipitation Sequencing Histones Binding Sites Nucleotide Motifs Neural Networks, Computer Software Algorithms Epigenesis, Genetic Epigenomics Protein Binding Humans Computational Biology
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Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification.

Clinical epigenetics Apr 3, 2020
BACKGROUND: Machine learning is a sub-field of artificial intelligence, which utilises large data sets to make predictions for future events. Although most algorithms used in machine learning were developed as far back as the 1950s, the advent of big...
Precision Medicine Supervised Machine Learning Epigenomics Epigenesis, Genetic Humans Diagnosis Disease DNA Methylation Machine Learning Unsupervised Machine Learning
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Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integration.

Genomics Mar 29, 2020
Gene expression analysis plays a significant role for providing molecular insights in cancer. Various genetic and epigenetic factors (being dealt under multi-omics) affect gene expression giving rise to cancer phenotypes. A recent growth in understan...
DNA Methylation DNA Copy Number Variations Linear Models Carcinoma, Hepatocellular RNA-Seq Genomics Epigenomics Transcriptome Deep Learning Liver Neoplasms
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Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

eLife Jan 27, 2020
Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict e...
Humans Deep Learning Genome-Wide Association Study Diabetes Mellitus, Type 2 Signal Transduction Chromatin Genetic Predisposition to Disease Models, Theoretical Islets of Langerhans Polymorphism, Single Nucleotide Epigenomics
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AIKYATAN: mapping distal regulatory elements using convolutional learning on GPU.

BMC bioinformatics Oct 7, 2019
BACKGROUND: The data deluge can leverage sophisticated ML techniques for functionally annotating the regulatory non-coding genome. The challenge lies in selecting the appropriate classifier for the specific functional annotation problem, within the b...
Cell Line Chromosome Mapping Deep Learning Regulatory Sequences, Nucleic Acid Epigenomics Humans Software
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Deciphering epigenomic code for cell differentiation using deep learning.

BMC genomics Sep 12, 2019
BACKGROUND: Although DNA sequence plays a crucial role in establishing the unique epigenome of a cell type, little is known about the sequence determinants that lead to the unique epigenomes of different cell types produced during cell differentiatio...
Cell Lineage Conserved Sequence Cell Differentiation Humans Histone Code CD4-Positive T-Lymphocytes Deep Learning Nucleotide Motifs Epigenomics
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