AIMC Topic: Genome, Human

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Sequence-Based Deep Learning Frameworks on Enhancer-Promoter Interactions Prediction.

Current pharmaceutical design Jan 1, 2021
Enhancer-promoter interactions (EPIs) in the human genome are of great significance to transcriptional regulation, which tightly controls gene expression. Identification of EPIs can help us better decipher gene regulation and understand disease mecha...
Genome, Human Promoter Regions, Genetic Regulatory Sequences, Nucleic Acid Humans Neural Networks, Computer Deep Learning
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The reactome pathway knowledgebase.

Nucleic acids research Jan 8, 2020
The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations in a single consistent data mo...
Databases, Chemical Genome, Human Humans Databases, Pharmaceutical Software Signal Transduction Protein Interaction Maps Metabolic Networks and Pathways Knowledge Bases
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SomaticSeq: An Ensemble and Machine Learning Method to Detect Somatic Mutations.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2020
A standard strategy to discover somatic mutations in a cancer genome is to use next-generation sequencing (NGS) technologies to sequence the tumor tissue and its matched normal (commonly blood or adjacent normal tissue) for side-by-side comparison. H...
Humans Machine Learning Software High-Throughput Nucleotide Sequencing Genome, Human Neoplasms Genomics Mutation
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Ensemble-Based Somatic Mutation Calling in Cancer Genomes.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2020
Identification of somatic mutations in tumor tissue is challenged by both technical artifacts, diverse somatic mutational processes, and genetic heterogeneity in the tumors. Indeed, recent independent benchmark studies have revealed low concordance b...
Humans Genome, Human INDEL Mutation Point Mutation Polymorphism, Single Nucleotide Software Mutation Neoplasms Supervised Machine Learning Genomics
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DL-CNV: A deep learning method for identifying copy number variations based on next generation target sequencing.

Mathematical biosciences and engineering : MBE Sep 30, 2019
Copy number variations (CNVs) play an important role in many types of cancer. With the rapid development of next generation sequencing (NGS) techniques, many methods for detecting CNVs of a single sample have emerged: (i) require genome-wide data of ...
Exons Proto-Oncogene Proteins c-met Humans Area Under Curve Lung Neoplasms Algorithms High-Throughput Nucleotide Sequencing Deep Learning Carcinoma, Non-Small-Cell Lung In Situ Hybridization, Fluorescence Genome-Wide Association Study Databases, Factual DNA Copy Number Variations Receptor, ErbB-2 ROC Curve Reproducibility of Results Genome, Human Sensitivity and Specificity False Positive Reactions
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HMMRATAC: a Hidden Markov ModeleR for ATAC-seq.

Nucleic acids research Sep 19, 2019
ATAC-seq has been widely adopted to identify accessible chromatin regions across the genome. However, current data analysis still utilizes approaches initially designed for ChIP-seq or DNase-seq, without considering the transposase digested DNA fragm...
Histones Nucleosomes Transposases DNA Supervised Machine Learning High-Throughput Nucleotide Sequencing Markov Chains Datasets as Topic Genome, Human Humans Software Sequence Analysis, DNA
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Promoter analysis and prediction in the human genome using sequence-based deep learning models.

Bioinformatics (Oxford, England) Aug 15, 2019
MOTIVATION: Computational identification of promoters is notoriously difficult as human genes often have unique promoter sequences that provide regulation of transcription and interaction with transcription initiation complex. While there are many at...
Transcription Initiation Site Genomics Genome, Human Promoter Regions, Genetic Humans Deep Learning
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The Kipoi repository accelerates community exchange and reuse of predictive models for genomics.

Nature biotechnology Jun 1, 2019
Genomics Whole Genome Sequencing Gene Editing Genome, Human Humans Machine Learning Databases, Factual
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EnsembleCNV: an ensemble machine learning algorithm to identify and genotype copy number variation using SNP array data.

Nucleic acids research Apr 23, 2019
The associations between diseases/traits and copy number variants (CNVs) have not been systematically investigated in genome-wide association studies (GWASs), primarily due to a lack of robust and accurate tools for CNV genotyping. Herein, we propose...
Datasets as Topic Genome, Human Genotyping Techniques Polymorphism, Single Nucleotide DNA Copy Number Variations Quality Control Humans Machine Learning
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Localizing and Classifying Adaptive Targets with Trend Filtered Regression.

Molecular biology and evolution Feb 1, 2019
Identifying genomic locations of natural selection from sequence data is an ongoing challenge in population genetics. Current methods utilizing information combined from several summary statistics typically assume no correlation of summary statistics...
Regression Analysis Software Genetics, Population Humans Computer Simulation Genome, Human Machine Learning Models, Genetic Genetic Techniques
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