AIMC Topic: Molecular Sequence Annotation

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ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.

PLoS computational biology Sep 7, 2021
Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understan...
Models, Genetic Mutation Gene Expression Regulation Deep Learning Genome-Wide Association Study Computational Biology Enhancer Elements, Genetic Genes, Reporter Regulatory Sequences, Nucleic Acid Transcription Initiation, Genetic Genome, Human Promoter Regions, Genetic Molecular Sequence Annotation Humans
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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...
Computational Biology Transcription Factors Databases, Genetic Gene Ontology Gene Expression Regulation Molecular Sequence Annotation
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DeepDRBP-2L: A New Genome Annotation Predictor for Identifying DNA-Binding Proteins and RNA-Binding Proteins Using Convolutional Neural Network and Long Short-Term Memory.

IEEE/ACM transactions on computational biology and bioinformatics Aug 6, 2021
DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) are two kinds of crucial proteins, which are associated with various cellule activities and some important diseases. Accurate identification of DBPs and RBPs facilitate both theoretical rese...
RNA-Binding Proteins DNA-Binding Proteins Neural Networks, Computer Molecular Sequence Annotation Algorithms Genomics
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Application of machine learning to large in-vitro databases to identify cancer cell characteristics: telomerase reverse transcriptase (TERT) expression.

Oncogene Jun 16, 2021
Advances in biotechnology and machine learning have created an enhanced environment for unearthing and exploiting previously unrecognized relationships between genomic and epigenetic data with potential therapeutic implications. We applied advanced a...
Humans Machine Learning Biomarkers, Tumor Gene Expression Regulation, Neoplastic Databases, Genetic Molecular Sequence Annotation Telomerase Gene Expression Profiling Liver Neoplasms Computational Biology
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A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets.

Genes Jun 10, 2021
Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type definin...
Natural Language Processing Organ Specificity Molecular Sequence Annotation Humans Single-Cell Analysis RNA-Seq Databases, Genetic
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Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data.

Nature communications May 11, 2021
Transcriptomic atlases have improved our understanding of the correlations between gene-expression patterns and spatially varying properties of brain structure and function. Gene-category enrichment analysis (GCEA) is a common method to identify func...
Molecular Sequence Annotation Gene Ontology Gene Expression Profiling Mice Mice, Inbred C57BL Software Reproducibility of Results Brain Animals Male Humans
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The Predictive Value of Monocytes in Immune Microenvironment and Prognosis of Glioma Patients Based on Machine Learning.

Frontiers in immunology Apr 16, 2021
Gliomas are primary malignant brain tumors. Monocytes have been proved to actively participate in tumor growth. Weighted gene co-expression network analysis was used to identify meaningful monocyte-related genes for clustering. Neural network and SVM...
Tumor Microenvironment Biomarkers, Tumor Gene Expression Profiling Molecular Sequence Annotation Machine Learning Glioma Leukocyte Count Prognosis Humans Lymphocytes, Tumor-Infiltrating Transcriptome Computational Biology Reproducibility of Results Databases, Genetic Monocytes ROC Curve Immunotherapy Genomics Treatment Outcome
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Establishing a consensus for the hallmarks of cancer based on gene ontology and pathway annotations.

BMC bioinformatics Apr 6, 2021
BACKGROUND: The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development and tumourigenesis. However, methods for translating these high-level concepts into data-le...
Consensus Semantics Humans Gene Ontology Neoplasms Molecular Sequence Annotation
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2passtools: two-pass alignment using machine-learning-filtered splice junctions increases the accuracy of intron detection in long-read RNA sequencing.

Genome biology Mar 1, 2021
Transcription of eukaryotic genomes involves complex alternative processing of RNAs. Sequencing of full-length RNAs using long reads reveals the true complexity of processing. However, the relatively high error rates of long-read sequencing technolog...
Software Algorithms Reproducibility of Results RNA-Seq Computational Biology Molecular Sequence Annotation Machine Learning RNA Splice Sites Introns Sequence Alignment RNA Splicing
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Graph embeddings on gene ontology annotations for protein-protein interaction prediction.

BMC bioinformatics Dec 16, 2020
BACKGROUND: Protein-protein interaction (PPI) prediction is an important task towards the understanding of many bioinformatics functions and applications, such as predicting protein functions, gene-disease associations and disease-drug associations. ...
Task Performance and Analysis Mice Saccharomyces cerevisiae Gene Ontology Computational Biology Area Under Curve Humans Protein Interaction Mapping Molecular Sequence Annotation Animals ROC Curve
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