AIMC Topic: 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...
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...
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...
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...
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...
Reproducibility of Results
Tumor Microenvironment
Biomarkers, Tumor
Lymphocytes, Tumor-Infiltrating
Gene Expression Profiling
Humans
Databases, Genetic
Transcriptome
Monocytes
Genomics
Machine Learning
Molecular Sequence Annotation
ROC Curve
Leukocyte Count
Treatment Outcome
Prognosis
Computational Biology
Glioma
Immunotherapy
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...
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...
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. ...
Predicting functions of maize proteins using graph convolutional network.
BMC bioinformatics
Dec 16, 2020
BACKGROUND: Maize (Zea mays ssp. mays L.) is the most widely grown and yield crop in the world, as well as an important model organism for fundamental research of the function of genes. The functions of Maize proteins are annotated using the Gene Ont...
Automatic Gene Function Prediction in the 2020's.
Genes
Oct 27, 2020
The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, emphasizing the need for accurate Automatic Function Prediction (AFP) methods. AFP has been an active...
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