AIMC Topic: Gene Ontology

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A Deep Learning Framework for Predicting Protein Functions With Co-Occurrence of GO Terms.

IEEE/ACM transactions on computational biology and bioinformatics Apr 3, 2023
The understanding of protein functions is critical to many biological problems such as the development of new drugs and new crops. To reduce the huge gap between the increase of protein sequences and annotations of protein functions, many methods hav...
Proteins Amino Acid Sequence Gene Ontology Deep Learning
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Identifying the tumor location-associated candidate genes in development of new drugs for colorectal cancer using machine-learning-based approach.

Medical & biological engineering & computing Aug 10, 2022
Numerous studies have been conducted to elucidate the relation of tumor proximity to cancer prognosis and treatment efficacy in colorectal cancer. However, the molecular pathways and prognoses of left- and right-sided colorectal cancers are different...
Machine Learning Colorectal Neoplasms Humans Gene Ontology
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DeepIDA: Predicting Isoform-Disease Associations by Data Fusion and Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2022
Alternative splicing produces different isoforms from the same gene locus, it is an important mechanism for regulating gene expression and proteome diversity. Although the prediction of gene(ncRNA)-disease associations has been extensively studied, f...
Computational Biology Proteome Protein Isoforms Gene Ontology Neural Networks, Computer Alternative Splicing
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Gene Identification and Potential Drug Therapy for Drug-Resistant Melanoma with Bioinformatics and Deep Learning Technology.

Disease markers Jul 23, 2022
BACKGROUND: Melanomas are skin malignant tumors that arise from melanocytes which are primarily treated with surgery, chemotherapy, targeted therapy, immunotherapy, radiation therapy, etc. Targeted therapy is a promising approach to treating advanced...
Gene Expression Regulation, Neoplastic Gene Expression Profiling Prognosis Gene Ontology Deep Learning Humans Melanoma Technology Protein Interaction Maps Computational Biology
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NILINKER: Attention-based approach to NIL Entity Linking.

Journal of biomedical informatics Jul 8, 2022
The existence of unlinkable (NIL) entities is a major hurdle affecting the performance of Named Entity Linking approaches, and, consequently, the performance of downstream models that depend on them. Existing approaches to deal with NIL entities focu...
Neural Networks, Computer Cluster Analysis Gene Ontology Knowledge Bases Data Mining
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Empowering the discovery of novel target-disease associations via machine learning approaches in the open targets platform.

BMC bioinformatics Jun 16, 2022
BACKGROUND: The Open Targets (OT) Platform integrates a wide range of data sources on target-disease associations to facilitate identification of potential therapeutic drug targets to treat human diseases. However, due to the complexity that targets ...
Power, Psychological Drug Discovery Humans Machine Learning Protein Interaction Maps Gene Ontology
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The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development.

BMC bioinformatics Mar 22, 2022
BACKGROUND: Ontologies of precisely defined, controlled vocabularies are essential to curate the results of biological experiments such that the data are machine searchable, can be computationally analyzed, and are interoperable across the biomedical...
Animals Biological Ontologies Gene Ontology Xenopus laevis Humans Phenotype
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Establishment of a Combined Diagnostic Model of Abdominal Aortic Aneurysm with Random Forest and Artificial Neural Network.

BioMed research international Mar 7, 2022
OBJECTIVES: Abdominal aortic aneurysm (AAA), a disease with high mortality, is limited by the current diagnostic methods in the early screening. This study aimed to screen novel and significant biomarkers and construct a diagnostic model for AAA by u...
Gene Ontology Humans Neural Networks, Computer Aortic Aneurysm, Abdominal Diagnosis, Computer-Assisted Metabolic Networks and Pathways Databases, Genetic
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Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin.

International journal of molecular sciences Feb 24, 2022
To better understand the molecular basis of respiratory diseases of viral origin, high-throughput gene-expression data are frequently taken by means of DNA microarray or RNA-seq technology. Such data can also be useful to classify infected individual...
COVID-19 Algorithms Reproducibility of Results SARS-CoV-2 Neural Networks, Computer Machine Learning Humans RNA-Seq Gene Expression Profiling Gene Ontology Transcriptome
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Identification of a novel four-gene diagnostic signature for patients with sepsis by integrating weighted gene co-expression network analysis and support vector machine algorithm.

Hereditas Feb 21, 2022
Sepsis is a life-threatening condition in which the immune response is directed towards the host tissues, causing organ failure. Since sepsis does not present with specific symptoms, its diagnosis is often delayed. The lack of diagnostic accuracy res...
Support Vector Machine Humans Gene Ontology Algorithms Sepsis Gene Regulatory Networks Gene Expression Profiling
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