AIMC Topic: Molecular Sequence Annotation
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GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation.
Bioinformatics (Oxford, England)
Sep 1, 2024
SUMMARY: The vast majority of proteins still lack experimentally validated functional annotations, which highlights the importance of developing high-performance automated protein function prediction/annotation (AFP) methods. While existing approache...
Integration of background knowledge for automatic detection of inconsistencies in gene ontology annotation.
Bioinformatics (Oxford, England)
Jun 28, 2024
MOTIVATION: Biological background knowledge plays an important role in the manual quality assurance (QA) of biological database records. One such QA task is the detection of inconsistencies in literature-based Gene Ontology Annotation (GOA). This man...
Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks.
Bioinformatics (Oxford, England)
Jun 28, 2024
MOTIVATION: Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and ...
From tradition to innovation: conventional and deep learning frameworks in genome annotation.
Briefings in bioinformatics
Mar 27, 2024
Following the milestone success of the Human Genome Project, the 'Encyclopedia of DNA Elements (ENCODE)' initiative was launched in 2003 to unearth information about the numerous functional elements within the genome. This endeavor coincided with the...
scMMT: a multi-use deep learning approach for cell annotation, protein prediction and embedding in single-cell RNA-seq data.
Briefings in bioinformatics
Jan 22, 2024
Accurate cell type annotation in single-cell RNA-sequencing data is essential for advancing biological and medical research, particularly in understanding disease progression and tumor microenvironments. However, existing methods are constrained by s...
Deepdefense: annotation of immune systems in prokaryotes using deep learning.
GigaScience
Jan 2, 2024
BACKGROUND: Due to a constant evolutionary arms race, archaea and bacteria have evolved an abundance and diversity of immune responses to protect themselves against phages. Since the discovery and application of CRISPR-Cas adaptive immune systems, nu...
Interpreting Gene Ontology Annotations Derived from Sequence Homology Methods.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2024
The Gene Ontology (GO) project describes the functions of the gene products of organisms from all kingdoms of life in a standardized way, enabling powerful analyses of experiments involving genome-wide analysis. The scientific literature is used to c...
HNetGO: protein function prediction via heterogeneous network transformer.
Briefings in bioinformatics
Sep 22, 2023
Protein function annotation is one of the most important research topics for revealing the essence of life at molecular level in the post-genome era. Current research shows that integrating multisource data can effectively improve the performance of ...
CoCoNat: a novel method based on deep learning for coiled-coil prediction.
Bioinformatics (Oxford, England)
Aug 1, 2023
MOTIVATION: Coiled-coil domains (CCD) are widespread in all organisms and perform several crucial functions. Given their relevance, the computational detection of CCD is very important for protein functional annotation. State-of-the-art prediction me...
PFresGO: an attention mechanism-based deep-learning approach for protein annotation by integrating gene ontology inter-relationships.
Bioinformatics (Oxford, England)
Mar 1, 2023
MOTIVATION: The rapid accumulation of high-throughput sequence data demands the development of effective and efficient data-driven computational methods to functionally annotate proteins. However, most current approaches used for functional annotatio...
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