AI Medical Compendium Journal:
BMC genomics

Showing 11 to 20 of 132 articles

Improving genetic variant identification for quantitative traits using ensemble learning-based approaches.

BMC genomics
BACKGROUND: Genome-wide association studies (GWAS) are rapidly advancing due to the improved resolution and completeness provided by Telomere-to-Telomere (T2T) and pangenome assemblies. While recent advancements in GWAS methods have primarily focused...

UTR-Insight: integrating deep learning for efficient 5' UTR discovery and design.

BMC genomics
The 5' UTR is critical for mRNA stability and translation efficiency in therapeutics. We developed UTR-Insight, a model integrating a pretrained language model with a CNN-Transformer architecture, explaining 89.1% of the mean ribosome load (MRL) vari...

Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.

BMC genomics
Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved in complex human diseases through interactions with proteins. Accurate identification of lncRNA-protein interactions (LPI) can help elucidate the func...

Gene ontology defines pre-post- hatch energy dynamics in the complexus muscle of broiler chickens.

BMC genomics
BACKGROUND: Chicken embryos emerge from their shell by the piercing movement of the hatching muscle. Although considered a key player during hatching, with activity that imposes a substantial metabolic demand, data are still limited. The study provid...

Addressing statistical challenges in the analysis of proteomics data with extremely small sample size: a simulation study.

BMC genomics
BACKGROUND: One of the most promising approaches for early and more precise disease prediction and diagnosis is through the inclusion of proteomics data augmented with clinical data. Clinical proteomics data is often characterized by its high dimensi...

Interpreting deep neural networks for the prediction of translation rates.

BMC genomics
BACKGROUND: The 5' untranslated region of mRNA strongly impacts the rate of translation initiation. A recent convolutional neural network (CNN) model accurately quantifies the relationship between massively parallel synthetic 5' untranslated regions ...

Interpretation knowledge extraction for genetic testing via question-answer model.

BMC genomics
BACKGROUND: Sequencing-based genetic testing is widely used in biomedical research, including pathogenic microorganism detection with metagenomic next-generation sequencing (mNGS). The application of sequencing results to clinical diagnosis and treat...

sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms.

BMC genomics
BACKGROUND: Bacterial small regulatory RNA (sRNA) plays a crucial role in cell metabolism and could be used as a new potential drug target in the treatment of pathogen-induced disease. However, experimental methods for identifying sRNAs still require...

Deep neural network models for cell type prediction based on single-cell Hi-C data.

BMC genomics
BACKGROUND: Cell type prediction is crucial to cell type identification of genomics, cancer diagnosis and drug development, and it can solve the time-consuming and difficult problem of cell classification in biological experiments. Therefore, a compu...

simona: a comprehensive R package for semantic similarity analysis on bio-ontologies.

BMC genomics
BACKGROUND: Bio-ontologies are keys in structuring complex biological information for effective data integration and knowledge representation. Semantic similarity analysis on bio-ontologies quantitatively assesses the degree of similarity between bio...