AIMC Topic: Genomics
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Geometric deep learning framework for de novo genome assembly.
Genome research
Apr 14, 2025
The critical stage of every de novo genome assembler is identifying paths in assembly graphs that correspond to the reconstructed genomic sequences. The existing algorithmic methods struggle with this, primarily due to repetitive regions causing comp...
Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics.
Scientific reports
Apr 10, 2025
Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitative measurements, although they could be concepts vital to understand pathogen epidemiology. This study demonstrates that the relative synonymous codon ...
Integrative Multi-Omics Analysis Reveals Molecular Subtypes of Ovarian Cancer and Constructs Prognostic Models.
Journal of immunotherapy (Hagerstown, Md. : 1997)
Apr 9, 2025
Ovarian cancer (OV) remains the most lethal gynecological malignancy. The aim of this study was to identify molecular subtypes of OV through integrative multi-omics analysis and construct machine learning-based prognostic models for predicting the ef...
DTreePred: an online viewer based on machine learning for pathogenicity prediction of genomic variants.
BMC bioinformatics
Apr 9, 2025
BACKGROUND: A significant challenge in precision medicine is confidently identifying mutations detected in sequencing processes that play roles in disease treatment or diagnosis. Furthermore, the lack of representativeness of single nucleotide varian...
MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles.
Genome biology
Apr 8, 2025
High-throughput multi-omic molecular profiling allows the probing of biological systems at unprecedented resolution. However, integrating and interpreting high-dimensional, sparse, and noisy multimodal datasets remains challenging. Deriving new biolo...
Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.
Journal of microbiological methods
Apr 7, 2025
Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential therapeutic targets by differentiating essential genes in pathogens and non-pathogenic genes. Since, identification of therapeutic targets and understand...
How did we get there? AI applications to biological networks and sequences.
Computers in biology and medicine
Apr 3, 2025
The rapidly advancing field of artificial intelligence (AI) has transformed numerous scientific domains, including biology, where a vast and complex volume of data is available for analysis. This paper provides a comprehensive overview of the current...
Machine learning and multi-omics integration: advancing cardiovascular translational research and clinical practice.
Journal of translational medicine
Apr 2, 2025
The global burden of cardiovascular diseases continues to rise, making their prevention, diagnosis and treatment increasingly critical. With advancements and breakthroughs in omics technologies such as high-throughput sequencing, multi-omics approach...
Causal machine learning for single-cell genomics.
Nature genetics
Mar 31, 2025
Advances in single-cell '-omics' allow unprecedented insights into the transcriptional profiles of individual cells and, when combined with large-scale perturbation screens, enable measuring of the effect of targeted perturbations on the whole transc...
Biological Prior Knowledge-Embedded Deep Neural Network for Plant Genomic Prediction.
Genes
Mar 31, 2025
Genomic prediction is a powerful approach that predicts phenotypic traits from genotypic information, enabling the acceleration of trait improvement in plant breeding. Traditional genomic prediction methods have primarily relied on linear mixed mode...
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