Multi-omics and AI integration reveal complex cancer microbiome patterns, advancing understanding and potential clinical applications.
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Genome Biology
BioMed Central · Genomics & Bioinformatics · ISSN 1465-6906
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Multi-omics and AI integration reveal complex cancer microbiome patterns, advancing understanding and potential clinical applications.
- 1 opens in JClub
- Open access
Genolator, a multimodal large language model, achieves over 365,000 question-answer pairs to accurately interpret protein functions from genomic and structural data.
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Dicast achieves 20% higher detection of candidate pathogenic deletions than consensus methods in short-read sequencing data.
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Ancient inland southwestern Finland shows continuous population genetics over a millennium, while coastal areas experienced significant genetic shifts since the Early Medieval period.
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COSIGT accurately genotypes complex loci from low-coverage sequencing, outperforming existing tools at 1-2X coverage and enabling population-scale analysis.
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Bakta and PGAP outperform other tools in annotating diverse prokaryotic genomes, with Bakta excelling in bacteria and PGAP in archaea and challenging assemblies.
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Genes linked to human polygenic traits show significantly higher connectivity in protein-protein interaction networks, with 4,756 phenotypes analyzed revealing key patterns.
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Genomic factors influencing mutation susceptibility are largely consistent across 25 human tissues, with chromatin structure and sequence context playing key roles.
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Deep learning splicing models rely on confounders and blind spots, resulting in systematic errors and poor performance on non-reference sequences.
SpatialDecon and cell2location achieve the most reliable cross-platform cell-type deconvolution, maintaining accuracy despite technological biases in transcriptomic data.
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Moving areas, week to 3 Oct 2026
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