Collaborative graphical lasso improves multi-omics network reconstruction by integrating data across layers, recovering known interactions and revealing new biological connections.
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Bioinformatics and Genomic Networks
Moving in Bioinformatics, Cell Genomics.
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A reconstructed protein interactome from LECA reveals ancient systems linked to modern genetic diseases, including novel associations for bone density and birth defects.
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Latest in Bioinformatics and Genomic Networks
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Embeddings from genome and protein language models enable high-resolution, alignment-free insights into genomics and proteomics, surpassing traditional methods.
Multimodal lineage tracing combined with advanced computational methods enables detailed reconstruction of cellular development with high accuracy and resolution.
Engineering translation control enables predictable gene expression by tuning initiation, elongation, and termination processes in biological systems.
Distinct tau polymorphs in Alzheimer’s, PSP, and DLB associate with unique protein networks, with 493 high-confidence interactors revealing disease-specific patterns.
- Open access
Protein interaction networks in a mouse tauopathy model undergo significant, phosphorylation-dependent remodeling, with over 20 key complexes showing dynamic changes during disease progression.
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BatchVaria reveals that subtype-protected ComBat maintains nearly unchanged subtype contributions after correction, unlike naive ComBat which reduces them by 4.23%.
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SpaCEy, an explainable graph neural network, predicts clinical outcomes from spatial proteomics data with 100% accuracy in identifying key tissue patterns.
- Open access
PTMExplorer enables multi-dimensional visualization of protein PTMs, integrating structural, functional, and disease data across eight model organisms, enhancing biological insights.
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