Skill UI

This skill provides comprehensive tools to analyze and engineer protein glycosylation patterns. It scans amino acid sequences for canonical N-glycosylation sequons (N-X-S/T) and predicts O-glycosylation hotspots. Use cases include optimizing therapeutic antibodies, designing vaccine antigens, and characterizing biosimilars by rationally modifying glycan structures for improved stability, function, or immune evasion.

This comprehensive skill provides a standardized pipeline for reconstructing the evolutionary history of biological sequences (genes, proteins, genomes). It guides users through essential steps, including multiple sequence alignment using MAFFT, maximum likelihood tree inference with IQ-TREE 2, and visualization with ETE3. Ideal for research in viral phylodynamics, molecular clock studies, and large-scale comparative genomics.

A comprehensive Python wrapper for OpenMS, designed for sophisticated computational mass spectrometry workflows. It supports end-to-end analysis in proteomics and metabolomics, enabling feature detection, peptide/protein identification, quantitative analysis (label-free/isobaric), and adduct/accurate mass annotation. Ideal for researchers processing complex LC-MS/MS raw data and running high-level pipelines.

scikit-bio is a comprehensive Python library designed for advanced bioinformatics and biological data analysis. It provides robust capabilities for sequence manipulation (DNA, RNA, Protein), performing complex sequence alignments (pairwise and multiple), constructing and analyzing phylogenetic trees, and calculating diverse ecological metrics. It is essential for microbiome analysis, evolutionary studies, and general biological data processing, supporting standard formats like FASTA, Newick, and BIOM.