design-dsrna
Design dsRNA candidates using sliding window algorithm
Design dsRNA candidates using sliding window algorithm
Integrate real-world street networks into VRP problems using OpenStreetMap data. Use when loading real map data, creating instances from actual locations, computing network-based distances, or building tutorials with real-world scenarios. Guides through installation, loading areas, extracting nodes, computing distance matrices, and creating PDPTW instances from map data.
This skill should be used when the user needs to visualize BAM alignment files in IGV (Integrative Genomics Viewer). Triggers include requests to generate IGV screenshots, visualize genomic regions with multiple BAM tracks, or create batch visualizations for WGS analysis results.
Visualization patterns for sparse single-cell gene expression data. Trigger: boxplots flat at zero, single-cell expression plots, sparse data visualization
ENVI spatial transcriptomics analysis toolkit - comprehensive documentation with tutorials and Python source code
ArchR docs served from downloaded_docs/archr_scrape - comprehensive scATAC-seq analysis toolkit with all HTML files explicitly listed
Network meta-analysis for comparing multiple treatments
LigandMPNN sequence design reference. Use when working with LigandMPNN, ProteinMPNN, sequence design, amino acid biasing, fixed residues, temperature, side chain packing, or membrane protein design.
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
Phase 1 of MIP pipeline - Research Gatsby metaphor scholarship, establish seed CMT systems, and document MIP procedure for annotators.
Teach Trial Sequential Analysis (TSA) for controlling type I and II errors in cumulative meta-analyses. Use when users need to assess if meta-analysis has sufficient information, want to avoid premature conclusions, or need to plan future trials.
Isolates skin regions from background clutter using calibrated thresholds for downstream analysis
Fast repository indexing for RLM workflows. Use before analysis to reduce context drift.
Run LAMMPS molecular dynamics simulations. Use when asked to run MD simulations, energy minimization, equilibration, production runs, or calculate properties like diffusion, RDF, MSD. Supports both CPU and GPU execution.
Process bulk RNA-seq datasets for VEuPathDB resources
This skill should be used when the user needs to query COSMIC Cancer Gene Census to check if genes are known cancer genes. Triggers include requests to annotate genes with cancer information, check if variants are in cancer genes, or retrieve cancer gene properties from COSMIC database.
Machine learning integration patterns for rRNA-Phylo covering three use cases - rRNA sequence classification (supervised learning with sklearn/PyTorch), multi-tree consensus (ensemble methods), and generative tree synthesis (GNNs/transformers). Includes feature engineering, model training, hyperparameter tuning, model serving, versioning, and evaluation metrics for bioinformatics ML workflows.
R-based single cell analysis using Seurat v5 for .rds/.rdata files
Survival analysis methods including weighted logrank, MaxCombo, RMST, and milestone tests. Use when analyzing TTE data or choosing analysis methods for non-proportional hazards.
Complete meta-analysis generation for neurosurgical outcomes
Master tidy modelling patterns for ITC analyses following TMwR principles. Covers workflow structure, consistent interfaces, reproducibility best practices, and data validation. Use when setting up ITC analysis projects or building pipelines.