Claude Skills by zongtingwei

Workflow for read alignment, sorting, indexing, mapping statistics, and downstream-ready alignment artifacts.

Workflow for retrieving public omics datasets, sequences, annotations, and literature-linked biological resources.

Workflow for sequencing read QC, trimming, contamination screening, and pre-alignment cleanup.

Workflow for packaging analysis outputs into reproducible reports, clean tables, and publication-ready figure exports.

Workflow for foundational sequence parsing, conversion, compression handling, and interval-aware file validation.

Workflow for orchestrating reproducible omics pipelines with workflow engines and clear execution provenance.

End-to-end EHR predictive modeling pipeline with PyHealth, covering dataset loading, task definition, model training, evaluation, calibration, and clinical interpretation.

ATAC-seq processing with assay QC, MACS3 peak calling, consensus peak matrices, differential accessibility, and motif or footprint follow-up.

ChIP-seq peak calling and downstream interpretation with MACS3, signal track export, annotation, motif analysis, and differential binding review.

Workflow for RNA modification analysis such as m6A peak calling, differential modification, and transcript-level visualization.

Workflow for regulatory network inference, regulon scoring, perturbation-aware comparison, and network visualization.

Workflow for Hi-C and related 3D genomics analyses including compartments, loops, TADs, differential contacts, and visualization.

Workflow for methylation alignment or calling, DMR analysis, methylation QC, and locus-level interpretation.

Workflow for orthology, synteny, ancestral reconstruction, and evolutionary comparison across genomes.

Workflow for copy-number estimation, segmentation, annotation, and visualization in sequencing-based assays.

Workflow for de novo assembly, scaffolding, polishing, contamination review, and assembly QC.

Workflow for nanopore or PacBio long-read QC, alignment, polishing, methylation-aware analysis, and structural variant discovery.

Workflow for haplotype phasing, genotype imputation, reference-panel matching, and imputation QC.

Workflow for small-variant and structural-variant discovery, filtering, annotation, and interpretation from sequencing data.

Shotgun metagenomics workflow with host-depletion-aware QC, taxonomic profiling, functional profiling, AMR follow-up, and reproducible community output tables.

Workflow for amplicon microbiome analysis including denoising, taxonomy assignment, diversity analysis, and differential abundance.

Workflow for outbreak-style pathogen genomics, surveillance, lineage assignment, and transmission-oriented comparative analysis.

Workflow for multiple sequence alignment, tree inference, annotated tree visualization, and distance-based evolutionary comparison.

Workflow for fine-mapping, colocalization, mediation, pleiotropy analysis, and Mendelian randomization.

Workflow for predictive modeling, biomarker discovery, survival modeling, and explainability over omics-derived features.

Workflow for integrating matched or partially matched omics layers into shared latent structure and cross-modal interpretation.

Workflow for enrichment testing, ranked-gene analysis, pathway scoring, and pathway-focused visualization across omics outputs.

Workflow for constraint-based metabolic modeling, context-specific models, gene essentiality, and systems-level interpretation.

AlphaFold2 / AlphaFold-Multimer structure prediction for validation and confidence scoring. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm2-sequence-scoring. For QC thresholds, use protein-design-qc.

End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-design-qc. For tool selection guidance, use binder-design-tool-selection.

Binder design campaign planning, monitoring, and troubleshooting. Use this skill when: (1) Planning a complete binder design campaign, (2) Converting high-level goals into runnable pipelines, (3) Assessing campaign health and pass rates, (4) Diagnosing why designs are failing QC, (5) Estimating time, cost, and expected yields, (6) Selecting between design tools for a specific target. This skill orchestrates the other protein design tools. For individual tool parameters, use the specific tool...

Binder design tool selection and workflow routing guidance. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use the individual tool skills (boltzgen, bindcraft, rfdiffusion, etc.).

Boltz-1 / Boltz-2 structure prediction for proteins, complexes, and ligand-aware validation. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources. For QC thresholds, use protein-design-qc. For AlphaFold2 prediction, use alphafold2-multimer. For Chai prediction, use chai1-structure-prediction.

All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For backbone-only generation, use rfdiffusion. For sequence-only design, use proteinmpnn. For structure validation, use boltz-structure-prediction.

Cell-free protein synthesis (CFPS) planning and optimization guidance. Use when: (1) Planning CFPS experiments, (2) Troubleshooting low yield or aggregation, (3) Optimizing DNA template design for CFPS, (4) Expressing difficult proteins (disulfide-rich, toxic, membrane).

Chai-1 structure prediction for protein complexes and design validation. Use this skill when: (1) Predicting protein-protein complex structures, (2) Validating designed binders, (3) Predicting protein-ligand complexes, (4) Using the Chai API for high-throughput prediction, (5) Need an alternative to AlphaFold2. For QC thresholds, use protein-design-qc. For AlphaFold2 prediction, use alphafold2-multimer. For ESM-based analysis, use esm2-sequence-scoring.

End-to-end protein design pipeline guide across preparation, generation, validation, and filtering. Use this skill when: (1) Starting a new protein design project, (2) Need step-by-step workflow guidance, (3) Understanding the full design pipeline, (4) Planning compute resources and timelines, (5) Integrating multiple design tools. For tool selection, use binder-design-tool-selection. For QC thresholds, use protein-design-qc.

ESM2 protein language model for sequence scoring, embeddings, and plausibility checks. Use this skill when: (1) Computing pseudo-log-likelihood (PLL) scores, (2) Getting protein embeddings for clustering, (3) Filtering designs by sequence plausibility, (4) Zero-shot variant effect prediction, (5) Analyzing sequence-function relationships. For structure prediction, use chai1-structure-prediction or boltz-structure-prediction. For QC thresholds, use protein-design-qc.

Structure similarity search with Foldseek. Use this skill when: (1) Finding similar structures in PDB/AFDB databases, (2) Structural homology search, (3) Database queries by 3D structure, (4) Finding remote homologs not detected by sequence, (5) Clustering structures by similarity. For sequence similarity, use uniprot BLAST. For structure prediction, use chai1-structure-prediction or boltz-structure-prediction.

Binder design ranking using ipSAE (interprotein Score from Aligned Errors). Use this skill when: (1) Ranking binder designs for experimental testing, (2) Filtering BindCraft or RFdiffusion outputs, (3) Comparing AF2/AF3/Boltz predictions, (4) Predicting binding success rates, (5) Need better ranking than ipTM or iPAE. For structure prediction, use chai1-structure-prediction or alphafold2-multimer. For QC thresholds, use protein-design-qc.

Ligand-aware protein sequence design using LigandMPNN. Use this skill when: (1) Designing sequences around small molecules, (2) Enzyme active site design, (3) Ligand binding pocket optimization, (4) Metal coordination site design, (5) Cofactor binding proteins. For standard protein design, use proteinmpnn. For solubility optimization, use solublempnn.

Fetch and analyze protein structures from RCSB PDB. Use this skill when: (1) Need to download a structure by PDB ID, (2) Search for similar structures, (3) Prepare target for binder design, (4) Extract specific chains or domains, (5) Get structure metadata. For sequence lookup, use uniprot. For binder design workflow, use binder-design-tool-selection.

Protein design quality control, filtering thresholds, and ranking guidance. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage filtering pipelines, (5) Computing PyRosetta interface metrics (dG, SC, dSASA), (6) Checking biophysical properties (instability, GRAVY, pI), (7) Ranking designs with comp...

Proteina-Complexa flow-based protein backbone generation with fold-conditioned sampling guidance. Use this skill when: (1) Generating de novo protein backbones with hierarchical fold conditioning, (2) Exploring long-chain backbone generation beyond standard diffusion baselines, (3) Using NVIDIA Proteina-style flow matching workflows for controllable backbone design, (4) Comparing flow-based backbone generation against RFdiffusion or BoltzGen, (5) Prototyping fold-guided backbone campaigns bef...

Design protein sequences using ProteinMPNN inverse folding. Use this skill when: (1) Designing sequences for RFdiffusion backbones, (2) Redesigning existing protein sequences, (3) Fixing specific residues while designing others, (4) Optimizing sequences for expression or stability, (5) Multi-state or negative design. For backbone generation, use rfdiffusion or bindcraft. For ligand-aware design, use ligandmpnn. For solubility optimization, use solublempnn.

Generate protein backbones using RFdiffusion, a diffusion-based generative model for de novo protein structure generation. Use this skill when: (1) Designing binder scaffolds for a target protein, (2) Generating novel protein backbones from scratch, (3) Scaffolding functional motifs into new proteins, (4) Specifying hotspot residues for interface design, (5) Creating symmetric oligomers. For sequence design after backbone generation, use proteinmpnn. For structure validation, use alphafold2-...

First-time setup for protein design tools. Use this skill when: (1) User is new and hasn't run any tools yet, (2) Commands fail with "file not found" or "modal: command not found", (3) Modal authentication errors occur, (4) User asks how to get started or set up the environment, (5) biomodals directory is missing or tools aren't working.

Solubility-optimized protein sequence design using SolubleMPNN. Use this skill when: (1) Designing for E. coli expression, (2) Optimizing solubility of designed proteins, (3) Reducing aggregation propensity, (4) Need high-yield expression, (5) Avoiding inclusion body formation. For standard design, use proteinmpnn. For ligand-aware design, use ligandmpnn.

SPR and BLI assay planning, kinetic interpretation, and troubleshooting guidance. Use when: (1) Planning binding kinetics experiments, (2) Troubleshooting poor/no binding signal, (3) Interpreting kinetic data artifacts, (4) Choosing between SPR vs BLI platforms.

Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.