5,819 件 ・ 関連度順
概要と使いどころ
Run Bayesian phylogenetic analysis with MrBayes, BEAST2, RevBayes, and PhyloBayes including MCMC convergence diagnostics and model comparison. Use when needing posterior probability support, Bayesian model averaging, site-heterogeneous models for deep phylogenies, or formal model comparison via stepping-stone sampling.
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Remove batch effects from RNA-seq data using ComBat, ComBat-Seq, limma removeBatchEffect, and SVA for unknown batch variables. Use when correcting batch effects in expression data.
日本語の概要は準備中です。原文の説明を表示しています。
Assess genome assembly quality using QUAST for contiguity metrics and BUSCO for completeness. Essential for evaluating assembly success and comparing assemblers. Use when evaluating assembly completeness and quality.
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Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified base detection, and quality filtering. Use when processing raw Nanopore data before alignment. Note: Guppy is deprecated; use Dorado for all new analyses.
日本語の概要は準備中です。原文の説明を表示しています。
Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Automated and marker-guided single-cell cell type annotation using CellTypist, marker review, reference transfer, and confidence-aware label curation.
日本語の概要は準備中です。原文の説明を表示しています。
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 before sequence design. This skill is based on the public NVIDIA Digital Bio Proteina project and uses "Proteina-Complexa" as the BioClaw-facing skill label. For sequence design after backbone generation, use proteinmpnn or solublempnn. For QC thresholds, use protein-design-qc.
日本語の概要は準備中です。原文の説明を表示しています。
Run BLAST sequence similarity searches. Use when the user asks to BLAST a sequence, find similar sequences, identify a gene/protein, or do homology search. Triggers on "blast", "sequence similarity", "homology", "identify sequence".
日本語の概要は準備中です。原文の説明を表示しています。
Workflow for small RNA and miRNA preprocessing, quantification, differential analysis, and target-oriented interpretation.
日本語の概要は準備中です。原文の説明を表示しています。
Query ClinVar for clinical variant significance. Use when user asks about variant pathogenicity, genetic variants, clinical significance, or disease-causing mutations. Triggers on "clinvar", "pathogenic", "variant significance", "clinical significance", "disease variant", "mutation pathogenicity".
日本語の概要は準備中です。原文の説明を表示しています。
Query InterPro for protein domains and families. Use when user asks about protein domains, functional sites, protein families, domain architecture, or motifs. Triggers on "interpro", "protein domain", "domain architecture", "protein family", "functional site", "motif".
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Query UniProt protein database. Use when user asks about protein sequences, functions, annotations, domains, or protein identifiers. Triggers on "uniprot", "protein function", "protein sequence", "gene product", "protein info".
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Query NCBI GEO for gene expression datasets. Use when user asks about RNA-seq datasets, microarray data, expression data, GEO accessions, or finding public datasets. Triggers on "geo", "gene expression omnibus", "expression dataset", "RNA-seq dataset", "microarray dataset", "GSE", "GDS".
日本語の概要は準備中です。原文の説明を表示しています。
Structure retrieval, confidence-aware AlphaFold DB usage, coordinate download, PAE and pLDDT interpretation, and structure-guided biological annotation.
日本語の概要は準備中です。原文の説明を表示しています。
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 composite scoring. This skill provides research-backed thresholds from binder design competitions and published benchmarks.
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Predicts ADMET properties using ADMETlab 3.0 (119 endpoints with uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES gold-standard endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB druglikeness filters. Use when filtering compounds for drug-likeness, prioritizing leads by predicted safety, or building an in-house ADMET QSAR model.
日本語の概要は準備中です。原文の説明を表示しています。
Query Ensembl for genomic data. Use when user asks about gene coordinates, genomic sequences, variants, gene structure, exons, transcripts, or species comparison. Triggers on "ensembl", "gene coordinates", "genomic location", "exon", "transcript", "variant location", "rsid", "rs number".
日本語の概要は準備中です。原文の説明を表示しています。
Bulk transcriptomics differential expression with count-aware modeling, design validation, contrast handling, thresholded exports, and publication-ready DE figures.
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Analyze DNA/RNA/protein sequences. Use when the user provides a sequence and asks for analysis, translation, GC content, ORFs, motifs, restriction sites, or primer design. Triggers on "sequence", "translate", "GC content", "ORF", "primer", "restriction", "complement", "reverse complement".
日本語の概要は準備中です。原文の説明を表示しています。
Identify direct miRNA-target interactions from AGO HITS-CLIP, AGO-CLEAR-CLIP (chimeric reads), HEAP (Halo-Ago2 mouse), chimeric eCLIP / miR-eCLIP (deep miRNA-target profiling), or CLASH using chimeric-read processing pipelines, seed-pairing analysis, and 3' auxiliary pairing rules. Use when distinguishing direct miRNA targets from indirect, integrating CLIP-derived target maps with TargetScan / miRDB / DIANA predictions, applying canonical 7mer-8mer seed matching with 3' UTR context, or recovering miRNA-mRNA chimeras at scale.
日本語の概要は準備中です。原文の説明を表示しています。
Workflow for gene and transcript quantification from RNA-seq reads using alignment-based or alignment-free tools.
日本語の概要は準備中です。原文の説明を表示しています。
Biology research tools reference. Always available inside agent containers.
日本語の概要は準備中です。原文の説明を表示しています。
Query AlphaFold protein structure predictions. Use when user asks about protein structure, 3D structure, protein folding, or structure prediction. Triggers on "alphafold", "protein structure", "3D structure", "folding", "pLDDT", "structure prediction".
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。