リポジトリの README を読み込んでいます…
収集済み skill 373 件中 40 件を表示しています。
Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when…
原文の言語: 英語
Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.
原文の言語: 英語
Computational cancer genomics workflows. Somatic mutation detection and annotation, structural variation characterization, copy number analysis, tumor purity/ploidy estimation, NMF metagene extraction, and DNA damage response network analysis. For cancer…
原文の言語: 英語
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
原文の言語: 英語
Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.
原文の言語: 英語
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with…
原文の言語: 英語
Complete flow cytometry analysis pipeline. FCS file handling, compensation, manual/automated gating, immunophenotyping, CFSE proliferation analysis, cell cycle analysis (Dean-Jett-Fox), and apoptosis assays. Extends flowio with analytical workflows. For raw…
原文の言語: 英語
Synthetic biology design and simulation tools. Codon optimization, gene circuit ODE modeling with growth feedback, SBML model creation, bifurcation analysis, barcode sequencing fitness analysis, and therapeutic genome engineering. For metabolic modeling use…
原文の言語: 英語
Analyze 1D 1H or 13C NMR data with nmrglue, generate spectrum plots and peak tables, compare against standard NMR libraries such as BMRB, HMDB, SDBS, and nmrshiftdb2, then produce a ranked candidate-compound report with evidence, caveats, and direct links.
原文の言語: 英語
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for…
原文の言語: 英語
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning…
原文の言語: 英語
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression…
原文の言語: 英語
Convert genomic intervals between coordinate conventions, normalise and compare variant representations, and detect assembly or contig-naming mismatches before they corrupt an analysis. Use whenever coordinates cross a format, tool, or assembly boundary -…
原文の言語: 英語
Assigns cell-type labels to clusters from a protein marker panel (multiplexed imaging such as MIBI, CODEX, IMC and CyCIF; mass and flow cytometry; CITE-seq protein), where the labels are judged against an expert reference. Within-dataset normalisation of…
原文の言語: 英語
Turns a crystal structure (CIF) of a hydrogen-bonded, coordination or covalent framework into its underlying net and the quantities a topology question asks for: node definition, the periodic quotient graph, connectivity as distinct neighbours rather than…
原文の言語: 英語
Turns the acceptance criteria a task states into executable checks and runs them against the finished outputs before delivering, rather than trusting that a correct-looking analysis satisfies them; rehearses the hidden condition when the grader scores unseen…
原文の言語: 英語
Writes the trace and report for an analysis whose output a reader will judge, restating the question with its binding clauses, recording data provenance, the method with every parameter that matters, results with raw and adjusted numbers and uncertainty, the…
原文の言語: 英語
Runs a hill-climbing study over many training or analysis runs with the study and experiments tools, one metric and direction, a baseline, ideas ranked by expected value, exactly one run per idea, kill criteria and a budget, verdicts with analysis and…
原文の言語: 英語
Chooses and runs compute for research work, local shell or kernel versus a detached compute_job on this machine, a saved SSH or Slurm host, or Modal GPUs, with the target discovered from what is actually configured, the run sized and priced before dispatch,…
原文の言語: 英語
Delegates independent work to worker agents through the Task tool, choosing between the explore scout and the ml, biology, physics, chemistry and data specialists, writing a self-contained brief for a worker that cannot see the conversation, setting…
原文の言語: 英語
Runs computations so they finish, reproduce and fit the machine that will re-execute them, detaching long jobs through compute_job instead of blocking or sleeping shells, checkpointing so reruns resume, fixing seeds and capping BLAS and OpenMP threads,…
原文の言語: 英語
Chooses and reports statistical tests the way a careful referee expects, deciding paired versus unpaired and parametric versus rank-based from the design, using ordered-trend tests such as Jonckheere-Terpstra and Cochran-Armitage for dose or grade levels,…
原文の言語: 英語
Writes code that survives being re-executed by someone else on inputs you never saw, targeting the grader's or collaborator's runtime rather than your own, with one self-contained entry point using only the libraries the specification names, no reliance on…
原文の言語: 英語
Solve partial differential equations — finite differences, spectral methods, and physics-informed neural networks (PINNs via DeepXDE). Supports 1D/2D/3D, steady/transient, linear/nonlinear PDEs with Dirichlet, Neumann, and periodic boundary conditions.
原文の言語: 英語
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional…
原文の言語: 英語
Fast LLM fine-tuning with Unsloth - 2-5x faster training, 50-80% less VRAM. Use for single-GPU LoRA/QLoRA SFT, GRPO/RL reasoning training, vision/TTS fine-tuning, and GGUF export to Ollama/vLLM/llama.cpp. Supports 300+ models including Llama, Qwen, Gemma,…
原文の言語: 英語
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
原文の言語: 英語
Creates or refines publication-quality technical diagrams with the native generate_image tool (Nano Banana Pro through Ace or a Gemini key, GPT Image 2 through an OpenAI key), method and architecture overviews, pipelines, CONSORT and PRISMA flows,…
原文の言語: 英語
Run NVIDIA BioNeMo NIMs through the hosted scientific_capability tool with your own NVIDIA API key. Boltz-2 and OpenFold2/OpenFold3 structure prediction, MSA Search alignments, DiffDock docking, ProteinMPNN sequence design, RFdiffusion backbones, GenMol and…
原文の言語: 英語
Design and validate de novo protein binders with the current NVIDIA BioNeMo Agent Toolkit workflow, while adapting honestly when NVIDIA-hosted credentials are unavailable.
原文の言語: 英語
Writes and revises machine-learning papers for NeurIPS, ICML, ICLR, ACL, COLM and AAAI, from a research repository or a set of tracked runs to a compiling LaTeX draft in the venue's template, with the contribution stated as claims backed by experiments,…
原文の言語: 英語
Writes and revises scientific manuscripts, journal articles, preprints, theses, reports, in full paragraphs with the argument built from the project's actual results and sources, as a real .tex or .md file in the working folder. Use for drafting or revising a…
原文の言語: 英語
Makes publication-quality plots from data with matplotlib, learning curves, scaling laws, benchmark and ablation comparisons, Pareto trade-offs, heatmaps and confusion matrices, sized for the page, vector, with uncertainty shown. Use whenever results are…
原文の言語: 英語
Generates or edits images with the native generate_image tool (Nano Banana Pro through Ace or a Gemini key, GPT Image 2 through an OpenAI key), for illustrations, cover art, graphical abstracts, conceptual visuals, photo-style figures and edits of existing…
原文の言語: 英語
Creates and audits truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn or Plotly, covering figure design, multi-panel layouts, uncertainty and missing-data displays, colour and contrast review, image metadata validation and…
原文の言語: 英語
[EXPERIMENTAL] Build slide decks and presentations for research talks using Nano Banana Pro AI. Generates stunning PDF presentations with AI-generated slides. Use for conference presentations, seminar talks, thesis defense slides, or any scientific talk.…
原文の言語: 英語
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
原文の言語: 英語
Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating…
原文の言語: 英語
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick…
原文の言語: 英語
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database…
原文の言語: 英語
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