This skill provides comprehensive integration with protocols.io API for managing scientific protocols. Use it to search existing protocols, create new protocols, manage collaborative workspaces, handle discussions, and organize laboratory documentation workflows.

Transform research content into professional research posters using HTML and CSS with AI-generated visuals. Export to PDF for printing or convert to PowerPoint for conference presentations.

This skill enables AI-powered web searches to find current information, recent scientific research, and grounded answers with source citations. It provides access to multiple Perplexity models through a single OpenRouter API key.

Access the RCSB Protein Data Bank to search for and download 3D structures of proteins and nucleic acids. This skill enables structural biology research, drug discovery, and protein engineering by providing programmatic access to over 200,000 experimentally determined and computationally modeled molecular structures.

PathML streamlines computational pathology workflows by providing unified tools for loading diverse slide formats, preprocessing images, and training ML models. Researchers can analyze whole-slide images, build tissue graphs, and quantify multiplex immunofluorescence data in a single framework.

Writing lab automation protocols requires specialized knowledge of robotics APIs and liquid handling procedures. This skill provides ready-to-use templates and comprehensive guidance for creating protocols that control Opentrons liquid handling robots.

Researchers spend hours searching through academic databases to find relevant papers and analyze research trends. This skill provides direct access to OpenAlex 240M+ scholarly works with powerful filtering, citation analysis, and bibliometric capabilities for efficient literature discovery.

Analyze physiological signals including ECG, EEG, EDA, and EMG for research and clinical applications. NeuroKit2 provides a unified Python toolkit for processing cardiovascular, neural, and autonomic nervous system data with comprehensive visualization and analysis tools.

Molecular machine learning requires converting chemical structures into numerical representations. Molfeat provides 100+ featurizers to transform SMILES strings into machine learning-ready features for QSAR modeling and drug discovery.

Search and retrieve metabolomics data from the NIH Metabolomics Workbench database containing 4,200+ studies. Access metabolite structures, study metadata, RefMet nomenclature, and perform mass spectrometry searches.

Mass spectrometry data contains complex spectral information that requires specialized processing. Matchms provides comprehensive tools to import, filter, and compare mass spectra for metabolite identification and compound analysis.

Create comprehensive 50+ page market research reports with professional LaTeX formatting. Generate strategic visuals, perform multi-framework analysis, and produce consulting-quality deliverables for business decisions.

Conducting literature reviews manually wastes hours searching databases and formatting citations. This skill automates systematic literature reviews by searching PubMed, arXiv, bioRxiv, and Semantic Scholar, verifying all citations, and generating professional PDFs.

Manage electronic lab notebooks programmatically. Automate data uploads, backup notebooks, and integrate with scientific tools like Jupyter and REDCap for research workflows.

Researchers need efficient access to KEGG bioinformatics data for pathway analysis and gene mapping. This skill provides Python helper functions for all KEGG REST API operations including pathway retrieval, gene-pathway mapping, compound searches, and ID conversion between databases.

Transform observations into structured, testable scientific hypotheses. This skill guides you through literature synthesis, mechanism development, experimental design, and prediction formulation using proven scientific method frameworks.

Researchers need efficient access to gene expression datasets for analysis. This skill enables querying, downloading, and analyzing data from NCBI's GEO database containing millions of genomics samples.

Geniml transforms BED files into machine learning embeddings for genomic region analysis. Train models to find patterns in chromatin accessibility, build consensus peak sets, and analyze single-cell ATAC-seq data.

Access comprehensive gene data from NCBI including sequences, annotations, and functional information. Search by gene symbol, ID, or biological context to retrieve RefSeqs, Gene Ontology, chromosomal locations, and phenotypes for bioinformatics research.

FluidSim brings high-performance computational fluid dynamics to Python. Run Navier-Stokes simulations, analyze turbulence, and visualize results with simple Python commands. No complex Fortran or C++ setup required.