---
title: "Scientific Skills"
description: "- **Database Lookup** - Search 78 public scientific, biomedical, materials science, and economic databases via their REST APIs and return structured JSON results. Covers physics/astronomy (NASA, NIST, SDSS, SIMBAD, Exoplanet Archive), earth/environment (USGS, NOAA, EPA, OpenWeatherMap), chemistry/drugs (PubChem, ChEMBL, DrugBank, FDA, KEGG, DailyMed, ZINC, BindingDB), materials science (Materials "
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/scientific-skills
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:46:24.866Z
license: CC-BY-4.0
attribution: "Scientific Skills — Claudary (https://claudary.paisolsolutions.com/skills/scientific-skills)"
---

# Scientific Skills
- **Database Lookup** - Search 78 public scientific, biomedical, materials science, and economic databases via their REST APIs and return structured JSON results. Covers physics/astronomy (NASA, NIST, SDSS, SIMBAD, Exoplanet Archive), earth/environment (USGS, NOAA, EPA, OpenWeatherMap), chemistry/drugs (PubChem, ChEMBL, DrugBank, FDA, KEGG, DailyMed, ZINC, BindingDB), materials science (Materials 

## Overview

# Scientific Skills

## Scientific Databases & Data Access

- **Database Lookup** - Search 78 public scientific, biomedical, materials science, and economic databases via their REST APIs and return structured JSON results. Covers physics/astronomy (NASA, NIST, SDSS, SIMBAD, Exoplanet Archive), earth/environment (USGS, NOAA, EPA, OpenWeatherMap), chemistry/drugs (PubChem, ChEMBL, DrugBank, FDA, KEGG, DailyMed, ZINC, BindingDB), materials science (Materials Project, COD), biology/genomics (Reactome, BRENDA, UniProt, STRING, Ensembl, NCBI Gene, GEO, GTEx, PDB, AlphaFold, InterPro, ChEBI, BioGRID, Gene Ontology, QuickGO, NCBI Protein/Taxonomy, dbSNP, SRA, ENA, gnomAD, UCSC Genome, ENCODE, JASPAR, MouseMine, PRIDE, LINCS L1000, Human Protein Atlas, Human Cell Atlas, RummaGEO, Metabolomics Workbench, EMDB, Addgene), disease/clinical (COSMIC, Open Targets, ClinPGx, ClinicalTrials.gov, OMIM, ClinVar, GDC/TCGA, cBioPortal, DisGeNET, GWAS Catalog, Monarch, HPO), regulatory (FDA, USPTO, SEC EDGAR), economics/finance (FRED, BEA, BLS, Federal Reserve, World Bank, ECB, US Treasury, Alpha Vantage, Data Commons), and demographics (US Census, Eurostat, WHO). Use this skill whenever the user wants to look up compounds, drugs, proteins, genes, pathways, enzymes, gene expression, variants, clinical trials, patents, SEC filings, economic indicators, crystal structures, astronomical objects, earthquakes, weather, or any data from a public database API
- **DepMap** - Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets
- **Imaging Data Commons** - Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses
- **PrimeKG** - Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological data including genes, drugs, diseases, phenotypes, and more. Integrates 20+ biomedical resources into a single knowledge graph for drug repurposing, disease mechanism exploration, and target identification
- **U.S. Treasury Fiscal Data** - Free, open REST API from the U.S. Department of the Treasury providing 54 datasets and 182 data tables covering federal fiscal data. No API key required. Access national debt (Debt to the Penny back to 1993, Historical Debt back to 1790), Daily Treasury Statements (TGA balances, deposits/withdrawals), Monthly Treasury Statements (federal budget receipts and outlays), Treasury securities auctions data (bills, notes, bonds, TIPS, FRNs since 1979), average interest rates on Treasury securities, Treasury reporting exchange rates (quarterly for 170+ currencies), I Bond and savings bond rates, TIPS/CPI data, and more. Supports filtering, sorting, pagination, and CSV/XML/JSON output formats

## Scientific Integrations

### Laboratory Information Management Systems (LIMS) & R&D Platforms
- **Benchling Integration** - Toolkit for integrating with Benchling's R&D platform, providing programmatic access to laboratory data management including registry entities (DNA sequences, proteins), inventory systems (samples, containers, locations), electronic lab notebooks (entries, protocols), workflows (tasks, automation), and data exports using Python SDK and REST API

### Cloud Platforms for Genomics & Biomedical Data
- **DNAnexus Integration** - Comprehensive toolkit for working with the DNAnexus cloud platform for genomics and biomedical data analysis. Covers building and deploying apps/applets (Python/Bash), managing data objects (files, records, databases), running analyses and workflows, using the dxpy Python SDK, and configuring app metadata and dependencies (dxapp.json setup, system packages, Docker, assets). Enables processing of FASTQ/BAM/VCF files, bioinformatics pipelines, job execution, workflow orchestration, and platform operations including project management and permissions

### Laboratory Automation
- **Opentrons Integration** - Toolkit for creating, editing, and debugging Opentrons Python Protocol API v2 protocols for laboratory automation using Flex and OT-2 robots. Enables automated liquid handling, pipetting workflows, hardware module control (thermocycler, temperature, magnetic, heater-shaker, absorbance plate reader), labware management, and complex protocol development for biological and chemical experiments
- **Ginkgo Cloud Lab** - Submit and manage protocols on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio), a web-based interface for autonomous lab execution on Reconfigurable Automation Carts (RACs). Supports three protocols: Cell Free Protein Expression Validation ($39/sample, 5-10 day turnaround), Cell Free Protein Expression Optimization ($199/sample, DoE across 24 conditions, 6-11 days), and Fluorescent Pixel Art Generation ($25/plate, bacterial artwork with 11 fluorescent E. coli strains, 5-7 days). Includes EstiMate AI agent for custom protocol feasibility and pricing

### Electronic Lab Notebooks (ELN)
- **LabArchives Integration** - Toolkit for interacting with LabArchives Electronic Lab Notebook (ELN) REST API. Provides programmatic access to notebooks (backup, retrieval, management), entries (creation, comments, attachments), user authentication, site reports and analytics, and third-party integrations (Protocols.io, GraphPad Prism, SnapGene, Geneious, Jupyter, REDCap). Includes Python scripts for configuration setup, notebook operations, and entry management. Supports multi-regional API endpoints (US, UK, Australia) and OAuth authentication
- **Open Notebook** - Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Organizes research materials into notebooks, ingests diverse content sources (PDFs, videos, audio, web pages, Office documents), generates AI-powered notes and summaries, creates multi-speaker podcasts from research, enables document chat with context-aware AI, and searches across materials with full-text and vector search. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting

### Workflow Platforms & Cloud Execution
- **LatchBio Integration** - Integration with the Latch platform for building, deploying, and executing bioinformatics workflows. Provides comprehensive support for creating serverless bioinformatics pipelines using Python decorators, deploying Nextflow/Snakemake pipelines, managing cloud data (LatchFile, LatchDir) and structured Registry (Projects, Tables, Records), configuring computational resources (CPU, GPU, memory, storage), and using pre-built Latch Verified workflows (RNA-seq, AlphaFold, DESeq2, single-cell analysis, CRISPR editing). Enables automatic containerization, UI generation, workflow versioning, and execution on scalable cloud infrastructure with comprehensive data management

### Microscopy & Bio-image Data
- **OMERO Integration** - Toolkit for interacting with OMERO microscopy data management systems using Python. Provides comprehensive access to microscopy images stored in OMERO servers, including dataset and screening data retrieval, pixel data analysis, annotation and metadata management, regions of interest (ROIs) creation and analysis, batch processing, OMERO.scripts development, and OMERO.tables for structured data storage. Essential for researchers working with high-content screening data, multi-dimensional microscopy datasets, or collaborative image repositories

### Protocol Management & Sharing
- **Protocols.io Integration** - Integration with protocols.io API for managing scientific protocols. Enables programmatic access to protocol discovery (search by keywords, DOI, category), protocol lifecycle management (create, update, publish with DOI), step-by-step procedure documentation, collaborative development with workspaces and discussions, file management (upload data, images, documents), experiment tracking and documentation, and data export. Supports OAuth authentication, protocol PDF generation, materials management, threaded comments, workspace permissions, and institutional protocol repositories. Essential for protocol standardization, reproducibility, lab knowledge management, and scientific collaboration

## Scientific Packages

### Bioinformatics & Genomics
- **AnnData** - Python package for handling annotated data matrices, specifically designed for single-cell genomics data. Provides efficient storage and manipulation of high-dimensional data with associated annotations (observations/cells and variables/genes). Key features include: HDF5-based h5ad file format for efficient I/O and compression, integration with pandas DataFrames for metadata, support for sparse matrices (scipy.sparse) for memory efficiency, layered data organization (X for main data matrix, obs for observation annotations, var for variable annotations, obsm/varm for multi-dimensional annotations, obsp/varp for pairwise matrices), and seamless integration with Scanpy, scvi-tools, and other single-cell analysis packages. Supports lazy loading, chunked operations, and conversion to/from other formats (CSV, HDF5, Zarr). Use cases: single-cell RNA-seq data management, multi-modal single-cell data (RNA+ATAC, CITE-seq), spatial transcriptomics, and any high-dimensional annotated data requiring efficient storage and manipulation
- **Arboreto** - Python package for efficient gene regulatory network (GRN) inference from single-cell RNA-seq data using ensemble tree-based methods. Implements GRNBoost2 (gradient boosting-based network inference) and GENIE3 (random forest-based inference) algorithms optimized for large-scale single-cell datasets. Key features include: parallel processing for scalability, support for sparse matrices and large datasets (millions of cells), integration with Scanpy/AnnData workflows, customizable hyperparameters, and output formats compatible with network analysis tools. Provides ranked lists of potential regulatory interactions (transcription factor-target gene pairs) with confidence scores. Use cases: identifying transcription factor-target relationships, reconstructing gene regulatory networks from single-cell data, understanding cell-type-specific regulatory programs, and inferring causal relationships in gene expression
- **BioPython** - Comprehensive Python library for computational biology and bioinformatics providing tools for sequence manipulation, database access, and biological data analysis. Key features include: sequence objects (Seq, SeqRecord, SeqIO) for DNA/RNA/protein sequences with biological alphabet validation, file format parsers (FASTA, FASTQ, GenBank, EMBL, Swiss-Prot, PDB, SAM/BAM, VCF, GFF), NCBI database access (Entrez Programming Utilities for PubMed, GenBank, BLAST, taxonomy), BLAST integration (running searches, parsing results), sequence alignment (pairwise and multiple sequence alignment with Bio.Align), phylogenetics (tree construction and manipulation with Bio.Phylo), population genetics (Hardy-Weinberg, F-statistics), protein structure analysis (PDB parsing, structure calculations), and statistical analysis tools. Supports integration with NumPy, pandas, and other scientific Python libraries. Use cases: sequence analysis, database queries, phylogenetic analysis, sequence alignment, file format conversion, and general bioinformatics workflows
- **BioServices** - Python library providing unified programmatic access to 40+ biological web services and databases. Supports major bioinformatics resources including KEGG (pathway and compound data), UniProt (protein sequences and annotations), ChEBI (chemical entities), ChEMBL (bioactive molecules), Reactome (pathways), IntAct (protein interactions), BioModels (biological models), and many others. Features consistent API across different services, automatic result caching, error handling and retry logic, support for both REST and SOAP web services, and conversion of results to Python objects (dictionaries, lists, BioPython objects). Handles authentication, rate limiting, and API versioning. Use cases: automated data retrieval from multiple biological databases, building bioinformatics pipelines, database integration workflows, and programmatic access to biological web resources without manual web browsing
- **Cellxgene Census** - Python package for querying and analyzing large-scale single-cell RNA-seq data from the CZ CELLxGENE Discover census. Provides access to 50M+ cells across 1,000+ datasets with standardized annotations and metadata. Key features include: efficient data access using TileDB-SOMA format for scalable queries, integration with AnnData and Scanpy for downstream analysis, cell metadata filtering and querying, gene expression retrieval, and support for both human and mouse data. Enables subsetting datasets by cell type, tissue, disease, or other metadata before downloading, reducing data transfer and memory requirements. Supports local caching and batch operations. Use cases: large-scale single-cell analysis, cell-type discovery, cross-dataset comparisons, reference dataset construction, and exploratory analysis of public single-cell data
- **deepTools** - Comprehensive suite of Python tools for exploring and visualizing next-generation sequencing (NGS) data, particularly ChIP-seq, RNA-seq, and ATAC-seq experiments. Provides command-line tools and Python API for processing BAM and bigWig files. Key features include: quality control metrics (plotFingerprint, plotCorrelation), coverage track generation (bamCoverage for creating bigWig files), matrix generation for heatmaps (computeMatrix, plotHeatmap, plotProfile), comparative analysis (multiBigwigSummary, plotPCA), and efficient handling of large files. Supports normalization methods, binning options, and various visualization outputs. Designed for high-throughput analysis workflows and publication-quality figure generation. Use cases: ChIP-seq peak visualization, RNA-seq coverage analysis, ATAC-seq signal tracks, comparative genomics, and NGS data exploration
- **FlowIO** - Python library for reading and manipulating Flow Cytometry Standard (FCS) files, the standard format for flow cytometry data. Provides efficient parsing of FCS files (versions 2.0, 3.0, 3.1), access to event data (fluorescence intensities, scatter parameters), metadata extraction (keywords, parameters, acquisition settings), and conversion to pandas DataFrames or NumPy arrays. Features include: support for large FCS files, handling of multiple data segments, access to text segments and analysis segments, and integration with flow cytometry analysis workflows. Enables programmatic access to flow cytometry data for downstream analysis, visualization, and machine le

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Source: [Claudary](https://claudary.paisolsolutions.com/skills/scientific-skills) · https://claudary.paisolsolutions.com