3. Data, Science & AI

Retrieves DNA/RNA sequences, FASTQ files, and genome assemblies from the European Nucleotide Archive for bioinformatics pipelines.

Provides a hardware-agnostic framework for quantum machine learning, enabling gradient-based training of quantum circuits and hybrid quantum-classical models across multiple quantum hardware providers.

Toolkit for creating, editing, and analyzing spreadsheet data with formulas, formatting, and visualization capabilities.

Enables constraint-based metabolic modeling for systems biology, including flux balance analysis and gene knockout simulations using SBML models.

Comprehensive toolkit for scientific research with access to databases, analysis tools, and domain-specific workflows in biology, chemistry, medicine, and computational fields.

Provides a standard pipeline for single-cell RNA-seq analysis including QC, normalization, dimensionality reduction, clustering, and visualization.

Enables programmatic querying of NIH Metabolomics Workbench database for metabolite data, MS/NMR spectra, and study metadata to accelerate biomarker discovery and metabolomics research.

Enables automated lab data management by integrating with Benchling R&D platform to access DNA, proteins, inventory, and ELN entries via API and Data Warehouse.

Automates scientific research workflows including data analysis, methodology development, computational experiments, literature searches, and LaTeX paper generation via customizable multiagent orchestration.

Provides UMAP-based dimensionality reduction for visualizing high-dimensional data in 2D/3D, supporting clustering and ML preprocessing.

Provides programmatic access to COSMIC database for querying cancer mutations, gene fusions, and mutational signatures in precision oncology research.

Simplifies PyTorch code organization and provides tools for distributed training, logging, and scalable neural network development.

Low-level Python library for creating customizable, publication-quality static visualizations in scientific and technical contexts.

Generates evidence-based clinical decision support documents with statistical analysis, biomarker stratification, and regulatory compliance for pharmaceutical research.

Performs symbolic mathematics in Python, including algebra, calculus, and physics calculations, providing exact variable-based solutions.

Framework for developing and running quantum algorithms on IBM Quantum hardware, including error mitigation and production workloads.

Comprehensive toolkit for processing and analyzing physiological signals including ECG, EEG, and EDA for research and clinical applications.

Efficiently searches bioRxiv preprints for life sciences literature, retrieving metadata and PDFs for scientific research and literature reviews.

Provides machine learning capabilities in Python using scikit-learn for supervised learning, model evaluation, and pipeline construction.

Provides comprehensive tools for astronomical data analysis including FITS file handling, coordinate transformations, and cosmological calculations.

Creates on-demand specialized AI agents for unmatched tasks, enabling persistent and self-evolving agent generation.

Provides programmatic access to Ensembl's REST API for genomic data retrieval, including gene sequences, variants, and orthologs across 250+ species.

Enables programmatic access to PubMed database via REST API, supporting Boolean/MeSH queries, batch processing, and citation management for biomedical data retrieval.

Simulates open quantum systems using master equations, Lindblad dynamics, and quantum optics for research and educational purposes.