3. Data, Science & AI

Enables efficient storage and processing of large scientific datasets using chunked arrays with cloud storage integration and compatibility with NumPy, Dask, and Xarray.

Queries Ensembl REST API for genomic data including gene lookups, sequences, variants, and VEP predictions for research.

Automates LLM-powered hypothesis generation and testing on tabular datasets, combining literature insights with empirical pattern analysis.

Toolkit for reading/writing genomic file formats (SAM/BAM, VCF, FASTA/FASTQ) and performing NGS data processing tasks like region extraction and coverage calculation.

A toolkit for deep generative models in single-cell omics, enabling probabilistic batch correction, transfer learning, and multi-modal integration.

Provides a Python toolkit for survival analysis, including Cox models, Random Survival Forests, and time-to-event modeling for censored data.

Manages MongoDB and PostgreSQL databases, including schema design, query optimization, indexing, migrations, and administration.

Direct REST API access to KEGG database for academic bioinformatics research, enabling pathway analysis and gene mapping.

Python library for geospatial vector data analysis, enabling spatial operations, coordinate transformations, and mapping for geographic data.

Provides molecular featurization tools for ML, including ECFP, MACCS, and ChemBERTa, converting SMILES to features for QSAR and molecular ML applications.

A toolkit for biological sequence analysis, phylogenetics, and microbiome diversity metrics including UniFrac and PERMANOVA.

Provides programmatic access to the CELLxGENE Census, a large-scale single-cell gene expression atlas for querying across tissues, diseases, and cell types.

Guides academic researchers in selecting statistical tests, checking assumptions, and generating APA-formatted results for research reporting.

Enables efficient processing and analysis of massive tabular datasets (billions of rows) using out-of-core operations, lazy evaluation, and fast aggregations without memory constraints.

Provides access to ZINC database for drug discovery, enabling compound searches by ID, SMILES, and similarity with 3D structures for virtual screening.

Lightweight tool for extracting and preprocessing whole slide images (WSI) in histopathology, featuring stain normalization for H&E images.

Automates exploratory data analysis for scientific data files, detecting formats and generating markdown reports with quality metrics and recommendations.

Queries NCBI ClinVar for variant clinical significance, supporting genomic medicine research through gene/position searches and VCF annotation.

Provides a comprehensive Python toolkit for creating, analyzing, and visualizing complex networks and graphs, including algorithms for pathfinding, centrality, and community detection.

Queries openFDA API for drug, device, adverse event, and recall data to enable regulatory analysis and safety research.

Efficiently searches bioRxiv preprint database for life sciences literature, retrieving metadata and PDFs via keyword, author, date, or category filters.

Python library for statistical modeling with OLS, GLM, ARIMA, and detailed diagnostics for econometrics and time series analysis.

Provides PyTorch-native graph neural network tools for molecular and protein modeling, enabling custom GNN architecture development in drug discovery and protein property prediction.

Python framework for discrete-event simulation, enabling modeling of processes, queues, and resource interactions over time.