Skill UI

Statsmodels is a Python library for detailed regression and time-series models, giving econometrics-grade inference, diagnostics, residual analysis, model comparison, and forecasting tools when you need publication-ready tables and rigorous testing.

UMAP-Learn delivers fast nonlinear dimensionality reduction for visualization, clustering prep, and feature engineering; it mirrors scikit-learn APIs and supports supervised/semi-supervised embeddings with tunable parameters.

Direct REST API access to UniProt for searching proteins, fetching FASTA sequences, mapping identifiers, selecting annotations, and streaming large datasets within Python workflows.

Vaex processes massive tabular datasets (billions of rows) with lazy, out-of-core DataFrames, fast aggregations, visualization, and ML pipelines without fitting data into memory, ideal for CSV/Arrow/Parquet workflows.

GeoMaster delivers a comprehensive geospatial science skill set for remote sensing, GIS, spatial analysis, and ML workflows using satellite imagery, point clouds, and cloud-native catalogs across 8 languages with 500+ code examples for Earth observation applications.

Build and analyze phylogenetic trees with MAFFT, IQ-TREE 2, FastTree, and visualize via ETE3 or FigTree, covering alignment, trimming, ML inference, and microbial/viral evolutionary studies.

Polars Bio delivers high-performance genomic interval arithmetic and bioinformatics I/O for BED/VCF/BAM/GFF datasets, streaming/cloud ready, with SQL interface and Polars-friendly APIs for overlap/nearest, merge, coverage, complement, subtract workflows.