Skill UI

Guides researchers through creating conference-ready posters in LaTeX, covering layouts, visuals, AI-generated graphics, and overflow-safe design for academic communication.

Offers MATLAB and GNU Octave guidance for matrix math, data import/export, visualizations, statistics, signal processing, differential equations, and general scripting—helpful when writing or translating MATLAB/Octave code and running scripts under either interpreter.

Medchem Filtering Toolkit is a Python library offering drug-likeness heuristics, structural alert and PAINS filters, group detection, catalogs, and complexity scoring to triage compound libraries and prioritize leads in drug discovery workflows.

Run OpenMM-powered molecular dynamics simulations and MDAnalysis trajectory workflows to build protein or small-molecule systems, minimize energy, equilibrate conditions, and characterize RMSD/RMSF, contacts, and free-energy surfaces for structural biology or drug studies.

End-to-end Neuropixels recording analysis covering SpikeGLX/OpenEphys/NWB loading, preprocessing, motion correction, Kilosort4 sorting, quality metrics, Allen/IBL curation, and AI-assisted visualization for extracellular electrophysiology.

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

A comprehensive toolkit for reconstructing and analyzing the evolutionary history of biological sequences (genes, proteins, genomes). The standard workflow includes multiple sequence alignment using MAFFT, robust maximum likelihood tree inference with IQ-TREE 2 and FastTree, and advanced visualization/manipulation using ETE3. This skill is essential for studies in viral phylodynamics, microbial genomics, protein family evolution, and molecular clock dating.

polars-bio accelerates genomic interval math and bioinformatics I/O by combining Polars, Arrow, and DataFusion to handle BED/VCF/BAM/GFF/FASTA streams, SQL queries, and cloud storage with overlap, coverage, and nearest APIs plus streaming fallbacks.

PyDESeq2 brings the DESeq2 differential expression workflow to Python, letting users load bulk RNA-seq counts, specify design formulas, fit DESeq2 models, run Wald tests with FDR correction, optionally apply apeGLM shrinkage, and export gene-level statistics within pandas/AnnData pipelines.

PyHealth is a modular Python toolkit designed for building deep learning pipelines using complex medical data, including EHR records, physiological signals, and medical imaging. It provides a standardized 5-stage workflow: Dataset → Task → Model → Trainer → Metrics. This allows users to train sophisticated models for clinical prediction (e.g., mortality, readmission, drug recommendation) while handling medical code mapping (ICD, ATC, RxNorm) and ensuring proper data splitting for rigorous research.

PyLabRobot is a vendor-agnostic, pure Python SDK designed for autonomous and automated laboratory workflows. It provides a unified interface to control a wide array of laboratory equipment, including liquid handling robots (Hamilton, Opentrons, Tecan), plate readers, pumps, shakers, and incubators. Ideal for developing complex, multi-device, reproducible protocols and simulating experiments before physical execution.

PyOpenMS provides comprehensive Python bindings for the OpenMS library, enabling advanced computational mass spectrometry analysis. It supports end-to-end workflows covering proteomics, metabolomics, and general spectral data processing. Key features include handling diverse file types (mzML, mzXML), signal processing, feature detection, and peptide/protein identification using established search engines.