Skill UI

This tool provides access to the Cancer Dependency Map (DepMap) data, derived from genome-wide CRISPR screens, RNAi, and compound sensitivity assays. It allows users to query gene dependency scores, identify cancer-specific vulnerabilities, predict synthetic lethal interactions, and validate potential oncology drug targets across various cancer cell lines.

The ETE Toolkit is a powerful Python library designed for analyzing, manipulating, comparing, and visualizing phylogenetic trees stored in Newick or Nexus formats. It allows users to perform topology edits, calculate phylogenetic distances (e.g., Robinson-Foulds), detect evolutionary events, and query external taxonomic databases like NCBI/GTDB. Note that this tool analyzes existing trees; it is not used for inferring trees from raw sequences.

FlowIO is a specialized, low-level library designed for reading, inspecting, and writing Flow Cytometry Standard (FCS) files (versions 2.0, 3.0, and 3.1). It allows users to extract event data as NumPy arrays, inspect detailed metadata (HEADER, TEXT, ANALYSIS), and handle multi-dataset structures. It is crucial for data preparation, format conversion, and foundational metadata management in bioinformatics pipelines, but does not perform complex analysis like gating or compensation.

A powerful skill covering geospatial science, including GIS, remote sensing, spatial statistics, and machine learning for Earth observation. It supports processing of various data types (raster, vector, point cloud) from sources like Sentinel and Landsat, and integrates modern cloud-native workflows (STAC, COG). Ideal for environmental monitoring, urban planning, and advanced spatial modeling tasks.

gget is a comprehensive command-line and Python package providing unified access to over 20 major bioinformatics databases. Users can perform deep analyses across genomics, proteomics, and disease associations. Key functions include gene information lookups, sequence alignment (BLAST), structural prediction (AlphaFold), single-cell analysis, and enrichment studies, supporting both interactive queries and automated pipelines.

This skill provides comprehensive tools for analyzing and engineering protein glycosylation patterns. It scans sequences for canonical N-glycosylation sequons (N-X-S/T), predicts O-glycosylation hotspots, and supports rational modification. It is essential for optimizing therapeutic antibodies, improving protein stability, or designing complex vaccine antigens.

Histolab is a specialized Python library for digital pathology designed to process Whole Slide Images (WSI). It automates critical steps including sophisticated tissue detection, customizable tile extraction (random, grid, score-based), and stain normalization. It is essential for preparing high-quality, structured datasets for deep learning model training and comprehensive quantitative whole slide analysis.

A comprehensive framework for transforming raw observations into rigorous, evidence-bounded, and testable research plans. It guides users through establishing research questions (PICO/PECO), formulating candidate hypotheses and rival explanations, defining causal estimands, and creating preregistration-ready analysis plans, all while maintaining strict ethical and scientific guardrails.

This skill guides the creation of highly auditable, evidence-traceable market research reports. It provides a structured workflow for defining market scope, mapping every claim to primary sources (like official filings and statistics), and conducting rigorous, assumption-driven market sizing (TAM/SAM/SOM) and forecasting scenarios. Essential for professional market analysis and strategic planning.

MarkItDown is a lightweight utility designed to convert heterogeneous documents (PDF, Office files, HTML, etc.) into structured, plain Markdown. It is specifically optimized for text analysis, search indexing, and preparing data for Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) systems, prioritizing content structure over visual fidelity. Supports local, stream, and advanced multimodal extraction scenarios.

A comprehensive toolkit for running and analyzing molecular dynamics (MD) simulations. This skill covers the entire workflow: system setup, force field definition, energy minimization, and equilibration using industry-standard tools like OpenMM and MDAnalysis. Essential for structural biology, drug binding studies, and biophysics research.

A comprehensive research toolkit for building and auditing reproducible workflows for physiological time-series data. It specializes in preprocessing, event/interval analysis, multimodal alignment, and extracting variability and complexity features from signals like ECG and EDA. Designed strictly for academic and research use, emphasizing rigorous data contracts and method-aware validation, while strictly disclaiming any diagnostic or medical device validation role.