Skill UI

This skill analyzes and aggregates public sentiment and discussions surrounding any topic over the last 30 days. It pulls engagement and content from a massive array of sources, including Reddit, X, YouTube, TikTok, Hacker News, GitHub, and the general web, providing a comprehensive, multi-platform view of current trends and public reactions.

Access the BRENDA SOAP API to retrieve enzyme kinetic parameters, reaction equations, organism-specific data, and environmental preferences, enabling biochemical research, metabolic pathway reconstruction, and enzyme engineering workflows.

RDKit delivers a Python-based cheminformatics toolkit for parsing SMILES/SDF, computing descriptors, generating 2D/3D coordinates, fingerprinting, searching substructures, managing reactions, and visualizing molecules, ideal for drug discovery and computational chemistry workflows.

Query the Reactome Content and Analysis Services (or the reactome2py client) to fetch pathway hierarchies, map genes, run overrepresentation/expression analyses, and explore disease interactions for systems biology research.

COBRApy is a comprehensive Python library for Constraint-Based Reconstruction and Analysis (COBRA) of metabolic models. It enables users to simulate complex cellular metabolism, performing crucial analyses such as Flux Balance Analysis (FBA), Flux Variability Analysis (FVA), and virtual gene/reaction knockouts. It is an essential tool for systems biology research and metabolic engineering design.

This comprehensive guide details the process of implementing a secure and robust system for handling Palantir Foundry webhook events. It covers key steps including API-based webhook registration, mandatory signature verification with replay protection, sophisticated event routing for various object lifecycles (create, update, delete), and ensuring idempotent processing using caching mechanisms like Redis. Use this when external microservices must react reliably and immediately to changes within the Foundry Ontology or data assets.

This skill performs advanced pathway and gene-set enrichment analysis crucial for interpreting gene lists (e.g., DE genes, screen hits). It distinguishes between Over-Representation Analysis (ORA) for thresholded lists and Gene Set Enrichment Analysis (GSEA) for full ranked lists. Supports scoring pathway activity (ssGSEA/GSVA) and utilizes major databases like GO, KEGG, Reactome, and MSigDB for comprehensive biological interpretation, ensuring publication-ready results.

This skill guides authors on how to proactively strengthen their academic manuscripts before submission, especially for highly demanding journals. It involves identifying the most likely expert reviewers, predicting their specific methodological, theoretical, or empirical objections, and strategically integrating countermeasures, robustness checks, and alternative explanations directly into the main text. It transforms the submission process from a defensive reaction to a proactive, structured argument.