Working with computational pathology requires specialized tools for whole-slide image analysis. This skill provides comprehensive reference documentation for PathML, enabling you to load gigapixel pathology images, preprocess H&E stains, train machine learning models, and analyze spatial proteomics data.

Transform academic papers into professional promotional materials for conferences and online sharing. This skill automates the creation of interactive websites, presentation videos, and conference posters from LaTeX or PDF sources.

Find therapeutic targets and drug candidates using integrated genetic, omics, and clinical data. Query gene-disease associations with evidence scores to accelerate drug discovery.

Research requires finding relevant academic papers and analyzing publication trends. This skill provides direct access to the OpenAlex database containing 240M+ scholarly works, enabling literature searches, citation analysis, and research output evaluation without manual database navigation.

Scientists and researchers need efficient ways to manage large microscopy image datasets. This skill provides complete reference documentation for the OMERO Python API, enabling automated image retrieval, pixel analysis, ROI management, and batch processing for high-content screening workflows.

Researching information scattered across multiple Notion pages takes time and risks missing key details. This skill provides a structured workflow to search, fetch, and synthesize Notion content into organized briefs, summaries, comparisons, or comprehensive reports with proper citations.

Analyzing Neuropixels recordings requires expertise with multiple tools and complex pipelines. This skill provides a complete workflow from raw data to curated units with preprocessing, spike sorting, quality metrics, and AI-assisted curation following best practices from SpikeInterface, Allen Institute, and IBL.

Search thousands of metabolomics studies and metabolite data from the NIH database. Access standardized nomenclature, mass spectrometry data, and study metadata for biomarker discovery and metabolic research.

Screening large compound libraries for drug candidates is time-consuming. This skill applies established medicinal chemistry rules like Lipinski Rule of Five, PAINS filters, and structural alerts to automatically identify promising compounds for further study.

Writing comprehensive market research reports is time-consuming and requires expertise in frameworks, formatting, and visual design. This skill streamlines the entire process by providing structured templates, automated visual generation, and professional LaTeX formatting that matches top consulting firm deliverables.

Researchers spend hours searching multiple databases and verifying citations manually. This skill streamlines literature reviews by searching academic databases, deduplicating results, verifying citations against CrossRef, and generating professional PDFs with proper formatting.

Biological datasets are hard to track, query, and reproduce. LaminDB provides a unified framework for managing scientific data with built-in ontology validation, workflow lineage tracking, and FAIR compliance for research reproducibility.

LabArchives integration enables programmatic access to electronic lab notebooks. Automate data backup, entry creation, and file attachments. Connect scientific tools like Jupyter, Prism, and REDCap for streamlined research documentation.

Researchers need efficient access to KEGG bioinformatics databases for pathway analysis. This skill provides Python helper functions to query pathways, genes, compounds, and drugs via the official KEGG REST API.

Researchers struggle to develop rigorous testable hypotheses grounded in evidence. This skill provides a systematic 8-step workflow to formulate mechanistic hypotheses, design discriminating experiments, and create professional LaTeX reports.

Manual hypothesis generation is slow and limited by human creativity. Hypogenic automates systematic hypothesis generation and testing using LLMs, combining data-driven patterns with literature insights for accelerated scientific discovery.

Researchers need quick access to metabolite information for metabolomics studies. This skill provides guidance for searching the Human Metabolome Database to find chemical properties, biomarkers, and spectral data for metabolite identification and research.

Digital pathology workflows require processing gigapixel whole slide images for computational analysis. This skill provides comprehensive guidance for extracting tiles, detecting tissue regions, and preparing datasets for deep learning pipelines in histopathology research.

Finding genetic associations for diseases requires navigating complex genomic databases. This skill provides clear guidance for querying the NHGRI-EBI GWAS Catalog to retrieve SNP-trait associations, p-values, and summary statistics for research.

Genomic interval analysis requires specialized tools for processing BED files, detecting overlaps, and generating coverage tracks. Gtars provides high-performance Rust implementations with Python bindings for computational genomics and machine learning workflows.