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Infers candidate gene regulatory networks from bulk or single-cell expression data using GRNBoost2 and GENIE3 algorithms. Ranks transcription factor-target associations with Dask-compatible parallel execution, sparse expression support, and network stability validation for biological research applications.

Programmatically query the CZ CELLxGENE Census for versioned single-cell and spatial transcriptomics data, including population-scale cell metadata, gene expression slices, summary counts, source H5AD URIs, embeddings, and reference atlas comparisons.

LaminDB is an open-source lineage-native lakehouse designed for biological datasets and models. It enables queryable, traceable, and validated data management across various storage formats like S3 and Postgres. Users can track computational workflows, curate data with ontologies via Bionty, and ensure FAIR compliance. Ideal for managing scRNA-seq, spatial transcriptomics, and integrating ML pipelines while maintaining reproducibility and collaboration.

scvi-tools is a comprehensive Python framework for probabilistic deep generative models in single-cell genomics. Built on PyTorch and PyTorch Lightning, it enables batch correction, transfer learning, differential expression analysis with uncertainty, and multi-modal data integration. Best for advanced modeling of single-cell RNA-seq, ATAC-seq, CITE-seq, spatial transcriptomics, and specialized modalities like methylation and cytometry.

This guide provides comprehensive instructions for setting up the AssemblyAI SDK in both Node.js and Python environments. It covers package installation, secure API key management using environment variables, and client initialization for utilizing transcription and streaming services.

A comprehensive setup guide for establishing a fast, reproducible local development environment for AssemblyAI projects. It incorporates hot reloading, local caching of transcription results, and mocked testing utilities to ensure rapid iteration cycles without relying on live API keys or incurring costs. Ideal for setting up new services or enhancing existing AI workflows.

This skill provides a comprehensive guide and implementation for deploying a containerized Fathom AI meeting service. It is designed to handle the processing of meeting transcripts, summaries, and action items via webhooks. The solution includes Docker setup, environment variable management, robust health checks, and detailed steps for implementing rolling updates, ensuring continuous and reliable meeting data synchronization.

A foundational guide to interacting with the Fathom API. This skill demonstrates essential use cases, including listing meetings, fetching detailed transcripts, and retrieving AI-generated summaries and action items. It is ideal for initial API testing, validating connectivity, or understanding the Fathom data response structure.

A comprehensive guide for setting up and authenticating access to the Fathom AI API. This skill walks users through generating API keys, configuring environment variables, and testing connectivity to retrieve meeting transcripts, summaries, and action items. Essential for integrating Fathom's meeting intelligence features into custom applications.

This setup provides a local development loop for integrating and testing Fathom API functionalities. It utilizes mock meeting and transcript data, making it ideal for building meeting analytics tools, simulating webhook handlers, or iterating on complex transcript processing pipelines without requiring live API calls. It ensures a robust environment for isolated development testing.

This module provides robust handling for Fathom API rate limits (60 requests/minute per user). It implements advanced retry strategies (handling 429 errors and server failures) and efficient batch processing to reliably sync large volumes of meeting intelligence, such as transcripts and action items, into external systems like CRMs or project trackers.

Provides production-ready client patterns for interacting with the Fathom API, implemented in both Python and TypeScript. This SDK wrapper is designed for building reusable client services, implementing robust meeting data pipelines, or integrating Fathom's core features (like transcripts and summaries) into specialized applications.