Results for “wit-ai”

Runs MySQL queries from an AI coding agent using the mysql2 Node.js library, with setup instructions for npm and TypeScript.

Perform astronomical data analysis with Astropy: coordinate transformations, unit conversions, FITS I/O, cosmological calculations, time handling, table operations, and WCS transformations.

Infer gene regulatory networks from gene expression data using scalable algorithms (GRNBoost2, GENIE3) with support for distributed computation.

Simplify molecular cheminformatics with a Pythonic wrapper around RDKit for SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing.

Build search applications with full-text, vector, semantic, and hybrid search using the Azure AI Search SDK for .NET.

Provides persistent, self-hosted semantic memory for AI agents via MCP, storing worklogs, decisions, and notes in PostgreSQL with pgvector for meaning-based retrieval across sessions.

Manages Neon serverless Postgres databases via the neonctl CLI and Neon API, covering projects, branches, databases, roles, endpoints, and compute scaling with a discovery-first workflow.

Query, analyze, and tune PostgreSQL databases through your AI agent with safe access controls, including index tuning recommendations, query plan analysis, health monitoring, and schema intelligence.

Perform constraint-based metabolic modeling with COBRApy: run FBA, FVA, gene knockouts, flux sampling, and manage SBML models for systems biology and metabolic engineering.

Manages Xata serverless databases via the xata CLI and REST API, covering discovery of workspaces, databases, branches, tables, schema, migrations, and record counts with read-only operations.

Build and train graph neural networks with PyTorch Geometric, covering node/link/graph classification, message passing layers, heterogeneous graphs, and custom datasets.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.

Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data, enabling efficient access to cell metadata, gene expression slices, summary counts, and embeddings without downloading whole datasets.

Perform high-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames, including overlap, nearest, merge, coverage, complement, subtract, and reading/writing BED, VCF, BAM, GFF, FASTA, and FASTQ formats with streaming and cloud-native support.

Generate professional clinical decision support documents for pharmaceutical and clinical research, including biomarker-stratified cohort analyses and evidence-based treatment recommendation reports with GRADE grading, statistical analysis, and publication-ready LaTeX/PDF output.

Analyze proteomics and metabolomics mass spectrometry data with PyOpenMS: read/write MS file formats, process spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines using ready-to-run scripts.