3. Data, Science & AI

Provides tools for building Graph Neural Networks (GNNs) including GCN, GAT, and GraphSAGE for node classification, link prediction, and molecular property analysis.

Accesses COSMIC database to query cancer mutations, gene fusions, and genomic data for precision oncology research and analysis.

Provides real-time AI-powered web search using Perplexity models via LiteLLM and OpenRouter, delivering grounded answers with source citations for current information and scientific literature.

Automates LLM-driven hypothesis generation and testing on tabular data, combining literature insights with empirical analysis for pattern exploration.

Comprehensive Python toolkit for survival analysis, including Cox models, Random Survival Forests, and time-to-event prediction evaluation.

Python library for reading, writing, and processing genomic file formats including SAM/BAM, VCF, and FASTA/FASTQ in next-generation sequencing workflows.

Provides access to ClinPGx pharmacogenomics database for querying gene-drug interactions, CPIC guidelines, and allele functions to support precision medicine and genotype-guided dosing.

Extracts events, metadata, and channels from FCS flow cytometry files (v2.0-3.1) into NumPy arrays and DataFrames for scientific data preprocessing.

Provides a comprehensive Python library for astronomical data analysis, including FITS file handling, coordinate transformations, and cosmological calculations.

Provides programmatic access to Data Commons for querying global statistical datasets including demographics, economics, health, and environmental data.

Multi-objective optimization framework with NSGA-II, NSGA-III, and Pareto front handling for engineering design and scientific problem-solving.

Integrates with DNAnexus for genomics data management, pipeline execution, and dxpy SDK-based workflow automation.

Provides molecular featurization for machine learning, including 100+ featurizers, SMILES to features conversion, and support for QSAR and molecular ML applications.

Performs symbolic mathematics in Python, including algebra, calculus, and equation solving for exact results.

Performs constraint-based metabolic modeling including flux balance analysis, gene knockouts, and flux sampling for systems biology research and metabolic engineering applications.

Toolkit for protein language models (ESM3, ESM C) enabling sequence, structure, and function prediction, protein design, and engineering via local/cloud inference.

Cloud platform automating protein testing, validation, and AI-driven sequence optimization using computational tools like ESM.

Queries Open Targets Platform for target-disease associations, drug target data, and omics evidence to support therapeutic target identification in biomedical research.

Accesses European Nucleotide Archive (ENA) via API/FTP to retrieve DNA/RNA sequences, FASTQ files, and genome assemblies for bioinformatics workflows.

Standard pipeline for single-cell RNA-seq analysis including QC, normalization, dimensionality reduction, clustering, and visualization.

DeepTools provides genomic data analysis for NGS workflows, including BAM to bigWig conversion, QC metrics, and visualization for ChIP-seq, RNA-seq, and ATAC-seq.

Provides molecular machine learning tools with diverse featurizers and pre-built datasets for property prediction using traditional ML or GNNs.

Statistical visualization library for exploratory data analysis, built on Matplotlib and integrated with pandas for distributions and relationships.

Cloud-based platform for quantum chemistry computations, offering molecular property prediction, protein-ligand docking, and AI-driven molecular simulations via Python API.