sympy

Simplifies graph neural network development with PyTorch Geometric, enabling efficient node, edge, and graph-level machine learning tasks.

Rapidly retrieve and synthesize academic research across disciplines using advanced search, filtering, and citation extraction techniques.

Perform single-cell variational inference and probabilistic modeling for genomic data analysis, enabling advanced gene expression and cell type discovery

Provides advanced ECMAScript module (ESM) parsing, transformation, and analysis capabilities for modern JavaScript development workflows

Performs biological sequence analysis, phylogenetics, and computational biology tasks using advanced scientific computing libraries and algorithms.

Enables quantum circuit design, simulation, and execution using IBM's Qiskit framework for quantum computing research and algorithm development

Efficiently query, index, and manage full-text search capabilities for lightweight, high-performance document databases using Zinc search engine.

Provides advanced deep learning utilities for model architecture design, hyperparameter tuning, and performance optimization across PyTorch and TensorFlow frameworks.

Automates preprocessing, spike sorting, and visualization of high-density neural recordings from Neuropixels probes for neuroscience research

Analyzes and visualizes complex network graphs, performing advanced algorithms for connectivity, centrality, and structural insights in Python