3. Data, Science & AI

Provides Python-based access to microscopy data management, enabling image retrieval, pixel analysis, ROI annotation, and batch processing for high-content screening workflows.

Applies medicinal chemistry rules including Lipinski, Veber, and PAINS filters to prioritize compounds and filter chemical libraries.

Automates scientific hypothesis generation and testing by combining LLMs with empirical data and literature for research discovery.

Comprehensive toolkit for building, testing, and deploying machine learning models using clinical data, healthcare datasets, and medical coding systems.

Enables zero-shot image classification, image-text matching, and cross-modal retrieval using a vision-language model trained on 400M image-text pairs.

Infers gene regulatory networks from transcriptomics data using scalable ML algorithms (GRNBoost2, GENIE3) for transcription factor-target gene analysis.

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

Cloud platform automating protein testing and validation, including binding assays, expression testing, and AI-driven sequence optimization using ESM.

Provides advanced data science capabilities including statistical modeling, A/B testing, and predictive analytics using Python, R, and SQL for data-driven decision making.

Queries STRING API for protein-protein interactions, enabling network analysis and functional enrichment (GO/KEGG) across 5000+ species for systems biology research.

Framework for building LLM-powered applications with agents, chains, RAG, and multi-provider support for chatbots and question-answering systems.

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

Generates journal-ready scientific figures with multi-panel layouts, error bars, and colorblind-safe designs using matplotlib, seaborn, and plotly.

Enables parallel and distributed computing to scale pandas and NumPy operations on datasets exceeding memory capacity.

Query ClinVar database for variant clinical significance, supporting gene/position searches and VCF annotation in genomic medicine.

Enables tracing, evaluation, and monitoring of LLM applications for debugging, model testing, and production system oversight.

Analyzes Excel spreadsheets, creates pivot tables, and generates charts for data visualization and tabular data analysis.

Provides scikit-learn compatible APIs for time series machine learning tasks including forecasting, anomaly detection, and clustering on temporal data.

Serverless GPU platform for deploying ML models as APIs and running scalable batch jobs without infrastructure management.

Primary Python toolkit for molecular biology data processing, including sequence manipulation, file parsing, and BLAST workflows.

Trains Mixture of Experts (MoE) models efficiently using DeepSpeed or HuggingFace, reducing compute costs while enabling sparse architectures for large-scale AI systems.

High-performance Rust toolkit with Python bindings for genomic interval analysis, BED file processing, and ML tokenization in computational genomics.

Framework for building AI systems with declarative programming, automatic prompt optimization, and modular RAG systems using DSPy.

Provides a vision-language pre-training framework for image captioning, visual question answering, and multimodal chat with zero-shot capabilities.