3. Data, Science & AI

Query ChEMBL database for bioactive molecules, retrieve bioactivity data (IC50, Ki), and perform structure-activity relationship studies in medicinal chemistry.

Provides type-safe structured output generation for AI models using Pydantic, ensuring valid JSON/XML/code with local model support and optimized speed.

Comprehensive single-cell RNA-seq analysis pipeline including data loading, QC, dimensionality reduction, clustering, and cell type annotation using Scanpy.

Statistical modeling toolkit providing OLS, GLM, logistic regression, ARIMA, and hypothesis tests for data analysis and econometric research.

DeepChem enables molecular property prediction, GNN-based drug discovery modeling, and benchmarking via MoleculeNet for pharmaceutical applications.

Conducts differential gene expression analysis on RNA-seq data with DESeq2, including statistical testing and visualization.

Provides tools for creating, editing, and analyzing spreadsheet data with formulas, formatting, and visualization for .xlsx and .csv files.

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.