3. Data, Science & AI

Extracts flow cytometry data from FCS files, converting events and metadata into NumPy arrays and DataFrames for scientific analysis.

Provides a unified Python interface for cross-database bioinformatics analysis, enabling ID mapping and consistent API access across 40+ biological databases.

Provides survival analysis tools for time-to-event data, including Cox models, Random Survival Forests, and evaluation metrics using scikit-survival.

Programmatically queries the CELLxGENE Census, a comprehensive single-cell gene expression atlas with 61M+ cells across tissues, diseases, and cell types for research analysis.

Framework for designing, simulating, and executing quantum circuits on Google Quantum AI hardware with noise-aware modeling and characterization capabilities.

Cloud platform automating protein testing, validation, and sequence optimization using AI tools like ESM and bioinformatics workflows.

Creates multi-agent orchestration workflows for automating complex, multi-phase tasks using AI agent coordination in enterprise environments.

Framework for Python-based computational fluid dynamics simulations, supporting Navier-Stokes, turbulence analysis, and HPC-optimized FFT methods.

Provides optimization strategies for processing large datasets exceeding memory limits using Dask in Python.

Python toolkit for reading, writing, and processing genomic file formats (SAM/BAM, VCF, FASTA/FASTQ) in next-generation sequencing pipelines.

Python library for reading, writing, and processing DICOM medical imaging files, including metadata handling and conversion for healthcare applications.

Predicts protein-ligand binding poses using diffusion models for structure-based drug design, supporting virtual screening with confidence scores.

Toolkit for web crawling and scraping to fetch and extract structured data from HTML content, including text, links, and elements.

Detects and reports system resources (CPU, GPU, memory, disk) to guide computational strategy for scientific tasks, including recommendations for parallel processing and GPU acceleration.

Lightweight tool for WSI tile extraction, tissue detection, and stain normalization of H&E histopathology images, optimized for dataset preparation and simple analysis pipelines.

Reduces LLM input token usage while preserving decision-critical information through advanced context compression techniques.

Provides programmatic access to global statistical datasets including demographics, economics, health, and environment for querying and relationship exploration.

Bioinformatics toolkit for processing and visualizing NGS data (ChIP-seq, RNA-seq, ATAC-seq) including QC and heatmap generation.

Comprehensive toolkit for developing and deploying machine learning models using clinical data, EHR, and healthcare datasets like MIMIC-III.

Provides molecular featurization for ML, including ECFP, MACCS, descriptors, and ChemBERTa, to convert SMILES into features for QSAR and molecular ML.

Performs time series machine learning tasks including forecasting, anomaly detection, and clustering with scikit-learn compatible APIs.

Specializes in database schema design, query optimization, indexing, and migration planning for relational and NoSQL databases.

Comprehensive platform for proteomics mass spectrometry analysis, including feature detection, peptide identification, and protein quantification.

Guides statistical test selection, assumption checking, and APA-formatted reporting for academic research.