A research-grade framework for forecasting tokenomic gene evolution across market cycles. Analyzes historical gene frequencies, models behavioral drift, and predicts future gene expression using interpretable trend and moving-average forecasting. Designed for tokenomics research, risk analysis, and evolutionary cryptoeconomics.

A cross-chain intelligence toolkit that maps suspicious smart-contract deployers across Ethereum, BSC, Arbitrum, and Base. Fetches deployer histories using Scan V2 APIs, builds a structured NetworkX graph, extracts ML-ready behavioral features, and assigns heuristic risk scores to identify scam clusters and malicious deployment patterns.

🔍 Analyze and forecast tokenomic gene frequencies across market cycles with this research-focused tool for effective market dynamics understanding.