A deep research study introducing the Gene Drift Hypothesis: a framework explaining how tokenomics mutate across market cycles. Analyzes evolutionary forces, selective pressures, behavioral traits, and economic genes that rise, fall, or mutate through bull/bear phases, shaping token species over time.

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.

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.

This codebase contains SQL queries for analyzing blockchain network metrics across different chains using Dune Analytics, focusing on transaction patterns, wallet behaviors, smart contract usage, and network activity trends.

EpicChain-Trace-Visualizer is a powerful tool designed for the EpicChain Private Net that enhances the debugging and analysis of smart contracts.