microalgae

Code and resources for LMFM-12 microalgae image classification, comparing seven CNN architectures and evaluating transfer learning performance

Microalgal growth simulation for CO₂ capture estimation. Monod kinetics, Steele photoinhibition, and CTMI temperature modeling for Chlorella vulgaris under Surat, India's tropical climate.

Computational biology research prototype for microalgal culture vulnerability assessment using transcriptomics, statistical analysis, ML, biological networks, and economic decision support. No biologically validated pathogen-risk model yet.

IoT-based portable photobioreactor monitoring system for distributed urban microalgae cultivation — Bangkit Academy capstone project integrating OD sensor data, growth tracking, and carbon capture estimation

Motor de IA preditiva para estimativa de crescimento de biomassa em tanques de cultivo de microalgas. Recebe dados de sensores IoT (pH, temperatura, turbidez, luminosidade e radiação PAR) e retorna previsão de biomassa em g/L, data estimada de colheita e confiança do modelo via API REST. Desenvolvido com Python 3.11, FastAPI e Random Forest (scikit

Research code for LA4SR protein-language modeling in microalgae (Patterns, 2025).

This pipeline could help microalgae scientists to calibrate the OD 680 curve to evaluate algae growth and its association with a potential axenic method using a penicillin-streptomycin hybrid antibiotic.

Open-source techno-economic analysis (TEA) and life-cycle assessment (LCA) for microalgae, cyanobacteria and aquatic protist biomass. Desktop app on a UI-agnostic engine; TEA and LCA derived from one shared mass and energy balance.

AI-powered platform for smart photobioreactor monitoring using IoT, multi-sensor data, computer vision, and real-time analytics. Built with FastAPI, Angular, PostgreSQL, MQTT, Docker, and Raspberry Pi.