Building GeroQubit for AI-powered drug discovery and Aeon Core for advanced materials technology.

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Dinesh K • Peerlist

GeroQubit is an AI-powered drug discovery platform focused on geroscience and age-related diseases. Unlike conventional molecular generation systems, GeroQubit uses a reaction-first design approach to generate synthesizable small-molecule candidates while integrating target biology, tissue specificity, ADMET prediction, and multi-objective optimization into a unified workflow. The platform helps researchers explore novel compounds with greater emphasis on practical synthesis and biological relevance. Designed for biotechnology companies, pharmaceutical R&amp;D teams, and academic researchers, GeroQubit combines computational chemistry, artificial intelligence, and longevity science to accelerate early-stage therapeutic discovery. GeroQubit is developed by Voxelta Private Limited.

Geroqubit

CRISPR Guide RNA Designer I developed an open-source, interactive web app to help researchers design and analyze CRISPR guide RNAs (gRNAs) with confidence and ease. Built with Python and Streamlit, it combines biology and AI insights to accelerate genome editing research. ✨ Key Features: 🧬 Identify candidate gRNAs based on customizable PAM sequences, guide lengths, and GC content 🔍 Predict off-target effects using mismatch tolerance against background DNA sequences 🧪 Simulate DNA edits and predict impacts on protein translation in silico 🤖 Generate AI-powered detailed reports with Gemini and OpenAI integrations 📊 Interactive visualization and ranking to simplify guide selection 🛠️ Fully open source and accessible to molecular biologists and bioinformaticians 🚀 This tool empowers scientists to design more reliable CRISPR experiments faster, fostering collaboration and innovation in gene editing.

CRISPR Guide RNA Designer

CRISPR Precision Studio is an open-source CRISPR guide design platform that discovers, ranks, explains, and validates guide RNAs in one lightweight application. It combines interpretable on-target scoring, both-strand off-target analysis, calibrated uncertainty, base-editing and prime-editing design, genome-wide search, multiplex library design, and per-feature explanations through a FastAPI-based local platform. Built to run entirely offline without GPUs, cloud services, or API keys, it provides transparent, reproducible CRISPR analysis for research workflow

CRISPR Precision Studio – Explainable CRISPR 

Plant DNA Designer is an open-source computational biology platform for designing de novo, crop-optimised plant expression cassettes. It combines validated trait-to-effector mapping, translation-aware multi-objective genetic algorithm optimisation, codon optimisation, CRISPR guide design, plant-specific safety analysis, and automated expression cassette assembly. The platform supports 46 validated traits across 18 crops, runs entirely offline without AI or cloud services, includes a reproducible benchmarking suite against established codon optimisation methods, and generates comprehensive reports for expression, stability, safety, and synthesis readiness. GitHub: https://github.com/Dinesh431786/Plant-DNA-Designer

Plant DNA Designer

⚛️ Q-Trace Pro — Quantum Python Security Analyzer Detects true quantum-native, adversarial threats in Python: probabilistic bombs, entanglement, chained logic, steganography, and quantum anti-debug. Shows real quantum risk — no classical simulation, no safe mode. 🚀 Features True quantum-native adversarial pattern detection Probabilistic bombs, chained logic, quantum steganography, entanglement, and anti-debugging logic Real quantum risk scoring — using Cirq quantum simulator (no regex, no fake simulation) Supports file uploads and direct code snippet analysis Visualizes logic extraction, risk graphs, quantum state probabilities Quantum ML anomaly detection for advanced threat identification “Red Team” adversarial code samples (optional) 🛡️ What Makes Q-Trace Pro Unique? Brutal honesty: Exposes quantum-inspired and adversarial code patterns missed by classical/static tools No safe mode: Analyses without restrictions — for advanced security and red team research No classical simulation: All patterns are mapped to quantum circuits and simulated Full logic extraction: Highlights all suspicious logic blocks, chained triggers, and cross-function threats 💡 How to Use Upload a .py Python file or paste a code snippet into the web UI Click Brutal Quantum Analysis Review detected patterns, quantum risk scores, logic extraction, and visualizations (Optional) Generate Red Team suite for adversarial sample code Requirements (for local use): Python 3.8+ cirq, numpy, streamlit, matplotlib (see requirements.txt) To run locally: bash Copy Edit pip install -r requirements.txt streamlit run app.py ⚠️ Legal / Disclaimer This tool is for defensive security research and education only. Do not use it to analyze or deploy real-world malware, ransomware, or illegal payloads. You are solely responsible for how you use this tool. 🧑💻 Credits Built by DInesh K at Voxelta Private Limited Core quantum simulation: Cirq, Streamlit, Gemini AI