Differential Bio

ESMC is the latest in the ESM family of protein language models, establishing a new frontier in representation learning for protein biology. Trained on billions of evolutionary sequences, it learns representations that reflect a mechanistic reduction of protein structure and function. The model is built on a transformer architecture, supports sequences as its core modality, and is trained on up to 6 billion proteins. ESMC is designed for protein science research, including structure prediction, function annotation, protein design, and understanding evolutionary relationships between proteins. It can generate novel proteins from partial sequence, structure, or functional constraints, helping researchers explore new possibilities in protein design and biological discovery. The Biohub Platform provides access to ESMC through the API and the ESM Python package, with quickstart resources for installing the package, creating an API key, connecting to the platform.

Sennos offers an AI-driven fermentation sensing, analytics, and optimization platform that combines precision in-tank hardware, cloud-based intelligence, and intuitive monitoring to give producers real-time visibility and predictive control over fermentation and fluidic processes. Sennos’s modular SennosM3 sensor modules continuously capture high-fidelity data, such as temperature, pH, pressure, density, dissolved oxygen, and other critical parameters, from fermentation tanks and send it to the cloud. There, the SennosIQ analytics engine applies AI to convert raw data into actionable, predictive insights that help users spot issues early, benchmark batches against historical performance, optimize outcomes, reduce waste, and improve consistency across production. The Sennoslink interface ties everything together, delivering real-time dashboards, alerts, and intuitive control from desktop or mobile devices so operators can monitor and manage operations from anywhere with clarity.