mlsanityData to 14 Oct 2026

Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating and Programming Biology at All Levels

arXiv 2412.06993 ↗First posted 9 Dec 2024cs.AI cs.LG q-bio.QMcited by 5

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Abstract (arXiv)

We present an approach of using AI to model and simulate biology and life. Why is it important? Because at the core of medicine, pharmacy, public health, longevity, agriculture and food security, environmental protection, and clean energy, it is biology at work. Biology in the physical world is too complex to manipulate and always expensive and risky to tamper with. In this perspective, we layout an engineering viable approach to address this challenge by constructing an AI-Driven Digital Organism (AIDO), a system of integrated multiscale foundation models, in a modular, connectable, and holistic fashion to reflect biological scales, connectedness, and complexities. An AIDO opens up a safe, affordable and high-throughput alternative platform for predicting, simulating and programming biology at all levels from molecules to cells to individuals. We envision that an AIDO is poised to trigger a new wave of better-guided wet-lab experimentation and better-informed first-principle reasoning, which can eventually help us better decode and improve life.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 17 of its 63 references that are in the map. First posted on arXiv 9 Dec 2024.

Builds on

17 of 63 references.

References · 17

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5 more
  1. 2022Protein Representation Learning by Geometric Structure Pretrainingcited by 162
  2. 2023Continual Pre-Training of Large Language Models: How to (re)warm your model?cited by 137
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 2.

5 papers.