Scientific Roadmap

The long-term objective of Foldomics is to contribute to a deeper understanding of how biological information becomes biological form. Rather than focusing on a single biological scale, this roadmap explores the intermediate organizational levels where regulatory information, cellular interactions, spatial organization, and morphology converge.

Foldomics

Foldomics investigates how living systems transform regulatory information into observable structure. Genes, signaling networks, environmental cues, and physical constraints continuously interact to generate biological organization. Understanding this transformation represents the foundational question of the Foldomics framework.

Mesoscopic Biology

Between molecular mechanisms and macroscopic anatomy lies a largely unexplored intermediate domain. Mesoscopic Biology seeks to characterize this organizational layer and identify the principles that govern the emergence of tissues, developmental structures, and biological architectures. This level of description may provide a bridge between regulatory dynamics and morphological outcomes.

Synthetic Morphogenesis

A deeper understanding of biological organization may eventually enable the controlled generation of form. Synthetic Morphogenesis represents the long-term effort to understand how biological systems construct themselves and how those processes might one day be reproduced, guided, or engineered. The goal is not simply to assemble biological structures, but to understand the configurations from which structure naturally emerges.

Evoscope

Evoscope serves as a computational framework for exploring the emergence of organization from regulatory interactions. Through simulation, representation learning, and analysis of emergent structures, Evoscope provides a platform for investigating possible mesoscopic principles governing biological form.

Spatial Biology

Advances in spatial transcriptomics and single-cell technologies now allow biological organization to be observed directly within tissues. Foldomics aims to leverage these technologies to identify relationships between gene regulation, spatial context, and emerging morphology.

Mouse Embryo Transcriptomics

Embryonic development provides one of the most informative systems for studying how biological information becomes form. Spatial transcriptomic datasets from developing embryos offer an opportunity to investigate latent organizational variables and potential morphogenetic grammars operating during development.

Disease Modeling

Many diseases can be understood as disruptions of biological organization. By studying the relationship between regulatory information and morphology, Foldomics seeks to contribute new perspectives on developmental disorders, tissue degeneration, cancer, and other conditions characterized by altered biological architecture.

AI-Assisted Biological Discovery

Artificial intelligence provides powerful tools for identifying patterns that may be difficult to observe directly. Within Foldomics, AI is viewed not as a replacement for biological investigation, but as a framework for discovering hidden organizational principles and generating new biological hypotheses.

Looking Forward

The ultimate vision of Foldomics is the development of a scientific framework capable of describing, predicting, and eventually guiding the emergence of biological form. This vision remains exploratory and long-term. The present goal is to build the conceptual, computational, and experimental foundations necessary to better understand the relationship between information, organization, and morphology in living systems.