Biology and biochemistry

Biology studies living systems at all levels of organization, from molecules and cells to ecosystems, while biochemistry focuses specifically on the chemical processes within living organisms. The field seeks to understand how life works, how it evolved, and how biological systems can be modified or designed for beneficial purposes.

Major challenges include understanding complex cellular processes, designing artificial biological systems, and developing new approaches to treat diseases and enhance human health. Modern biology is increasingly quantitative and engineering-oriented, with synthetic biology and systems biology approaches enabling unprecedented manipulation and understanding of living systems.

The 10 biology and biochemistry problems

  • Complete Cell Atlas at Molecular Resolution

  • Synthetic Minimal Cell

  • Brain Organoid with Consciousness Markers

  • Multi-Scale Simulation of Cellular Systems

  • Comprehensive Human Immune System Map

  • Complete Protein Structure and Function Prediction

  • Aging Reversal Intervention

  • Whole-Brain Neural Activity Map

  • Predictive Developmental Biology Framework

  • Engineered Multicellular System with Emergent Cognition

Biology and biochemistry problem sample

* These are just preliminary ideas and do not represent final problems of the Berkeley 100 Challenge. The final problems will be determined by our Scientific Committees.

Multi-Scale Simulation of Cellular Systems

Problem Statement:

Develop a computational framework capable of simulating complete cellular behavior across scales from quantum mechanical interactions to whole-cell phenotypes, integrating molecular, subcellular, and cellular processes with quantitative accuracy.

Evaluation Criteria:

  • Accurate simulation of cellular dynamics down to molecular resolution

  • Integration of processes across at least 12 orders of magnitude in time (femtoseconds to hours)

  • Integration of processes across at least 9 orders of magnitude in space (angstroms to millimeters)

  • Validated predictions of cell behavior in response to genetic or environmental perturbations

  • Computational efficiency enabling simulation of multicellular systems

  • Open-source implementation accessible to the broader scientific community

  • Application across at least three different cell types demonstrating generalizability

Feasibility Assessment: 

Extremely challenging, likely requiring 15-25 years. Requires revolutionary advances in multiscale modeling and computational resources. Progress in molecular dynamics simulation, systems biology modeling, and machine learning approaches would be important precursors.

Impact on the Field: 

Would transform biology from primarily experimental to a predictive science where simulations guide experiments. Would enable in silico testing of drugs and genetic modifications. May reveal emergent properties arising from cross-scale interactions that have been inaccessible to current approaches focused on single scales.

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