We still don't understand human cell behavior. That's about to change.

"The human body is a problem. For most of us, it's a management problem: nutrition, exercise, blood work, the occasional X-ray or MRI, a treatment regimen. For doctors, it's a disease problem: What drives the formation of amyloid plaques in Alzheimer's? Which factors make certain cancers resistant to therapies? Why can't we detect Parkinson's sooner? (Doctors trying to study these questions may also say the human body is a funding problem.)"

""There are on the order of billions of proteins just in an individual human cell. The three billion nucleotides in the genome specify the entire program for the human body. There's just tremendous, tremendous complexity," says Alex Rives, Ph.D., head of science at Biohub, a nonprofit research organization developing AI-powered tools to improve (and speed) human health research. The complexity becomes exponentially greater once you factor in all the ways disease can arise, explains Rives's colleague Andrea Califano, Ph.D., Biohub's president of immune cell reprogramming. "There are 10 to the 400th power possible mutational patterns that can lead to cancer," he says. "It's more than the number of atoms in the universe.""

Human biology presents immense complexity, with billions of proteins per cell and three billion genomic nucleotides encoding the body's program. Mutational landscapes multiply that complexity, with roughly 10^400 possible mutational patterns that can lead to cancer. Practical challenges span personal management of health, clinical diagnostics, and research funding. Researchers are developing AI-powered tools and assembling novel datasets to render cellular behavior legible and to speed insight into cancer, neurodegeneration, and other diseases. Work focuses on mapping moment-to-moment cell behavior, stress responses, and intercellular interactions that drive transitions from health to illness.

Read at Big Think