Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes. Here the authors create layered assemblies of genetically encoded devices that perform non-binary logic computation and signal processing using combinatorial promoters and feedback regulation.
CRISPR, the gene-editing technology, has been one of the major breakthroughs in biology in the last two decades. And while students learn about the capability to cut, paste, and alter genes, it’s rare that they get the chance to understand the technology by using it themselves.
However, more recent research suggests there are likely countless other possibilities for how life might emerge through potential chemical combinations. As the British chemist Lee Cronin, the American theoretical physicist Sara Walker and others have recently argued, seeking near-miraculous coincidences of chemistry can narrow our ability to find other processes meaningful to life. In fact, most chemical reactions, whether they take place on Earth or elsewhere in the Universe, are not connected to life. Chemistry alone is not enough to identify whether something is alive, which is why researchers seeking the origin of life must use other methods to make accurate judgments.
Today, ‘adaptive function’ is the primary criterion for identifying the right kinds of biotic chemistry that give rise to life, as the theoretical biologist Michael Lachmann (our colleague at the Santa Fe Institute) likes to point out. In the sciences, adaptive function refers to an organism’s capacity to biologically change, evolve or, put another way, solve problems. ‘Problem-solving’ may seem more closely related to the domains of society, culture and technology than to the domain of biology. We might think of the problem of migrating to new islands, which was solved when humans learned to navigate ocean currents, or the problem of plotting trajectories, which our species solved by learning to calculate angles, or even the problem of shelter, which we solved by building homes. But genetic evolution also involves problem-solving. Insect wings solve the ‘problem’ of flight. Optical lenses that focus light solve the ‘problem’ of vision. And the kidneys solve the ‘problem’ of filtering blood. This kind of biological problem-solving – an outcome of natural selection and genetic drift – is conventionally called ‘adaptation’. Though it is crucial to the evolution of life, new research suggests it may also be crucial to the origins of life.
This problem-solving perspective is radically altering our knowledge of the Universe. Life is starting to look a lot less like an outcome of chemistry and physics, and more like a computational process.
New research led by the Institute for Bioengineering of Catalonia (IBEC) has studied the migratory movement of groups of cells using light control. The results show that there is no leader cell that directs the collective movement, as previously thought, but that all cells participate in the process.
Check out this astonishing publication by Durrant et al.
A bispecific non-coding RNA expressed by the IS110 family of mobile genetic elements forms the basis of a programmable genome-editing system that enables the insertion, excision or inversion of specific target DNA sequences.
The Road To Wisdom — Dr. Francis Collins, MD, PhD — Former Director, National Institutes of Health (NIH); Distinguished Investigator, Center for Precision Health Research, National Human Genome Research Institute.
Dr. Francis S. Collins, M.D., Ph.D., (https://www.francisscollins.com/) is the former Director of the U.S. National Institutes of Health (NIH), where as the longest serving director of NIH (spanning 12 years and three presidencies) he oversaw the work of the largest supporter of biomedical research in the world, from basic to clinical research.
In a new study, scientists from Arizona State University and their collaborators studied genetic changes in a naturally isolated population of Daphnia pulex, a species of water flea. This tiny crustacean, nearly invisible to the naked eye, plays a vital role in freshwater ecosystems and provides a valuable insight into natural selection and evolution.
Their findings, recently published in the journal Proceedings of the National Academy of Sciences (PNAS), rely on a decade of research. Using advanced genomic techniques, the research team analyzed DNA samples from nearly 1,000 Daphnia.
They discovered that the strength of natural selection on individual genes varies significantly from year to year, maintaining variation and potentially enhancing the ability to adapt to future changing environmental conditions by providing raw material for natural selection to act on.
Irrespective of their personal, professional and social circumstances, different individuals can experience varying levels of life satisfaction, fulfillment and happiness. This general measure of life satisfaction, broadly referred to as “well-being,” has been the key focus of numerous psychological studies.
Better understanding the many factors contributing to well-being could help to devise personalized and targeted interventions aimed at improving people’s levels of fulfillment. While many past studies have tried to delineate these factors, few have done so leveraging the advanced machine learning models available today.
Machine learning models are designed to analyze large amounts of data, unveiling hidden patterns and making accurate predictions. Using these tools to analyze data collected in previous studies in neuroscience and psychology could help to shed light on the environmental and genetic factors influencing well-being.
Marfan syndrome is a genetic disorder that leads to a greater risk of aneurysms developing in a patient’s aorta. Early detection is key to survival. Researchers at Yale School of Medicine studied the use of artificial intelligence in the diagnostic process. The results could eventually lead to an easier and more accessible test.
Have we created an operating system for life? How close are we to cloning humans, and what would that even look like?
You’re in for a fascinating episode as the line between science and science fiction gets blurred. My guest is microbiologist and geneticist Andrew Hessel, the CEO and Founder of The Genome Project-Write, and author of \.
