AI model from Google's DeepMind reads recipe for life in DNA An AI model developed by Google's DeepMind could transform our understanding of DNA - the complete recipe for building and running the human body - and its impact on disease and medicine discovery, according to researchers. Called AlphaGenome, the model could help scientists discover why subtle differences in our DNA put us at risk of conditions such as high blood pressure, dementia and obesity. It could also dramatically accelerate our understanding of genetic diseases and cancer. The developers of the model acknowledge it's not perfect, but experts have described it as an incredible feat and a major milestone. We see AlphaGenome as a tool for understanding what the functional elements in the genome do, which we hope will accelerate our fundamental understanding of the code of life, says Natasha Latysheva, research engineer at DeepMind.

Innovative research into the gene-editing tool targets influenza's ability to replicate--stopping it in its tracks. As he addressed an audience of virologists from China, Australia, and Singapore at October's Pandemic Research Alliance Symposium, Wei Zhao introduced an eye-catching idea. The gene-editing technology Crispr is best known for delivering groundbreaking new therapies for rare diseases, tweaking or knocking out rogue genes in conditions ranging from sickle cell disease to hemophilia . But Zhao and his colleagues at Melbourne's Peter Doherty Institute for Infection and Immunity have envisioned a new application. They believe Crispr could be tailored to create a next-generation treatment for influenza, whether that's the seasonal strains which plague both the northern and southern hemispheres on an annual basis, or the worrisome new variants in birds and other wildlife that might trigger the next pandemic.

Can AI create a life form? These "generative" genomes are a start Artificial intelligence can draw cat pictures and write emails. A research team in California says it used AI to propose new genetic codes for viruses--and managed to get several of these viruses to replicate and kill bacteria. The scientists, based at Stanford University and the nonprofit Arc Institute, both in Palo Alto, say the germs with AI-written DNA represent the "the first generative design of complete genomes." The work, described in a preprint paper, has the potential to create new treatments and accelerate research into artificially engineered cells. It is also an "impressive first step" toward AI-designed life forms, says Jef Boeke, a biologist at NYU Langone Health, who was provided an advance copy of the paper by .

This essay explores the possibility of making use of Evidenc e Theory (ET) [51] in order to represent communication between and within living organisms ranging from humans to bacteria. ET, also known as "Dempster-Shafer Theo ry" or "Belief Functions Theory," is a mathematical theory of uncertain reasoning th at takes as prototypical situation a judge evaluating testimonies, or a detective ex amining cues, rather than a gambler playing dice [48] [52]. This marks a sharp differenc e with Probability Theory (PT) because, albeit fundamental constructs such as Bayes' Theorem can be obtained from the corresponding expressions of ET as special cases, g amblers know the faces of a die or the numbers on a roulette -- they assume to live in a clos ed world -- whereas judges and detectives are aware that unexpected clues and te stimonies may open up novel possibilities -- they are aware of living in an open worl d [23]. I submit that ET is more appropriate than PT to represent info rmation transmission through arbitrary codes that multiply the generation o f novelties. Furthermore, its paradigmatic situation of judges listening to testimonies is structurally similar to information communication, whereas the paradigmatic situation of gamblers playing games of chance is not [52].

Paul Nurse: DNA contains the genetic code found in all known life on our planet. In each of nearly all of your roughly 30 trillion cells, there are 6.4 billion letters of DNA. If the DNA in all of your cells was used to store computer data, it could hold the equivalent of all the digital data we currently store on Earth. I'm Paul Nurse, and I've spent much of my working life thinking about DNA, in particular how it's copied and distributed inside cells every time they divide. I was awarded the Nobel Prize for this work in 2001. Our understanding of deoxyribonucleic acid, or DNA, has grown enormously since its discovery in the 19th century.

About 10 years ago, Žiga Avsec was a PhD physics student who found himself taking a crash course in genomics via a university module on machine learning. He was soon working in a lab that studied rare diseases, on a project aiming to pin down the exact genetic mutation that caused an unusual mitochondrial disease. This was, Avsec says, a "needle in a haystack" problem. There were millions of potential culprits lurking in the genetic code--DNA mutations that could wreak havoc on a person's biology. Of particular interest were so-called missense variants: single-letter changes to genetic code that result in a different amino acid being made within a protein.

Entrepreneur Elon Musk, one of the masterminds behind projects such as Tesla and SpaceX, announced his next venture, namely Neuralink. The company aims to merge humans with electronics, creating what Musk calls the neural lace. It is a device that injected into the jugular vein would reach the brain and then unfold into a network of electrical connections connected directly to human neurons. The idea is to develop enhanced brain-computer interfaces to increase the extent to which the biological brain can interact and communicate with external computers. The neural lace will go down to the level of brain neurons: it will be a mesh that will be able to connect directly to brain matter and then connect with a computer. That human being will be a cyborg.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The United States Food and Drug Administration (FDA) wants the public to be aware of counterfeit at-home over-the-counter (OTC) COVID-19 diagnostic tests circulating in the United States, according to a recent press release. "Counterfeit COVID-19 tests are tests that are not authorized, cleared, or approved by the FDA for distribution or use in the United States, but are made to look like authorized tests so the users will think they are the real, FDA-authorized test," the administration said. "The performance of these counterfeit tests has not been adequately established and the FDA is concerned about the risk of false results when people use these unauthorized tests." The at home diagnostic kits are primarily antigen tests.

With 2021 behind us, we're going down memory lane to highlight biotech innovations that shaped the year--with impact that will likely reverberate for many years to come. Covid-19 dominated the news, but science didn't stand still. CRISPR spun off variations with breathtaking speed, expanding into a hefty toolbox packed with powerhouse gene editors far more efficient, reliable, and safer than their predecessors. CRISPRoff, for example, hijacks epigenetic processes to reversibly turn genes on and off--all without actually snipping or damaging the gene itself. Prime editing, the nip-tuck of DNA editing that only snips--rather than fully cutting--DNA received an upgrade to precisely edit up to 10,000 DNA letters in a variety of cells.

Biomimicry is a tool which can be used while seeking innovation. The concept is that nature has already solved many design problems through the process of evolution. Living things that are still extant have received bits and bytes of code in the form of genetic material and when this information interfaces with the environment, sustainable life forms emerge. Animals, plants, viruses, and bacteria adapt by engineering themselves over the billions of years that life has existed on Earth. The Biomimicry Institute provides numerous examples.