DeepMind software that can predict the 3D shape of proteins is already changing biology.
Category: biological – Page 120
Scientists believe they have found evidence of microbes that were thriving near hydrothermal vents on Earth’s surface just 300m years after the planet formed – the strongest evidence yet that life began far earlier than is widely assumed.
If confirmed, it would suggest the conditions necessary for the emergence of life are relatively basic.
A new PV module makes electricity from thermal radiation. Imagine that.
The electromagnetic spectrum is comprised of thousands upon thousands of frequencies. Sound and light are all part of the spectrum, as are the frequencies that make radio and television broadcasts possible. Today’s solar panels harvest light waves from a small part of the EM spectrum and turn them into electricity, but there are many other frequencies like thermal radiation that could someday stimulate new kinds of photovoltaic cells to generate electricity as well.
Researchers at Stanford have recently published a study in the journal Applied Physics Letters that describes a new type of cell that converts thermal radiation into electricity. When the sun goes down, living organisms and physical structures like buildings, road, and sidewalks radiate heat back into the atmosphere. We call this radiational cooling and it is those electromagnetic waves the Stanford researchers say can be put to work making electricity.
Chemical biology professor, Suyang Xu, works to crack the secrets of new states of matter.
Throughout human history, most of our efforts to store information, from knots and oracle bones to bamboo markings and the written word, boil down to two techniques: using characters or shapes to represent information. Today, huge amounts of information are stored on silicon wafers with zeros and ones, but a new material at the border of quantum chemistry and quantum physics could enable vast improvements in storage.
Suyang Xu, assistant professor of chemical biology, is tying quantum mechanical “knots” in topological materials, which may be the key to unlocking the potential of quantum technologies to store and process vast arrays of information and bring game-changing advances in a variety of fields.
“Imagine a rope identified by a number of knots,” Xu said. “No matter how much the shape of the rope is changed, the number of knots — known as the topological number — cannot be changed without altering its fundamental identity by adding or undoing knots.” It is this robustness that potentially makes topological materials particularly useful.
Lyons, B., Isaac, E., Choi, N.H. et al. The Simularium Viewer: an interactive online tool for sharing spatiotemporal biological models. Nat Methods (2022). https://doi.org/10.1038/s41592-022-01442-1
Chemical engineers and materials scientists are continuously looking for the following groundbreaking material, chemical, or medication. The emergence of machine-learning technologies has accelerated the discovery process, which may typically take years. Ideally, the objective is to train a machine-learning model on a few known chemical samples and then let it build as many manufacturable molecules of the same class with predictable physical attributes as feasible. You can develop new molecules with ideal characteristics if you have all of these components and the know-how to synthesize them.
However, current approaches need large datasets for training models. Many class-specific chemical databases only contain a few example compounds, restricting their capacity to generalize and construct biological molecules that might be generated in the real world.
This issue was addressed by a team of researchers from MIT and IBM by employing a generative graph model to create new synthesizable compounds within the same training data’s chemical class. The research was presented in a research paper. They model the production of atoms and chemical bonds as a graph and create a graph grammar — a linguistic analog of systems and structures for word ordering — that provides a set of rules for constructing compounds like monomers and polymers.
A Promising Method for Life-Detection
Posted in biological, space
Using the characteristic movement pattern of microbes to detect them on mars and the icy moons.
Microbial Motility.
The dissemination of synthetic biology into materials science is creating an evolving class of functional, engineered living materials that can grow, sense and adapt similar to biological organisms.
Nature has long served as inspiration for the design of materials with improved properties and advanced functionalities. Nonetheless, thus far, no synthetic material has been able to fully recapitulate the complexity of living materials. Living organisms are unique due to their multifunctionality and ability to grow, self-repair, sense and adapt to the environment in an autonomous and sustainable manner. The field of engineered living materials capitalizes on these features to create biological materials with programmable functionalities using engineering tools borrowed from synthetic biology. In this focus issue we feature a Perspective and an Article to highlight how synergies between synthetic biology and biomaterial sciences are providing next-generation engineered living materials with tailored functionalities.
Innovations in computing tech have improved the accuracy of DNA synthesis and enabled synthetic biology to work in the real world.
I don’t know about you, but I’m constantly looking for the “next big thing” in the stock market. And I think synthetic biology might just be it.
Why? If you invested just $10,000 into any of those world-changing stocks back in their early days, you’d have MILLIONS today. Forget the Iraq War, the housing crash, the European debt crisis. Forget the pandemic and the Russia-Ukraine war. Through it all, you’d have millions today.
Scientists have created synthetic organisms that can self-replicate. Known as “Xenobots,” these tiny millimeter-wide biological machines now have the ability to reproduce — a striking leap forward in synthetic biology.
Published in the Proceedings of the National Academy of Sciences 0, a joint team from the University of Vermont, Tufts University, and Harvard University used Xenopus laevis frog embryonic cells to construct the Xenobots.
Their original work began in 2020 when the Xenobots were first “built.” The team designed an algorithm that assembled countless cells together to construct various biological machines, eventually settling on embryonic skin cells from frogs.