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.
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.
Continue reading “The Biggest Revolution Since the Computer Is Here — Synthetic Biology 🧫” »
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.
Scientists at Northwestern Medicine are using new advances in CRISPR gene-editing technology to uncover new biology that could lead to longer-lasting treatments and new therapeutic strategies for Human Immunodeficiency Virus (HIV).
The HIV epidemic has been overlooked during the COVID-19 pandemic but represents a critical and ongoing threat to human health with an estimated 1.5 million new infections in the last year alone.
Drug developers and research teams have been searching for cures and new treatment modalities for HIV for over 40 years but are limited by their understanding of how the virus establishes infection in the human body. How does this small, unassuming virus with only 12 proteins—and a genome only a third of the size of SARS-CoV-2—hijack the body’s cells to replicate and spread across systems?
Mar 31, 2022
Our 91st episode with a summary and discussion of last week’s big AI news!
Outline:
Continue reading “DeepMind Mafia, DishBrain, PRIME, ZooKeeper AI, Instant NeRF” »
Computer scientists at the University of California San Diego are showing how soil microbes can be harnessed to fuel low-power sensors. This opens new possibilities for microbial fuel cells (MFCs), which can power soil hydration sensors and other devices.
Computer scientists at the University of California San Diego are showing how soil microbes can be harnessed to fuel low-power sensors. This opens new possibilities for microbial fuel cells (MFCs), which can power soil hydration sensors and other devices.
Led by Department of Computer Science and Engineering (CSE) Assistant Professor Pat Pannuto and Gabriel Marcano, a Ph.D. student working with Pannuto, this research was presented today at the first Association for Computer Machinery (ACM) Workshop on No Power and Low Power Internet of Things.
Continue reading “Computer scientists show how bacteria can fuel low-power sensors” »
