New paper on protein language model interpretability with Alp Tartıcı and Russ Altman

A revolutionary scientific achievement is changing our understanding of biology. Scientists have successfully created life using a six letter genetic code, expanding the natural DNA alphabet from four letters to six. Normally, DNA is built from four bases A T C and G that encode all life on Earth. By adding two new synthetic bases, researchers have rewritten the fundamental rules of genetic information. This synthetic DNA, often called Hachimoji DNA, can store and transmit genetic instructions just like natural DNA but with even greater flexibility. In the lab, these modified organisms were able to replicate and pass on their expanded genetic code, proving that life can exist with a completely new biological blueprint. The implications are extraordinary. This breakthrough could lead to the creation of novel proteins, revolutionary medicines, and entirely new forms of life with traits never seen before. It also offers valuable insights into how life might exist on other planets with different chemical foundations. While ethical discussions and safety measures remain crucial, this discovery represents a bold step into the future of synthetic biology. Scientists have not only reimagined what life is but have also opened the door to designing it in ways nature never attempted. #SyntheticBiology #DNABreakthrough #FutureOfLife #ScienceRevolution

A revolutionary scientific achievement is changing our understanding of biology. Scientists have successfully created life using a six letter genetic code, expanding the natural DNA alphabet from four letters to six. Normally, DNA is built from four bases A T C and G that encode all life on Earth. By adding two new synthetic bases, researchers have rewritten the fundamental rules of genetic information. This synthetic DNA, often called Hachimoji DNA, can store and transmit genetic instructions just like natural DNA but with even greater flexibility. In the lab, these modified organisms were able to replicate and pass on their expanded genetic code, proving that life can exist with a completely new biological blueprint. The implications are extraordinary. This breakthrough could lead to the creation of novel proteins, revolutionary medicines, and entirely new forms of life with traits never seen before. It also offers valuable insights into how life might exist on other planets with different chemical foundations. While ethical discussions and safety measures remain crucial, this discovery represents a bold step into the future of synthetic biology. Scientists have not only reimagined what life is but have also opened the door to designing it in ways nature never attempted. #SyntheticBiology #DNABreakthrough #FutureOfLife #ScienceRevolution

🔬 Flipping Life’s Chemistry: Exploring Mirror-Image Molecular Biology 🧬 What if we could build life as a perfect mirror image of what we know today? Mirror-image molecular biology is no longer science fiction — researchers are synthesizing mirror DNA, mirror enzymes, and even pieces of mirror ribosomes. In my latest blog, I break down: ✅ The science of chirality and stereoisomerism ✅ Key breakthroughs in mirror nucleic acids, enzymes & translation systems ✅ Potential applications in medicine, diagnostics, and sustainability ✅ The global debate on biosafety, ethics, and regulation This field doesn’t just challenge our technical skills — it forces us to ask deep questions about what life could be and how far we should go in redesigning it. 📖 Read the full article here: [https://lnkd.in/dw4_Umw5] 💬 I’d love to hear your thoughts: Do you think we should pursue the creation of self-sustaining mirror organisms, or put a moratorium until global governance is ready? #SyntheticBiology #MolecularBiology #Biotech #MirrorBiology #LifeSciences #ResearchEthics #ScienceCommunication

✨ Have you ever wondered how a painkiller “knows” exactly where the pain is? The answer lies deep within proteins and their sequences. Proteins are the real messengers of our bodies, every signal, every response, every medicine’s action depends on them. In this short video, I’m sharing a glimpse of how we separate and study protein-peptide chains using bioinformatics tools. This process allows us to understand how proteins interact, how medicines target them, and ultimately how treatments are designed. 🔬 Bioinformatics and Computational Biology open an entirely new dimension to medicine from decoding protein structures to designing drugs that can revolutionize healthcare. The more we understand proteins, the closer we get to personalized and precise treatments. This is the beauty of science: what starts as a simple question, “How does the medicine know where to go?” , unfolds into a whole world of discoveries. PS: In the end my system turned off as I had been studying for so long and completely forgot to pluck in my charger 🙃 #Bioinformatics #ComputationalBiology #Proteins #DrugDiscovery #FutureOfMedicine

EzraBio_ Translation Biology Series — #7： Hallmarks of Good Ribo-seq Data -01 These features ensure that Ribo-seq truly captures translation at codon resolution. Without them, signals can be blurred by noise, but with them, data becomes a powerful lens into how proteins are made inside cells.dow

RFdiffusion3: All-Atom Protein Design for Biomolecules The provided podcast is an excerpt from a scientific paper introducing RFdiffusion3 (RFD3), a novel deep learning diffusion model for the de novo design of protein structures and their interactions with other biomolecules. RFD3 is presented as an advancement over previous methods, shifting to an all-atom generative approach that explicitly models all polymer atoms, including side chains, to enable more complex and precise conditioning for design challenges. The paper details the architecture and training of RFD3, highlighting its efficiency and reduced computational cost compared to predecessors like AlphaFold3 and RFdiffusion2. Furthermore, it demonstrates RFD3's broad applicability through in silico benchmarks and experimental validation across tasks such as designing protein-protein, protein-nucleic acid, and protein-small molecule binders, as well as de novo enzyme design. The conclusion emphasizes that RFD3 offers unprecedented control and precision in designing complex biological functions due to its atomic-level foundation and comprehensive conditioning mechanisms. https://lnkd.in/gkafC__6

“Turning biological complexity into human clarity.” Dr PB *Biotechnology is the Future "Bioinformatics stands as the intellectual crucible where computational algorithms converge with molecular biology, forging pathways to decipher the intricate codes of life. It transforms raw genomic and proteomic data into predictive models, enabling precision medicine, sustainable agriculture, and synthetic biology innovations. By integrating statistical rigor with computational power, bioinformatics illuminates biological networks that were once invisible, empowering humanity to anticipate disease trajectories, engineer resilient crops, and unravel evolutionary mysteries. It is not merely a discipline but a transformative paradigm — where data becomes discovery, and discovery becomes destiny.” Unkown

How did the building blocks of life come together to spawn the first organisms? It's one of the most longstanding questions in biology — and scientists just got a major clue. In a new study published in the journal Nature, a team of biologists say they've demonstrated how RNA molecules and amino acids could combine, by purely random interactions, to form proteins — the tireless molecules that are essential for carrying out nearly all of a cell's functions. Proteins don't replicate themselves but are created inside a cell's complex molecular machine called a ribosome, based on instructions carried by RNA. That leads to a chicken-and-egg problem: cells wouldn't exist without proteins, but proteins are created inside cells. Now we've gotten a glimpse at how proteins could form before these biological factories existed, snapping a major puzzle piece into place. https://lnkd.in/dAK5ceP8

#newpaper 🔬 A new study published in Nature Communications presents an interactive platform that brings together nearly a billion protein structures, making it easier to explore how proteins function, how they relate to diseases, and how they can guide new therapies. The project was carried out in international collaboration with partners from the Flatiron Institute and the Open Molecular Software Foundation, with a strong contribution from MCB researchers working together with colleagues from Sano Science – Centre for Computational Medicine. The platform integrates major protein databases, including the Nobel Prize-winning AlphaFold, and introduces the concept of “functional locality” — showing that proteins with similar functions tend to group together structurally. Using AI tools such as deepFRI, the team was also able to predict functions for previously uncharacterized proteins. Congratulations to the Authors! Jagiellonian University NCN National Science Centre 🖥️ Explore the interactive map: https://lnkd.in/ee4Fq3-Z 📄 Read the paper: https://lnkd.in/dCuTJbRs 📸 In the photo: Dr Paweł Szczerbiak, PhD (left) and Dr Tomasz Kościółek (right) – the main authors of the study.

Really want to be an expert #bioinformatician? Understand biology is a must! My experience in #bioinformatics already taught me that #biology understanding needs to come first, and this phenomena is not working in the reverse way. Let me tell you an example. In #microarray technology for human #genotyping, such as Illumina Infinium, the signal that will be given by machine just only divided by three kind of signal. Red, green, or red and green together. Why the output only two type of signal then? Only when we understand biology we can find the answer. We know that human is a #diploid organism, which may produce homozygote (dominant or recessive) or heterozygote alleles. Therefore, two kind of signals in microarray is already enough to capture the variation of genes in human. Just a reminder, this phenomena can be different with other organism such as plant with polyploid alleles types. By understanding biology, bioinformatician can formulate hypothesis and reduce any false informations. That is why, biological context is necessary for bioinformatician and hopefully, this real example will help you understand how bioinformaticians work! 🥰