Computational and Structural Biotech Journal

Our research article: ChatGPT not only matches seasoned human doctors but also outperforms junior doctors, exemplifying the remarkable power of AI innovation in healthcare. #AI #HealthcareInnovation #ChatGPT #MedicalTech #FutureOfMedicine Computational and Structural Biotech Journal

We proudly announce our brand-new innovation report in the Computational and Structural Biotech Journal. Under the title “SSbD4CheM project innovations in the textiles, cosmetic and automotive sectors”, the paper summarises the project aims and the case studies. You can read it here: https://lnkd.in/dRU2GreT Big congrats to all authors: Dr. Mansoor Ahmad Bhat, Tanja Radu, Nacho Martín-Fabiani, Panagiotis Kolokathis, Tassos Papadiamantis, Stephan Wagner, Yvonne Kohl, Witters Hilda, Wouter Gebbink, Yentl Pareja Rodriguez, Giuseppe Cardellini, Roel Degens, Ivana Burzic, Beatriz Alfaro Serrano, Claudia Pretschuh, Eduardo Santamaría Aranda, Elena Contreras García, Judith Sinic, Christoph Jocham, Dror Jacques Cohen, Zeevi Maor, Assaf Assis, Ph.D., Ondrej Panák, Uroš Novak, Dr. Sukriti Hans, Antje Biesemeier, Pau Camilleri Lledó, Fruela Pérez Sánchez, Thomas Arblaster, Nils Thonemann, Jeroen Guinée, Andrea Pipino, Onur Çelen , (PhD), Hariprasad Alwe, Roland Drexel, Florian Meier, Indre Piragyte-Langa Oliva, Ghada Tagorti, PhD , Barry Hardy, and Milica Velimirovic #materialsengineering #nanotechnology #chemicalengineering #nanoparticles #chemicalsafety #sustainability #riskassessment #SSbD #SSbDframework

Lads and Gents, with the graphical abstract in all its glory, our paper on a disease-related ACTG2 (and ACTA2) missense variant - same mutation, Arg257(258)Cys, but in two different actins, similar phenotype, but in different tissues - has been assigned to the in progress CBSJ, General section, volume 👇 Thx to Federica Chiappori, Federica Viti and Matteo de Rosa for the combined effort!

🧬 This study challenges the conventional assumption that gene regulation occurs in a homogeneous nuclear environment. By incorporating spatial heterogeneity, researchers improve the accuracy of stochastic simulations—offering a more realistic representation of gene expression dynamics. Here are the 10 key takeaways from the paper: 👇 1️⃣ Homogeneous Assumptions Fall Short: Traditional stochastic simulations assume even molecular distribution, which is unrealistic for slow-diffusing transcription factors. 2️⃣ Spatial Heterogeneity Matters: When transcription factors move slowly, gene expression patterns deviate significantly from predictions made using homogeneous models. 3️⃣ Gillespie Algorithm Limitations: The widely used Gillespie algorithm does not account for molecular positioning, leading to inaccuracies in certain conditions. 4️⃣ Computational Challenges: Modeling spatial heterogeneity increases computational load, requiring alternative simulation strategies. 5️⃣ Quasi-Steady-State Approximations (QSSA): To balance accuracy and efficiency, researchers tested different QSSA methods for reducing simulation complexity. 6️⃣ Stochastic Low-State QSSA (slQSSA) Prevails: While both stQSSA and slQSSA speed up simulations, only slQSSA accurately captures gene regulation under spatial constraints. 7️⃣ Oscillatory Systems Impact: Using an inaccurate QSSA (stQSSA) can distort the natural oscillations in gene regulatory networks. 8️⃣ Error Reduction & Performance Gains: slQSSA reduces errors and computational time significantly while maintaining biological accuracy. 9️⃣ Guidelines for Future Simulations: The study provides a framework for selecting appropriate stochastic simulation methods based on system properties. 🔟 Advancing Computational Biology: By refining stochastic models, this research paves the way for more precise gene regulation studies in complex biological systems. 📝 Seok Joo Chae, Seolah Shin, Kangmin Lee, Seunggyu Lee, Jae Kyoung Kim 🔗 From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation. Computational and Structural Biotech Journal, DOI: 10.1016/j.csbj.2025.01.004 📚 CSBJ: https://www.csbj.org/ #GeneRegulation #ComputationalBiology #StochasticSimulations #QSSA #Bioinformatics #Genomics #DNA

Influence of CTG repeats from the human DM1 locus on murine gut microbiota. Read the article here: https://lnkd.in/gXugVZ9h

Novel metal sites revealed by spectroscopic and structural characterization of the ferric uptake regulator from Acidithiobacillus ferrooxidans. Read the article here: https://lnkd.in/gb5MhU5g

m6A2Circ: A comprehensive database for decoding the regulatory relationship between m6A modification and circular RNA. Read the article here: https://lnkd.in/g-PXwd-S

Protein design accelerates the development and application of optogenetic tools. Read the article here: https://lnkd.in/g4tifnFC

Identification of novel inhibitors targeting serine acetyltransferase from Neisseria gonorrhoeae. Read the article here: https://lnkd.in/gEEd7zdF

MMRT: MultiMut Recursive Tree for predicting functional effects of high-order protein variants from low-order variants. Read the article here: https://lnkd.in/g6C9nvS6