New Proteins for new threads

** James Murray博士提出了一种使用深度学习和机器学习指导技术的布料生产创新方法，该方法有可能快速跟踪纺织行业向可持续发展的过渡。时尚业是 ** 造成严重环境问题的三大行业之一 **，占全球碳排放量的10%（超过英国，法国和德国的碳足迹总和）。大部分来自纺织材料生产，因为它严重依赖牲畜和石油基材料，这些材料与制造过程中的二氧化碳排放以及水和微塑料污染有关。据估计，如果不进行重大变革，到2050年，时尚业将占全球碳足迹的 **26%。该项目直接解决了纺织纤维可持续生产的需求。因此，Murray博士和合作者将开发一种新型蛋白质，可以纺成纤维并将纤维包裹起来，为指导商业化工作提供见解。与动物源性织物（碳足迹严重，使用大量淡水）和合成石油基织物（不可生物降解）相比，这种新型生物材料将更具可持续性。这种新方法的独特之处在于两个方面：* 首先，蛋白质将使用先进的深度学习方法重新设计 * 其次，机器学习将指导微生物菌株开发，用于使用精密发酵（PF）生产蛋白质（繁殖微生物以产生特定产品）。PF是唯一允许大规模产生新蛋白质的方法。这项技术不需要使用动物，因此不残忍，碳足迹也很低。默里博士将利用他在蛋白质开发方面的专业知识，设计一种具有理想特性的新型蛋白质，这种蛋白质将用于制造耐用的纤维，适用于生产柔软透气的织物。通过与英国生物技术公司Eden Bio的合作，他将能够选择高产微生物菌株，以满足使用ML技术的时尚行业大规模生产的需求。总之，本项目提供了一种创新，能够显着提高英国最大的行业之一的可持续性。

**Dr James Murray proposes an innovative approach to cloth production using deep learning and machine-learning-guided technology, which has the potential to fast-track the textile industry's transition to sustainability.**The fashion industry is among the **top 3 industries causing severe environmental problems**, contributing to 10% of carbon emissions globally (more than the total carbon footprint of the UK, France, and Germany combined). The majority comes from textile material production, as it relies heavily on livestock and petroleum-based materials, which are associated with CO2 emissions during manufacturing, as well as water and microplastic pollution. It's estimated that without drastic changes, the fashion industry will account for **26% of the global carbon footprint by 2050\.**This project addresses the need for sustainable production of textile fibres head-on. As such, Dr Murray and collaborators will develop a novel protein that can be spun into fibre and characterise the fibre to provide insights to guide commercialisation efforts. Compared to animal-derived fabrics (which have heavy carbon footprints and use a lot of fresh water) and synthetic petroleum-based fabrics (that don't biodegrade), this novel biomaterial will be more sustainable.Two aspects make this novel approach unique:* first, the proteins will be designed _de novo_ using advanced deep-learning methods* second, machine learning will guide microorganism strain development for protein production using precision fermentation (PF) (multiplying microbes to create specific products). PF is the only approach that allows the generation of novel proteins at scale. This technology is cruelty-free since it doesn't require the use of animals, and its carbon footprint is low.Dr Murray will apply his expertise in developing proteins to the design of a novel protein with desirable features, which will be used to create durable fibres suitable for producing soft, breathable fabrics. Through collaborating with UK-based biotech company Eden Bio, he will enable the selection of high-yielding microorganism strains to meet the demands of mass production in the fashion industry using ML technology.In summary, the present project offers an innovation capable of significantly enhancing the sustainability of one of the biggest industries in the UK.