圣地亚哥大学科学家利用基因组分析和机器学习预测疟疾的抗药性。 UC San Diego scientists predict drug resistance in malaria using genome analysis and machine learning.

圣地亚哥哥伦比亚大学的研究人员分析了724种疟疾寄生虫的基因组,以预测抗药性,这一突破可能有助于确定新疗法的优先次序。 Researchers at UC San Diego analyzed the genomes of 724 malaria parasites to predict drug resistance, a breakthrough that could help prioritize new treatments. 科学家利用机器学习,不仅可以预测疟疾的抗药性,还可以预测包括癌症在内的其他疾病的抗药性。 Using machine learning, scientists could forecast resistance not just in malaria but also in other diseases, including cancer. 该研究报告发表在《科学》上,它揭示了各种病原体和人体细胞之间驱动药物抗药性的一贯遗传模式。 The study, published in Science, reveals consistent genetic patterns driving drug resistance across various pathogens and human cells.