科技日报--人工智能发现超过160000种新的RNA病毒
2024-11-04 10:31阅读：
题记：一旦AI参与人类的科学技术，就会产生飞跃。它是一个效率极高且富有创意的好助手；相信在今后的人类文明进程中，它一定会大显身手，与人类共同完成科学和技术的发展与进步。如今，AI已经渗透到人类生活与工作的各个角落，它也正在悄无声息地改变着人类的进步与文明。
通过人工智能发现了超过161000种RNA病毒，展示了巨大的、未经探索的病毒多样性，并为进一步的科学突破奠定了基础。来源：SciTechDaily.com
Largest discovery of new virus species sheds light on the
hidden virosphere.
新病毒物种的最大发现揭示了隐藏的病毒圈。
Artificial intelligence (AI) has been used to reveal
details of a diverse and fundamental branch of lif
e living right under our feet and in every corner of the globe.
These viruses not only play significant roles in human health but
are also prevalent in extreme environments, highlighting their
crucial roles in ecosystems and offering insights into viral
evolution and diversity.
人工智能（AI）已被用来揭示生活在我们脚下和全球每个角落的多样化和基本的生命分支的细节。这些病毒不仅在人类健康中发挥着重要作用，而且在极端环境中也很普遍，突显了它们在生态系统中的关键作用，并为病毒进化和多样性提供了见解。
Using a machine learning tool, researchers have discovered
161,979 new species of RNA virus, a breakthrough that could
dramatically enhance our understanding of Earth’s biodiversity and
assist in identifying millions more viruses yet to be
characterized.
利用机器学习工具，研究人员发现了161979种新的RNA病毒，这一突破可能会大大增强我们对地球生物多样性的理解，并有助于识别数百万种尚未被鉴定的病毒。
Published on October 9 in the journal Cell and conducted
by an international team of researchers, the study is the largest
virus species discovery paper ever published.
该研究于10月9日发表在《细胞》杂志上，由一个国际研究小组进行，是有史以来发表的最大的病毒物种发现论文。
Unprecedented Viral Diversity Unveiled
“We have been offered a window into an otherwise hidden
part of life on earth, revealing remarkable biodiversity,” said
senior author Professor Edwards Holmes from the School of Medical
Sciences in the Faculty of Medicine and Health at the University of
Sydney.
前所未有的病毒多样性揭晓
悉尼大学医学与健康学院医学科学学院的资深作者Edwards
Holmes教授说：“我们看到了地球上生命中一个隐藏的部分，揭示了非凡的生物多样性。”
“This is the largest number of new virus species
discovered in a single study, massively expanding our knowledge of
the viruses that live among us,” Professor Holmes said. “To find
this many new viruses in one fell swoop is mind-blowing, and it
just scratches the surface, opening up a world of discovery. There
are millions more to be discovered, and we can apply this same
approach to identifying bacteria and parasites.”
霍姆斯教授说：“这是在一项研究中发现的数量最多的新病毒物种，极大地扩展了我们对生活在我们中间的病毒的认识。”“一举发现这么多新病毒令人震惊，它只是触及了表面，开辟了一个被发现的世界。还有数百万种病毒有待发现，我们可以应用同样的方法来识别细菌和寄生虫。”
The Role of RNA Viruses in Extreme
Environments
Although RNA viruses are commonly associated with human
disease, they are also found in extreme environments around the
world and may even play key roles in global ecosystems. In this
study they were found living in the atmosphere, hot springs, and
hydrothermal vents.
RNA病毒在极端环境中的作用
尽管RNA病毒通常与人类疾病有关，但它们也存在于世界各地的极端环境中，甚至可能在全球生态系统中发挥关键作用。在这项研究中，他们被发现生活在大气、温泉和热液喷口中。
“That extreme environments carry so many types of viruses
is just another example of their phenomenal diversity and tenacity
to live in the harshest settings, potentially giving us clues on
how viruses and other elemental life-forms came to be,” Professor
Holmes said.
霍姆斯教授说：“极端环境携带了如此多种类型的病毒，这只是它们在最恶劣环境中生存的惊人多样性和坚韧性的另一个例子，可能为我们提供了病毒和其他元素生命形式是如何形成的线索。”
Advancements in Viral Identification via
AI
The researchers built a deep learning algorithm, LucaProt,
to compute vast troves of genetic sequence data, including lengthy
virus genomes of up to 47,250 nucleotides and genomically complex
information to discover more than 160,000 viruses.
人工智能在病毒识别方面的进展
研究人员构建了一种深度学习算法LucaProt，用于计算大量的遗传序列数据，包括长达47250个核苷酸的长病毒基因组和基因组复杂的信息，以发现超过160000种病毒。
“The vast majority of these viruses had been sequenced
already and were on public databases, but they were so divergent
that no one knew what they were,” Professor Holmes said. “They
comprised what is often referred to as sequence ‘dark matter’. Our
AI method was able to organize and categorize all this disparate
information, shedding light on the meaning of this dark matter for
the first time.
霍姆斯教授说：“这些病毒中的绝大多数已经被测序，并在公共数据库中，但它们差异很大，没有人知道它们是什么。”“它们由通常被称为序列‘暗物质’的东西组成。我们的人工智能方法能够组织和分类所有这些不同的信息，首次揭示了这种暗物质的含义。
The AI tool was trained to compute the dark matter and
identify viruses based on sequences and the secondary structures of
the protein that all RNA viruses use for
replication.
人工智能工具经过训练，可以计算暗物质，并根据所有RNA病毒用于复制的蛋白质的序列和二级结构来识别病毒。
Future Directions and Applications of AI in
Virology
It was able to significantly fast-track virus discovery,
which, if using traditional methods, would be time
intensive.
人工智能在病毒学中的未来发展方向和应用
它能够显著加快病毒发现的速度，如果使用传统方法，这将是耗时的。
Co-author from Sun Yat-sen University, the study’s
institutional lead, Professor Mang Shi said: “We used to rely on
tedious bioinformatics pipelines for virus discovery, which limited
the diversity we could explore. Now, we have a much more effective
AI-based model that offers exceptional sensitivity and specificity,
and at the same time allows us to delve much deeper into viral
diversity. We plan to apply this model across various
applications.”
该研究的机构负责人、中山大学的合著者芒石教授说：“我们过去依赖繁琐的生物信息学管道来发现病毒，这限制了我们可以探索的多样性。现在，我们有了一个更有效的基于人工智能的模型，它提供了卓越的敏感性和特异性，同时允许我们更深入地研究病毒多样性。我们计划将这个模型应用于各种应用。”
Co-author Dr Zhao-Rong Li, who researches in the Apsara
Lab of Alibaba Cloud Intelligence, said: “LucaProt represents a
significant integration of cutting-edge AI technology and virology,
demonstrating that AI can effectively accomplish tasks in
biological exploration. This integration provides valuable insights
and encouragement for further decoding of biological sequences and
the deconstruction of biological systems from a new perspective. We
will also continue our research in the field of AI for
virology.”
合作作者、阿里云智能Apsara实验室研究员李兆荣博士表示：“LucaProt代表了前沿人工智能技术与病毒学的重大融合，表明人工智能可以有效完成生物探索任务。这种融合为进一步解码生物序列和从新的角度解构生物系统提供了宝贵的见解和鼓励。我们还将继续在人工智能病毒学领域进行研究。”
Professor Holmes said: “The obvious next step is to train
our method to find even more of this amazing diversity, and who
knows what extra surprises are in store.”
霍姆斯教授说：“显而易见的下一步是训练我们的方法，以发现更多这种惊人的多样性，谁知道还会有什么额外的惊喜呢。”
