A robot scientist for yeast systems biology

酵母系统生物学机器人科学家

• 批准号: BB/D00425X/1
• 负责人: Ross King
• 金额: $ 74.83万
• 依托单位: Aberystwyth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FD00425X%2F1
• 关键词: robot; scientist; yeast; systems; biology

The application of Artificial Intelligence to scientific research is growing in importance because of the increasing power of computers increased use of laboratory automation. The need for automation is particularly important in the branch of science known as systems biology, where scientists are trying to understand how genes work together to form living cells. Applying Artificial Intelligence to laboratory robotics we have previously developed a Robot Scientist that generates hypotheses about the function of particular genes in bakers yeast, and then designs and carries out experiments to test them. Baker's yeast (Saccharomyces cerevisiae) is used as a model organism for human cells, as it easier to grow and experiment with, and relatively simple (approximately 6,000 genes compared to approximately 30,000 in humans). We set the robot the problem of discovering the function of different genes in yeast. The functions of about 30 per cent of the genes in yeast are still unknown and, with many of these genes thought to be common to the human genome, they could prove to be medically important in the future. The research involved using knockout strains of yeast that have had one gene removed. By observing how the yeast grows, or doesn't grow, on defined chemical substrates, it is possible to start establishing different possible functions for the gene being investigated. It is like trying to understand what the different components in a car do by removing them one by one. The robot scientist generates a set of hypotheses from what it knows about yeast metabolism and then plans an experiment that will eliminate as many hypotheses as possible, as fast and as cheaply as possible. It conducts experiments by dispensing and mixing liquids and then measuring the growth of yeast using an adjacent plate reader that feeds the results back into the system. The robot then evaluates the results against the set of hypotheses, generates new hypotheses, and the process starts again - the same type of cycle human scientists use to understand the world. In this proposal we plan to extend the Robot Scientist in a number of ways: We shall use the Robot Scientist to develop a model of the whole of yeast metabolism. We shall develop new reasoning mechanisms for the robot. We shall use a much bigger robot capable to running many more experiments automatically.

人工智能在科学研究中的应用越来越重要，因为计算机的功能越来越强大，实验室自动化的使用越来越多。自动化的需求在系统生物学的分支科学中尤为重要，科学家们正试图了解基因是如何共同作用形成活细胞的。将人工智能应用于实验室机器人技术，我们以前开发了一个机器人科学家，可以生成关于面包酵母中特定基因功能的假设，然后设计并进行实验来测试它们。面包酵母（Saccharomyces cerevisiae）被用作人类细胞的模式生物，因为它更容易生长和实验，并且相对简单（约6，000个基因，而人类约30，000个基因）。我们给机器人设置了发现酵母中不同基因功能的问题。酵母中大约30%的基因的功能仍然未知，其中许多基因被认为是人类基因组所共有的，它们可能在未来被证明具有重要的医学意义。这项研究涉及使用一个基因被移除的酵母敲除菌株。通过观察酵母在特定的化学基质上如何生长或不生长，可以开始为正在研究的基因建立不同的可能功能。这就像试图通过一个接一个地拆卸汽车中的不同部件来了解它们的作用一样。机器人科学家根据它对酵母代谢的了解生成一组假设，然后计划一个实验，尽可能快、尽可能便宜地消除尽可能多的假设。它通过分配和混合液体进行实验，然后使用相邻的酶标仪测量酵母的生长，将结果反馈到系统中。然后，机器人根据假设集评估结果，生成新的假设，然后重新开始这个过程-与人类科学家用来理解世界的循环相同。在这个提案中，我们计划以多种方式扩展机器人科学家：我们将使用机器人科学家开发整个酵母代谢的模型。我们将为机器人开发新的推理机制。我们将使用一个大得多的机器人，能够自动进行更多的实验。

项目成果

From Petri Plates to Petri Nets, a revolution in yeast biology.

从培养皿到培养网，酵母生物学的一场革命。

• DOI: 10.17863/cam.81152
• 发表时间: 2022
• 作者: Oliver S

An Integrated Laboratory Robotic System for Autonomous Discovery of Gene Function

用于自主发现基因功能的集成实验室机器人系统

• DOI: 10.1016/j.jala.2009.10.001
• 发表时间: 2010
• 期刊: Journal of the Association for Laboratory Automation
• 作者: Sparkes A

NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding.

• DOI: 10.1038/s41540-021-00200-x
• 发表时间: 2021-10-20
• 期刊: NPJ systems biology and applications
• 影响因子: 4
• 作者: Wang K;Stevens R;Alachram H;Li Y;Soldatova L;King R;Ananiadou S;Schoene AM;Li M;Christopoulou F;Ambite JL;Matthew J;Garg S;Hermjakob U;Marcu D;Sheng E;Beißbarth T;Wingender E;Galstyan A;Gao X;Chambers B;Pan W;Khomtchouk BB;Evans JA;Rzhetsky A
• 通讯作者: Rzhetsky A