Byte-sized bioinformatics: introducing Big Data through computational biology

字节大小的生物信息学：通过计算生物学引入大数据

• 批准号: ST/T000872/1
• 负责人: Daniel Barker
• 金额: $ 6.27万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FT000872%2F1
• 关键词: Byte; sized; bioinformatics; introducing; Big

This project will build on our successful public engagement with senior secondary school classes and teachers across Scotland. We propose increased reach and depth of coverage through:- further school visits to deliver our curriculum-linked workshop for Higher Biology, Higher Human Biology and Advanced Higher Biology pupils;- national deployment of our recently developed workshop for younger pupils, taking National 4 and National 5 Biology; and- enrichment and further development of long-term relationships with schools.We aim to have directly impacted bioinformatics teaching in at least 70% of secondary schools in Scotland by the end of the project. We will deliver, refine and share whole-class activities in bioinformatics across Scottish schools for Biology students in S3-S6, as well as continuing professional development (CPD) for teachers in Scotland. Priorities will include schools remote from major centres of STEM activity, and schools with low progression rates to university.Bioinformatics is an example of Big Data - a topic central to STFC's mission. Big Data is at the heart of many aspects of modern life, including communications, design, business, finance, manufacturing, transport, engineering, recreation and marketing as well as science. We use curriculum-linked bioinformatics as an entry point to engage young people with computational science and Big Data.Computational science and Big Data provide career development opportunities, an ability to conduct and support internationally competitive research, and are a keystone to future economic growth and security. These subjects are typically taught within university science programmes. But for rapid progress, social inclusion and public understanding, acquiring these skills must be integrated at much earlier stages in education.Bioinformatics (computational biology) provides an excellent means to allow young people to gain computational skills and to demonstrate the pervasive relevance of computational science and Big Data. Computational thinking - and many computational skills - are transferable across Big Data and STEM including computer science, physics, astronomy, chemistry, statistics and applied mathematics. Bioinformatics underpins current and future progress in medicine, agriculture and environmental research, and many STFC science and technology projects have a bioinformatics component.In Scotland, an important leap forward was made with the new Curriculum for Excellence for Higher Biology and Higher Human Biology curricula, which explicitly include bioinformatics. However, the topic is usually taught without a practical component, and may be seen as distant from practice in schools. In reality, practical bioinformatics can be easily accessible to schools - requiring only free software and an Internet connection to access exactly the same tools, data and environment as used professionally.Whole-class activities in bioinformatics for biology students reach an almost entirely new audience for scientific computation, and off-set the strong male gender bias associated with computer science. Our whole-class activities have extensive advantages for diversity and inclusion. Our workshops will give a taste of practical university-level activities, link topics within the Biology curriculum and across Biology and computing, and increase understanding of Big Data.We will leave Scottish teachers self-sufficient in bioinformatics, and we will leave pupils with a better understanding of bioinformatics and an awareness of the central role of computational science and Big Data in modern research, industry and society. The materials that we will develop will be made freely available to all, online.This project follows a pilot project funded via the University of Edinburgh and a successful project part-funded by an STFC Public Engagement Large Award (ST/R000328/1).

这个项目将建立在我们与苏格兰高中班级和教师成功的公众参与的基础上。我们建议通过以下方式扩大覆盖面和深度：-进一步访问学校，为高等生物学、高等人类生物学和高级高等生物学学生提供与课程相关的研讨会；-在全国部署我们最近为低年级学生开发的讲习班，参加国家四年级和国家五年级的生物课程；丰富和进一步发展与学校的长期关系。我们的目标是在项目结束时直接影响到苏格兰至少70%的中学的生物信息学教学。我们将在苏格兰学校为3- 6年级的生物学学生提供、完善和分享生物信息学的全班活动，并为苏格兰的教师提供持续专业发展（CPD）。优先考虑的学校将包括远离STEM主要活动中心的学校，以及升学率较低的学校。生物信息学是大数据的一个例子——这是STFC使命的核心主题。大数据是现代生活许多方面的核心，包括通信、设计、商业、金融、制造、运输、工程、娱乐和营销以及科学。我们使用课程链接的生物信息学作为切入点，让年轻人参与计算科学和大数据。计算科学和大数据提供了职业发展机会，开展和支持具有国际竞争力的研究的能力，是未来经济增长和安全的基石。这些科目通常在大学科学课程中教授。但要实现快速进步、社会包容和公众理解，就必须在更早的教育阶段就整合这些技能。生物信息学（计算生物学）提供了一个很好的方法，让年轻人获得计算技能，并展示计算科学和大数据的普遍相关性。计算思维和许多计算技能可以在大数据和包括计算机科学、物理、天文学、化学、统计学和应用数学在内的STEM领域进行转换。生物信息学是医学、农业和环境研究当前和未来进展的基础，许多STFC科技项目都有生物信息学成分。在苏格兰，新的高等生物学和高等人类生物学卓越课程取得了重要的飞跃，其中明确包括生物信息学。然而，这个主题通常没有实际的组成部分，并且可能被视为远离学校的实践。在现实中，实用的生物信息学可以很容易地进入学校——只需要免费软件和互联网连接就可以访问与专业使用完全相同的工具、数据和环境。为生物学学生提供的生物信息学课堂活动，为科学计算提供了几乎全新的受众，并抵消了与计算机科学相关的强烈的男性性别偏见。我们的班级活动具有广泛的多样性和包容性优势。我们的研讨会将提供实用的大学水平的活动，在生物学课程和跨生物学和计算的主题联系起来，并增加对大数据的理解。我们将让苏格兰教师在生物信息学方面自给自足，我们将让学生更好地理解生物信息学，并意识到计算科学和大数据在现代研究、工业和社会中的核心作用。我们将开发的材料将在网上免费提供给所有人。该项目遵循由爱丁堡大学资助的试点项目和由STFC公共参与大型奖（ST/R000328/1）部分资助的成功项目。

项目成果

DNA sonification for public engagement in bioinformatics.

• DOI: 10.1186/s13104-021-05685-7
• 发表时间: 2021-07-15
• 期刊: BMC research notes
• 影响因子: 1.8
• 作者: Plaisier H;Meagher TR;Barker D
• 通讯作者: Barker D

Bringing bioinformatics to schools

将生物信息学引入学校

• 发表时间: 2021
• 期刊: Hello World
• 作者: Bain SA

Bioinformatics in schools

学校生物信息学

• 发表时间: 2022
• 期刊: Genetics Society News
• 作者: Bain SA

Design, delivery and evaluation of a bioinformatics education workshop for 13-16-year-olds

• DOI: 10.1080/00219266.2020.1858932
• 发表时间: 2020-12-28
• 期刊: JOURNAL OF BIOLOGICAL EDUCATION
• 影响因子: 1.1
• 作者: Barker, Daniel;Bain, Stevie A.;Meagher, Thomas R.
• 通讯作者: Meagher, Thomas R.

Bringing bioinformatics to schools with the 4273pi project.

• DOI: 10.1371/journal.pcbi.1009705
• 发表时间: 2022-01
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Bain SA;Plaisier H;Anderson F;Cook N;Crouch K;Meagher TR;Ritchie MG;Wallace EWJ;Barker D
• 通讯作者: Barker D