MSc Applied Bioinformatics

生物信息学是通过信息技术的应用来解决生物学问题。生物分析平台的最新进展使人们能够获得大量重要的生物学数据。由于大规模基因组测序项目的完成，这些数据的数量和复杂性都进一步增长，我们现在有了一个框架，在此基础上建立了所谓的后基因组技术：转录组学、蛋白质组学和代谢组学。前沿生物学越来越多地集中在阐明生物信息学技术所需要的潜在生物机制。这些包括生物标志物发现的高级数据分析和系统生物学所需的数据集成策略。这个定制的理学硕士课程是在行业投入的基础上开发的，旨在培养能够与实验室从业者交流的毕业生，并在现代跨学科生物学中发挥越来越重要的作用。因此，学生将接受最先进的生物信息学工具和分析技术的培训，以理解和处理复杂的数据集，并学习用生物信息学中使用的主要语言进行编程；R， Perl和Java。本课程包括五个主要的必修要素：1。导论课程：两个课程旨在培养生命科学或信息技术专业的学生，使他们成为生物信息学专业的学生，能够用共同的语言进行交流，并通过核心应用模块获得坚实的基本技能和知识基础。2. 五个核心模块：每个模块由一到两周的密集教学组成，授课和动手操作的时间平均各占一半。每个模块之后通常是一个学习周，在这个学习周中，学生们要完成与模块相关的重要课程作业。这些课程作业都是为了解决真正的生物学问题而设计的，这些问题需要使用生物信息学来解决，例如编写软件工具，从数据中提取生物学相关信息，整合数据或建模交互或系统。3. 软件开发小组项目：小组项目是课程中两个综合评估点之一，旨在将学习发展与m级经验结合起来，发展核心模块的关键编程技能和特定应用的信息学方法。在最初的讲座涵盖了特定于项目的技能之后，组成团队来处理具有挑战性的小组项目。鼓励每个团队在课程导师的指导下制定自己的角色和管理结构。4. 综合考试：由所有学生在小组项目之后和开始个人研究项目之前进行。该考试评估技术和概念知识的广度，以及学生在生物信息学和更广泛的相关领域讨论这些知识的能力。5. 由学生选择的为期18周的论文项目：与硕士课程的目标保持一致，所有项目必须涉及应用生物信息学方法来解决生物学问题。通常项目涵盖不同的应用程序（如微阵列，蛋白质组学，文本挖掘，系统生物学），并需要不同的信息技能(如。编程、统计、数据库)。项目是我们工业合作伙伴参与的主要途径，也是学生获得实际经验的绝佳机会。该课程规定最多招收25名学生，最少招收10名学生，但在特殊情况下也会招收更少的学生。在现有员工的情况下，最佳学生人数是15人。请参阅支持案例和相关计划规格以了解更多细节。

Bioinformatics is about solving biological problems through the application of information technologies. Recent advances in bioanalytical platforms have resulted in the ability to acquire vast amounts of biologically-important data. Since the completion of large-scale genome sequencing projects both the volume and complexity of such data have further grown and we now have a framework on which to base what are known as the post-genomic technologies: transcriptomics, proteomics and metabolomics. Cutting-edge biology is focused increasingly on the elucidation of underlying biological mechanisms for which bioinformatic techniques are needed. These include advanced data analysis for biomarker discovery and data integration strategies required for systems biology. Developed with industry input, this bespoke MSc aims to produce graduates who are able to talk a common language with laboratory-based practitioners and play an increasingly important role in modern interdisciplinary biology. As such students will be trained in state-of-the-art bioinformatics tools and the analytical techniques for understanding and handling complex data sets, and also learn to programme in the major languages used in bioinformatics; R, Perl and Java. The course comprises five main compulsory elements: 1. Introductory streams: two streams designed to develop life science or IT students who join the course into a coherent cohort of bioinformatics students, able to communicate with a common language, and progress through the core application modules with a solid foundation of fundamental skills and knowledge. 2. A series of five core modules: Each module consists of one or two intensive weeks of teaching, with an average 50/50 split between lectures and hands-on computer work. Each module is typically followed by a study week in which the students tackle a significant piece of coursework related to the modules. These coursework assignments are all designed to typify real biological problems, which need to be solved using bioinformatics - examples include writing a software tool, extracting biologically relevant information from data, integrating data or modelling interactions or systems. 3. A software development group project: the group project is one of two integrative assessment points during the course designed to align the learning development with M-level experience and develop on key programming skills and application-specific informatics approaches form the core modules. Following initial lectures covering skills specific to the project, teams are formed to tackle challenging group projects. Each team is encouraged to work out their roles and management structure with guidance from the course tutors. 4. Integrating examination: undertaken by all students following the group project and immediately prior to beginning their individual research projects. This exam assesses the breadth of technical and conceptual knowledge and the student's ability to discuss this in the context of bioinformatics and wider associated fields. 5. An 18-Week Thesis Project Selected by the Student : In keeping with the aims of the MSc course, all projects must involve the application of bioinformatics approaches to solve a biological problem. Typically projects cover different applications (e.g. microarrays, proteomics, text mining, systems biology) and requiring different informatic skills (e.g .programming, statistics, databases). Projects are a major avenue for the involvement of our industrial partners, and an excellent opportunity for students to gain real-world experience. The course is specified to run with a maximum of 25 students and a minimum of 10, although it has run with fewer under exceptional circumstances. The optimum student number with current staff is 15. Please see the Case for Support and associated programme specifications for more details.