MSc in Bioinformatics and Theoretical Systems Biology
生物信息学和理论系统生物学硕士
基本信息
- 批准号:BB/H021035/1
- 负责人:
- 金额:$ 39.37万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Training Grant
- 财政年份:2010
- 资助国家:英国
- 起止时间:2010 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Aims and objectives: - To train students for a research career in bioinformatics and systems biology in academia, industry or the public sector. - Develop understanding of the fundamental disciplines underlying bioinformatics and systems biology. - Develop broad research and analytical skills necessary to conduct original research in bioinformatics and systems biology. - Enable discipline hopping for talented mathematicians, physicists and computer scientists. - Provide mathematical, statistical and computational skills to biologists. and biomedical scientists. - To equip students with the general skills for effective research in academia and industry the fields of bioinformatics and systems biology. The MSc in Bioinformatics and Theoretical Systems Biology addresses the need for highly trained individuals at the interface between the life, medical and physical sciences. The course offers an important and highly sought after opportunity for biologists and medical scientists to acquire numerical and computational skills, and for people from mathematics, physics, computer science or engineering to enter the life- and biomedical sciences. We provide a modern introduction to molecular and cellular biology, genomics and proteomics as well as the recent developments in integrative systems biology; furthermore students receive in-depth introductions to mathematical and statistical methods for bioinformatics and systems biology, as well as training in a range of relevant programming languages. Graduates of this course are able to engage with complex biological systems. They learn how to generate and test hypotheses from large and integrative biological datasets, and how to draw functional inferences from comparisons of different biological systems in different species. Students are exposed to a broad range of topics in bioinformatics and systems biology. Teaching of the course involves academics from all faculties (Medicine, Natural Sciences, Engineering) at Imperial College as well as industry representatives. The breadth in basic training - essential to ensure successful discipline hopping or interdisciplinary training - is complemented by in-depth research projects (in total 75% of the time are spent on three research projects); good students typically manage to get a peer-reviewed research publication out of one of these projects. Bioinformatics and Systems Biology and the structrue of the MSc has changed to reflect these developments. The course has increasingly moved into the area of mathematical modelling of biological systems and processes and now has substantial components covering these areas. This has been in response to student feedback, external examiners as well as from colleagues in academia, industry and research funding bodies.
宗旨和目标: - 培训学生在学术界、工业界或公共部门从事生物信息学和系统生物学的研究工作。 - 加深对生物信息学和系统生物学基础学科的理解。 - 培养进行生物信息学和系统生物学原创研究所需的广泛研究和分析技能。 - 为有才华的数学家、物理学家和计算机科学家提供学科跳跃。 - 为生物学家提供数学、统计和计算技能。和生物医学科学家。 - 使学生具备在学术界和工业界生物信息学和系统生物学领域进行有效研究的一般技能。生物信息学和理论系统生物学理学硕士解决了生命、医学和物理科学之间对训练有素的人员的需求。该课程为生物学家和医学科学家提供了一个重要且备受追捧的机会,让他们获得数值和计算技能,也为数学、物理、计算机科学或工程学的人们进入生命和生物医学科学领域提供了一个重要且备受追捧的机会。我们提供分子和细胞生物学、基因组学和蛋白质组学以及综合系统生物学的最新发展的现代介绍;此外,学生还将深入了解生物信息学和系统生物学的数学和统计方法,以及一系列相关编程语言的培训。本课程的毕业生能够参与复杂的生物系统。他们学习如何从大型综合生物数据集中生成和测试假设,以及如何从不同物种的不同生物系统的比较中得出功能推论。学生接触到生物信息学和系统生物学的广泛主题。该课程的教学涉及帝国理工学院所有院系(医学、自然科学、工程)的学者以及行业代表。基础培训的广度对于确保成功的学科跳跃或跨学科培训至关重要,并辅以深入的研究项目(总共 75% 的时间花在三个研究项目上);优秀的学生通常能够从这些项目中获得一份经过同行评审的研究出版物。生物信息学和系统生物学以及理学硕士的结构已经发生变化,以反映这些发展。该课程越来越多地进入生物系统和过程的数学建模领域,现在有涵盖这些领域的重要组成部分。这是对学生反馈、外部审查员以及学术界、工业界和研究资助机构同事的反馈的回应。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Michael Stumpf其他文献
Learning qualitative and quantitative reasoning in a microworld for elastic impacts
在微观世界中学习定性和定量推理以获得弹性影响
- DOI:
10.1007/bf03173135 - 发表时间:
1990 - 期刊:
- 影响因子:3
- 作者:
R. Ploetzner;H. Spada;Michael Stumpf;K. Opwis - 通讯作者:
K. Opwis
Closing the gap: endoscopic treatment of esophageal anastomotic leakage—a retrospective cohort study
- DOI:
10.1007/s00464-025-11904-0 - 发表时间:
2025-07-14 - 期刊:
- 影响因子:2.700
- 作者:
Myriam W. Heilani;Daniel Teubner;Thomas Haist;Mate Knabe;Patrizia Malkomes;Florian Alexander Michael;Michael Stumpf;Stefan Zeuzem;Wolf Otto Bechstein;Mireen Friedrich-Rust;Georg Dultz - 通讯作者:
Georg Dultz
Michael Stumpf的其他文献
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{{ truncateString('Michael Stumpf', 18)}}的其他基金
Next generation approaches to connect models and quantitative data
连接模型和定量数据的下一代方法
- 批准号:
BB/P028306/1 - 财政年份:2018
- 资助金额:
$ 39.37万 - 项目类别:
Research Grant
Statistical modelling of in vivo immune response dynamics in zebrafish to multiple stimuli
斑马鱼对多种刺激的体内免疫反应动态的统计模型
- 批准号:
BB/K017284/1 - 财政年份:2013
- 资助金额:
$ 39.37万 - 项目类别:
Research Grant
Development of a high-throughput quantitative immunofluorescence method and stochastic modeling of signalling networks
开发高通量定量免疫荧光方法和信号网络随机建模
- 批准号:
BB/G530268/1 - 财政年份:2009
- 资助金额:
$ 39.37万 - 项目类别:
Research Grant
Inference-based Modelling in Population and Systems Biology
群体和系统生物学中基于推理的建模
- 批准号:
BB/G007934/1 - 财政年份:2009
- 资助金额:
$ 39.37万 - 项目类别:
Research Grant
Developing methods for inferring regulatory mechanisms from intact systems: a neisseria case study
开发从完整系统推断调控机制的方法:奈瑟菌案例研究
- 批准号:
BB/G001863/1 - 财政年份:2008
- 资助金额:
$ 39.37万 - 项目类别:
Research Grant
Systems approaches to biological research training grant
生物研究培训补助金的系统方法
- 批准号:
BB/F52902X/1 - 财政年份:2008
- 资助金额:
$ 39.37万 - 项目类别:
Training Grant
A rational in-silico and experimental approach to mapping interactomes applied to Candida glabrata
一种合理的计算机模拟和实验方法来绘制应用于光滑念珠菌的相互作用组图
- 批准号:
BB/F013566/1 - 财政年份:2008
- 资助金额:
$ 39.37万 - 项目类别:
Research Grant
Predicting properties of biological networks from noisy and incomplete data
从嘈杂和不完整的数据预测生物网络的特性
- 批准号:
BB/E01612X/1 - 财政年份:2007
- 资助金额:
$ 39.37万 - 项目类别:
Research Grant
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PAML 5:用于系统基因组学的友好且强大的生物信息学资源
- 批准号:
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2321666 - 财政年份:2024
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规划方案:CREST生物信息学中心
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合作研究:IIBR:创新:生物信息学:连接化学和生物空间:属性控制分子生成的深度学习和实验
- 批准号:
2318829 - 财政年份:2023
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$ 39.37万 - 项目类别:
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Building a Bioinformatics Ecosystem for Agri-Ecologists
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