英国论文代写|BIRMINGHAM UNIVERSITY MSC DISSERTATION |Analysis of the networks controlling life and death of cancer cells

随着经济的发展,越来越多的中国人选择到英国留学,在获取更高的知识水平和感受雾都美好风景的同时,每学期如约而至的论文却成了很多人心中的痛。也难怪很多留学生会选择英国论文代写

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MSc MORSE/Financial Engineering/Mathematical Finance

A Bayesian Framework for Sensor Placements
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Alternating Direction Method of Multipliers for Big Data
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Conic Optimization with Application to Integer Programming
Robust Linear Programming
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Travelling salesman problem
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Public key cryptography based on Max-Plus Algebra
Portfolio Allocation using Mean-Variance Optimization
Credit Scoring Algorithms and Analysis
Sentiment Analysis of Social Media Posts
Predicting Results in a Football Match
Prediction of Heart Failure using Learning Methods
Modelling high-fidelity clinical data using statistical learning methods
Risk factor analysis using statistical learning methods
How weather influence England Acute Care Hospitals, Emergency Department admissions and ICU admissions
Understanding Uncertainties and market volatilities
Estimating the reproduction number of COVID-19 in the UK
Microgravity Data Postprocessing using Wavelets

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天气如何影响英格兰急诊医院、急诊室收治和ICU收治的情况
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估计英国COVID-19的繁殖数量
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英国论文代写|BIRMINGHAM UNIVERSITY MSC DISSERTATION |Analysis of the networks controlling life and death of cancer cells

英国论文代写|Birmingham University MSc Dissertation |Analysis of the networks controlling life and death of cancer cells

processing of food and generation of energy to live, grow and divide. Such networks also control cell death, which may, for example, be initiated, in response to limited oxygen or food, or to cell damage. Cancer cells are characterised by their advanced capabilities to survive and proliferate in adverse cellular environments, giving them growth advantages compared to healthy tissue. They are also characterised by increased resistance to cell death. Therefore, a lot of research has focused on how the cellular networks within cancer cells is reprogrammed. Traditionally most of the experimental and modelling research focused on the analysis of the networks within individual cancer cells, treating them as isolated closed systems. However, we now know that cancer cells will behave very differently in different cellular environments. These different environments are characterised by the presence of healthy cells, including immune cells or stromal cells, but also by physical variables including mechanical resistance of the tissue, or the local oxygen concentrations. New experimental evidence shows that some healthy cells can produce nutrients that are taken up by cancer cells. Therefore, the molecular crosstalk with healthy cells can help to fuel the growth of these cancer cells. In this project, you will develop mathematical models to uncover the crosstalk of cancer and healthy cells. The models will be initially set up with experimental data from the lab of Prof Dan Tennant (https://www.tennantlab.uk/). Then, you will make new predictions to identify key molecules that facilitate the crosstalk of these cells. This work may therefore identify new drug targets that can inhibit the crosstalk and therefore limit cancer growth, or, in the best case, reprogram cancer cells towards cell death. By working closely with the experimentalists, you will ensure the developed models are realistic and can be validated by new experiments. Methods: There is some flexibility on which methods can be applied, depending on the student’s interests, It may involve differential equations, dynamical systems, metabolic flux analysis, optimisation or machine learning.

英国论文代写|控制癌细胞生与死的网络分析

加工食物和产生能量来生存、成长和分裂。这种网络还控制细胞死亡,例如,响应有限的氧气或食物,或细胞损伤,可以启动细胞死亡。癌细胞的特征在于其在不利的细胞环境中生存和增殖的先进能力,与健康组织相比,它们具有生长优势。它们的特征还在于对细胞死亡的抵抗力增加。因此,许多研究都集中在癌细胞内的细胞网络如何被重新编程。传统上,大多数实验和建模研究都集中在分析单个癌细胞内的网络,将它们视为孤立的封闭系统。然而,我们现在知道癌细胞在不同的细胞环境中会表现得非常不同。这些不同环境的特点是存在健康细胞,包括免疫细胞或基质细胞,还包括物理变量,包括组织的机械阻力或局部氧浓度。新的实验证据表明,一些健康细胞可以产生被癌细胞吸收的营养物质。因此,与健康细胞的分子串扰有助于促进这些癌细胞的生长。在这个项目中,您将开发数学模型来揭示癌症和健康细胞的串扰。这些模型最初将使用 Dan Tennant 教授实验室 (https://www.tennantlab.uk/) 的实验数据建立。然后,您将做出新的预测,以确定促进这些细胞串扰的关键分子。因此,这项工作可能会确定可以抑制串扰并因此限制癌症生长的新药物靶点,或者在最好的情况下,将癌细胞重新编程为细胞死亡。通过与实验人员密切合作,您将确保开发的模型是现实的,并且可以通过新的实验进行验证。方法:根据学生的兴趣,可以应用哪些方法具有一定的灵活性,它可能涉及微分方程、动力系统、代谢通量分析、优化或机器学习。

英国论文代写|BIRMINGHAM UNIVERSITY MSC DISSERTATION |Analysis of the networks controlling life and death of cancer cells

英国论文代写

英国论文代写|Analysis of the networks controlling life and death of cancer cells选题导师介绍

Dr Sovan Sarkar is a Birmingham Fellow at the University of Birmingham, and holds the distinction of Former Fellow for life at Hughes Hall, University of Cambridge. He is also involved in setting up academic and research collaborations with India. His laboratory studies the biological process of autophagy, which is an intracellular degradation pathway essential for cellular survival. Using human embryonic stem cells (hESCs) and disease-specific human induced pluripotent stem cells (hiPSCs), he works on the regulation and therapeutic application of autophagy in relation to human physiology and diseases. He aims to develop a pipeline originating from basic biology to drug discovery, and potentially translate the findings for biomedical applications. 

His research has been funded by grants from the Wellcome Trust, LifeArc and UKIERI (UK-India Education and Research Initiative), amongst others. He has also hosted researchers with Newton Bhabha PhD Placement Award, Rutherford Fellowship, University of Birmingham India Institute Visiting Fellowship and University of Birmingham Brazil Visiting Fellowship, amongst others.

Sovan has made several contributions during his tenure at University of Cambridge towards the identification of mTOR-independent signalling pathways and small molecules modulating autophagy. These findings not only provided mechanistic insights into the cell biology of this process, but also generated potential therapeutic candidates for diverse human diseases, including a number of neurodegenerative diseases, where upregulating autophagy acts as a protective pathway.

His work at Whitehead Institute in Massachusetts Institute of Technology involves the fundamental aspects of autophagy in hESCs, and its deregulation in hiPSC-based disease models of neurodegenerative and lysosomal storage disorders. He has authored more than 50 scientific publications, which have collectively received ~ 12000 citations, and have generated a number of patents and research features. His notable awards include Gates Cambridge Scholarship, Hughes Hall Research Fellowship, Biochemical Society Early Career Research Award in Cell Biology and Birmingham Fellowship.

Dr Sarkar is interested in supervising Doctoral and Masters research students in the following areas: 

  • The role and regulation of autophagy in human embryonic stem cells and in differentiated adult cell types.
  • The molecular mechanisms of mammalian autophagy in its role in cellular homeostasis, neurodegeneration, aging and metabolism.
  • Mechanisms of cellular degeneration and proteostasis in disease-relevant human cell types derived from disease-specific induced pluripotent stem cells.
  • Drug discovery in human disease-affected cell types derived from disease-specific induced pluripotent stem cells. 

英国论文代写|Analysis of the networks controlling life and death of cancer cells选题参考文献

References:

See Google Scholar Citations for full list of all publications, citations and h-index. See Sovan Sarkar lab website for full details of all publications.

Trehalose limits opportunistic mycobacterial survival during HIV co-infection by reversing HIV-mediated autophagy block. (2021) Sharma V., Makhdoomi M., Singh L., Kumar P., Khan N., Singh S., Verma H.N., Luthra K., Sarkar S. and Kumar D. Autophagy 17(2): 476-495.

Autophagy promotes cell and organismal survival by maintaining NAD(H) pools. (2020) Sedlackova L., Otten E.G., Scialo F., Shapira D., Kataura T., Carroll B., Seranova E., Rabanal-Ruiz Y., Kelly G., Stefanatos R., Nelson G., Acharjee A., Kenneth N., Trushin S., Zhang T., Bascom C.C., Tasseff R., Isfort R.J., Oblong J.E., Trushina E., Imoto M., Saiki S., Lazarou M., Chronakis M.P., Maddocks O.D.K., Sarkar S., Sanz A. and Korolchuk V.I.
BioRxiv [pre-print server for biology] doi: https://doi.org/10.1101/2020.01.31.928424. Joint corresponding authors 

Human induced pluripotent stem cell models of neurodegenerative disorders for studying the biomedical implications of autophagy. (2020) Seranova E., Palhegyi A.M., Verma S., Dimova S., Lasry R., Naama M., Sun C., Barrett T., Rosenstock T.R., Kumar D., Cohen M.A., Buganim Y. and Sarkar S. Journal of Molecular Biology 432(8): 2754-2798. 

Autophagy in rare (non-lysosomal) neurodegenerative diseases. (2020) Zatyka M., Sarkar S. and Barrett T. Journal of Molecular Biology 432(8): 2735-2753. 

英国论文代写|Birmingham University MSc Dissertation |Trophic coherence and ecosystem stability

英国论文代写|Trophic coherence and ecosystem stability 请认准UprivateTA™. UprivateTA™为您的留学生涯保驾护航。

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离散数学代写

离散数学研究基于离散空间而不是连续的数学结构。 与連續变化的实数不同,离散数学的研究对象——例如整数、图和数学逻辑中的命题——不是連續变化的,而是拥有不等、分立的值。 因此离散数学不包含微积分和分析等「连续数学」的内容。 离散数学在计算领域有广泛的应用,例如密码学、编码理论、 形式方法, 语言理论, 可计算性, 人工智能, 理论 数据库和软件的可靠性。 离散数学的重点是理论和应用,而不是为了数学本身而研究数学。 一切算法的基础都是离散数学一切加密的理论基础都是离散数学 编程时候很多奇怪的小技巧(特别是所有和位计算相关的东西)核心也是离散数学 其他相关科目课程代写:组合学Combinatorics集合论Set Theory概率论Probability组合生物学Combinatorial Biology组合化学Combinatorial Chemistry组合数据分析Combinatorial Data Analysis my-assignmentexpert愿做同学们坚强的后盾,助同学们顺利完成学业,同学们如果在学业上遇到任何问题,请联系my-assignmentexpert™,我们随时为您服务!



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如果你也在 怎样金融数学Financial Mathematics这个学科遇到相关的难题,请随时右上角联系我们的24/7代写客服。金融数学Financial Mathematics是将数学方法应用于金融问题。(有时使用的同等名称是定量金融、金融工程、数学金融和计算金融)。它借鉴了概率、统计、随机过程和经济理论的工具。传统上,投资银行、商业银行、对冲基金、保险公司、公司财务部和监管机构将金融数学的方法应用于诸如衍生证券估值、投资组合结构、风险管理和情景模拟等问题。依赖商品的行业(如能源、制造业)也使用金融数学。 定量分析为金融市场和投资过程带来了效率和严谨性,在监管方面也变得越来越重要。

我们提供的金融数学Financial Mathematics及其相关学科的代写,服务范围广, 其中包括但不限于:

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微观经济学代写

经济学Economics是研究商品和服务的生产、分配和消费的社会科学。 经济学Economics的重点是经济主体的行为和互动,以及经济如何运作。

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什么是计量经济学?
计量经济学是统计学和数学模型的定量应用,使用数据来发展理论或测试经济学中的现有假设,并根据历史数据预测未来趋势。它对现实世界的数据进行统计试验,然后将结果与被测试的理论进行比较和对比。

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MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中,其中问题和解决方案以熟悉的数学符号表示。典型用途包括:数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发,包括图形用户界面构建MATLAB 是一个交互式系统,其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题,尤其是那些具有矩阵和向量公式的问题,而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问,这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展,得到了许多用户的投入。在大学环境中,它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域,MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要,工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数(M 文件)的综合集合,可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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