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NSF Student Travel Grant for 2019 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC)

NSF Student Travel Grant for 2019 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC)
NSF 学生旅费资助 2019 年计算网络生物学国际研讨会:建模、分析和控制 (CNB-MAC)
批准号:
1937825
负责人:
Ranadip Pal
金额:
$1.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-01 至 2020-07-31

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中文摘要
翻译
第六届计算网络生物学:建模、分析和控制国际研讨会(CNB-MAC 2019)将于2019年9月7日在纽约尼亚加拉瀑布举行。研讨会将与第十届ACM生物信息学、计算生物学和健康信息学会议(ACM-BCB 2019)一起举办。与ACM-BCB的持续合作将提高研讨会的知名度,并吸引来自工程学、计算机科学、统计学、生物学和医学等不同学科的研究人员。CNB-MAC 2019旨在提供一个国际科学论坛,用于展示计算网络生物学的最新进展,并提高人们对严格数学建模在将大生物医学数据转化为可重复和有意义的科学知识方面的重要性的认识。CNB-MAC最重要的使命之一是在新兴的计算网络生物学领域培养下一代科学家。该研讨会旨在提供主题演讲、教程和研究讲座,为参与的研究生和博士后研究人员,特别是女性和少数族裔提供未来的研究方向。CNB-MAC 2019将提供旅行奖励,鼓励研究生参加研讨会并展示他们的最新研究成果。具体地说,研讨会计划将至少15%的奖项分配给女性和少数族裔学生,以鼓励她们参与。下一代高通量剖析技术使人们能够更系统和更全面地研究生命系统。网络模型在理解支配生物系统的复杂相互作用以及它们与外部环境的相互作用方面起着至关重要的作用。CNB-MAC 2019的主要重点将是研究生物网络的严格数学模型和高效计算方法,大规模OMICS数据的综合分析,为研究人类-微生物-环境相互作用开发数学模型,以及与计算网络生物学相关的其他主题。作为对ACM-BCB 2019关于大数据的信息学工具和学习算法的关注的补充,CNB-MAC的主要关注点是计算网络生物学,涉及不同条件下生物系统的建模、分析和控制,以及大规模OMICS数据的面向系统的分析,目的是为展示该领域的最新进展提供一个充满活力的国际科学论坛。这项提议寻求为八名研究生提供旅行支持,以参加CNB-MAC 2019,展示他们的最新研究成果,并积极参与该领域的其他研究人员的互动。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The Sixth International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC 2019) will be held in Niagara Falls, New York, September 7, 2019. The workshop will be organized in conjunction with the 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2019). The continuing partnership with ACM-BCB will enhance the visibility of the workshop and attract researchers from various disciplines across engineering, computer science, statistics, biology, and medicine. CNB-MAC 2019 aims to provide an international scientific forum for presenting recent advances in computational network biology and boost the awareness of the importance of rigorous mathematical modeling in transforming big biomedical data into reproducible and meaningful scientific knowledge. One of the missions of CNB-MAC that is of foremost importance is to foster next-generation scientists in the emerging field of computational network biology. The workshop aims to offer keynote, tutorial, and research talks to provide future research directions for participating graduate students and post-doctoral researchers, especially women and minorities. CNB-MAC 2019 will provide travel awards to encourage graduate students to participate in the workshop and present their latest research findings. Specifically, the workshop plans to allocate a minimum of 15% of the awards to female and minority students to encourage their participation.Next-generation high-throughput profiling technologies have enabled more systematic and comprehensive studies of living systems. Network models play crucial roles in understanding the complex interactions that govern biological systems, and their interactions with the external environment. The main emphasis of CNB-MAC 2019 will be on rigorous mathematical models and efficient computational approaches for studying biological networks, integrative analysis of large-scale OMICS data, developing mathematical models for the investigation of human-microbiome-environment interactions, and other topics relevant to computational network biology. Complementary to the focus of ACM-BCB 2019 on informatics tools and learning algorithms for big biomedical data, CNB-MAC's main focus is on computational network biology that involves modeling, analysis, and control of biological systems under different conditions, and system-oriented analysis of large-scale OMICS data with the goal of providing a dynamic international scientific forum for presenting the latest advances in the field. This proposal seeks travel support for eight graduate students to attend CNB-MAC 2019, present their latest research findings, and actively engage in interactions with other researchers in the field.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Collaborative Research: FET: Small: Machine Learning Models for Function-on-Function Regression
  • 批准号:
    2007903
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.0万
  • 财政年份:
    2020
  • 负责人:
    Ranadip Pal
  • 依托单位:
NSF Student Travel Grant for 2018 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC)
  • 批准号:
    1841780
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.0万
  • 财政年份:
    2018
  • 负责人:
    Ranadip Pal
  • 依托单位:
International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC 2017)
  • 批准号:
    1743820
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.0万
  • 财政年份:
    2017
  • 负责人:
    Ranadip Pal
  • 依托单位:
PFI:AIR - TT: Design of functionally-tested, genomics-informed personalized cancer therapy drug treatment plans
  • 批准号:
    1500234
  • 项目类别:
    Standard Grant
  • 资助金额:
    $19.44万
  • 财政年份:
    2015
  • 负责人:
    Ranadip Pal
  • 依托单位:
海外基金