Conference: Workshop on Predictive Modeling in Biology and Medicine

会议：生物学和医学预测模型研讨会

• 批准号: 2331170
• 负责人: Mark Alber
• 金额: $ 3.01万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-11-15 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2331170&HistoricalAwards=false
• 关键词: Conference; Workshop; Predictive; Modeling; Biology

The conference on "Predictive Modeling in Biology and Medicine" is to be held on November 17-19 (Friday-Sunday), 2023, at the University of California, Riverside (UCR) (https://icqmb.ucr.edu/predictive-modeling-biology-and-medicine-conference). The conference will bring together researchers at different stages of their career and with diverse backgrounds to exchange ideas and novel approaches as well as to promote interdisciplinary collaborations on predictive modeling in biology and medicine. By bringing together researchers from different disciplines and at different career stages, the aim of the conference is to promote communication and collaboration among researchers with diverse backgrounds, as well as to help the new generation of researchers, especially those from underrepresented groups, to establish their own research programs. The conference includes a workshop with a special focus on promoting Diversity, Equity, and Inclusion (DEI) in mathematical and computational biology and, more broadly, in the mathematical and scientific community. The first day of the conference will include a workshop consisting of two plenary talks and two panel discussions. The first is concerned with promoting DEI in education and research, and the second panel will focus on career paths in mathematical and computational biology so that the participants can discuss and plan concrete actions to cultivate an inclusive and welcoming research community environment. In the last two decades, a variety of multi-scale mathematical and computational models have been developed and widely applied to better understand biological systems. Recently, large amounts of data generated from biological experiments as well as clinical data provided new opportunities for developing novel data-driven modeling approaches combined with machine learning algorithms to gain novel insights into biology and medicine. The conference will focus on three main research topics: 1. Multi-scale modeling in biology and medicine, 2. Data driven and machine learning methodologies in biology and medicine, 3. Predictive modeling in biology and medicine. A broad spectrum of speakers, some of the leading experts in the field, with diverse backgrounds will share their experiences and encourage the next generation of researchers. Two poster sessions with more than 50 posters will promote research of graduate students and postdoctoral associates. A large number of graduate students and postdoctoral associates from underrepresented groups, including those from UCR, will participate in the conference, which will allow them to learn the most recent research approaches in the field, and provide them with advice and resources to successfully pursue Ph.D. degrees and seek career opportunities in STEM fields working in academia, industry, health care or for the government.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.

“生物学和医学预测建模”会议将于2023年11月17日至19日（星期五至星期日）在加州大学滨江分校（UCR）举行（https：//icqmb.ucr.edu/predictive-modeling-biology-and-medicine-conference）。 该会议将汇集研究人员在他们的职业生涯的不同阶段，并与不同的背景，交流思想和新的方法，以及促进跨学科的合作，在生物学和医学预测建模。通过汇集来自不同学科和不同职业阶段的研究人员，会议的目的是促进具有不同背景的研究人员之间的交流与合作，并帮助新一代研究人员，特别是那些来自代表性不足的群体的研究人员，建立自己的研究计划。 会议包括一个研讨会，特别关注促进数学和计算生物学以及更广泛的数学和科学界的多样性，公平性和包容性（DEI）。 会议的第一天将包括一个由两个全体会议和两个小组讨论组成的研讨会。 第一个是关于在教育和研究中促进DEI，第二个小组将专注于数学和计算生物学的职业道路，以便参与者可以讨论和计划具体行动，以培养包容和欢迎的研究社区环境。在过去的二十年中，各种多尺度数学和计算模型已经被开发并广泛应用于更好地理解生物系统。最近，从生物实验以及临床数据中产生的大量数据为开发新的数据驱动建模方法提供了新的机会，这些方法与机器学习算法相结合，以获得对生物学和医学的新见解。会议将集中讨论三个主要研究课题：1。生物学和医学中的多尺度建模，2。生物学和医学中的数据驱动和机器学习方法，3。生物学和医学中的预测建模。一个广泛的发言者，在该领域的一些领先的专家，具有不同的背景将分享他们的经验，并鼓励下一代的研究人员。 两次海报会议，50多张海报将促进研究生和博士后的研究。 来自代表性不足群体的大量研究生和博士后研究员，包括来自UCR的研究生和博士后研究员，将参加会议，这将使他们能够学习该领域最新的研究方法，并为他们提供成功攻读博士学位的建议和资源。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。