权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Computational and mathematical modeling of biomedical systems

生物医学系统的计算和数学建模

基本信息

批准号：
10629316
负责人：
Timothy W. Secomb
金额：
$ 30.17万
依托单位：
UNIVERSITY OF ARIZONA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10629316
关键词：
Computer Models System mathematical model

项目摘要

This program prepares scientists for research careers in the computational and mathematical modeling of medically significant biological systems through interdisciplinary training at the predoctoral level. Noted for its well-established system of interdisciplinary graduate programs and for its tradition of collaborations across departmental boundaries, the University of Arizona provides a highly suitable environment for such training. Fifteen training faculty with appointments in multiple departments and interdisciplinary graduate programs provide strength in five broad areas: bioinformatics; molecular dynamics; cellular processes; physiology and pathophysiology; biostatistics and stochastic processes. Students will be drawn from multiple graduate programs in mathematical and life sciences, including the programs in Applied Mathematics and in Biochemistry and Molecular & Cellular Biology. In most cases, students will receive two years of support from this program, starting in their second or third year of graduate training. Trainees will pursue the coursework requirements of their own graduate programs and, in addition, take graduate courses in mathematical modeling and in bioinformatics, which are tailored to the trainees' needs and take into account their diverse scientific backgrounds. All trainees will take part in a weekly Quantitative Biology Colloquium that has been running continuously for more than twenty years. This colloquium includes presentations by students, faculty and visiting speakers, and promotes dialog between trainees and faculty with primarily mathematical or computational backgrounds and those with strong biological training. It will include components explicitly devoted to training in responsible conduct of research, methods for enhancing reproducibility, and career development including preparation for a range of careers in biomedical research. Trainees will carry out their doctoral research with advisors whose research, whether theoretical or experimental, emphasizes application of theoretical approaches to biomedical problems. Trainees participating in this program will not only receive research training in relevant areas, but, equally importantly, will develop the ability to communicate and collaborate across traditional disciplinary boundaries and to work with researchers with complementary expertise. Researchers with such skills are critically needed in many areas of biomedical science in which sophisticated theoretical approaches are necessary in order to achieve further progress.

该计划为科学家在计算和数学领域的研究职业做好准备。通过跨学科培训建立具有医学意义的生物系统模型博士前水平。以其完善的跨学科研究生课程体系而闻名亚利桑那大学有着跨部门合作的传统，为这种训练提供了非常合适的环境。15名培训教师，在多个部门和跨学科的研究生课程任命提供实力在五个广泛的领域：生物信息学;分子动力学;细胞过程;生理学和病理生理学;生物统计学和随机过程。学生将从多个数学和生命科学的研究生课程，包括应用程序数学和生物化学和分子与细胞生物学。在大多数情况下，学生将从研究生的第二年或第三年开始，接受该计划为期两年的支持训练学员将追求自己的研究生课程的课程要求，此外，还应修读数学建模和生物信息学研究生课程，这些培训是根据受训者的需要量身定制的，并考虑到他们不同的科学背景。所有学员将参加每周一次的定量生物学研讨会，连续二十多年。本次座谈会包括学生的演讲，教师和客座演讲者，并促进学员和教师之间的对话，主要是数学或计算背景和那些有很强的生物训练。它将包括明确致力于负责任地进行研究、方法提高再现性和职业发展，包括为一系列从事生物医学研究。学员将与顾问一起进行博士研究他的研究，无论是理论的还是实验的，都强调理论的应用。解决生物医学问题。参加该计划的学员不仅将获得在相关领域的研究培训，但同样重要的是，将发展能力，跨传统学科界限进行沟通和协作，具有互补专业知识的研究人员。具有这种技能的研究人员是迫切需要的，生物医学科学的许多领域，其中复杂的理论方法是必要的以便取得进一步的进展。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip.

DOI：
10.1016/j.bios.2022.114192
发表时间：
2022-07-01
期刊：
Biosensors & bioelectronics
影响因子：
12.6
作者：
Akarapipad P;Kaarj K;Breshears LE;Sosnowski K;Baker J;Nguyen BT;Eades C;Uhrlaub JL;Quirk G;Nikolich-Žugich J;Worobey M;Yoon JY
通讯作者：
Yoon JY

Aedes-AI: Neural network models of mosquito abundance.

DOI：
10.1371/journal.pcbi.1009467
发表时间：
2021-11
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Kinney AC;Current S;Lega J
通讯作者：
Lega J

A Hansel & Gretel breadcrumb-style dynamically deployed communication network paradigm using mesh topology for planetary subsurface exploration.

汉塞尔

DOI：
10.1016/j.asr.2023.02.012
发表时间：
2023
期刊：
Advances in space research : the official journal of the Committee on Space Research (COSPAR)
影响因子：
0
作者：
Fink,Wolfgang;Fuhrman,Connor;Zuniga,AndresNuncio;Tarbell,Mark
通讯作者：
Tarbell,Mark

Sensitive, smartphone-based SARS-CoV-2 detection from clinical saline gargle samples.

DOI：
10.1093/pnasnexus/pgac028
发表时间：
2022-03
期刊：
PNAS NEXUS
影响因子：
0
作者：
Breshears, Lane E.;Nguyen, Brandon T.;Akarapipad, Patarajarin;Sosnowski, Katelyn;Kaarj, Kattika;Quirk, Grace;Uhrlaub, Jennifer L.;Nikolich-Zugich, Janko;Worobey, Michael;Yoon, Jeong-Yeol
通讯作者：
Yoon, Jeong-Yeol

Combined flat-field and frequency filter approach to correcting artifacts of multichannel two-photon microscopy.