Workshop: Community Building for Long Non-Coding RNA; Fall/Summer; Morgantown, WVA; Houston, TX
Workshop: Community Building for Long Non-Coding RNA; Fall/Summer; Morgantown, WVA; Houston, TX
批准号:
1747788
负责人:
Donald Adjeroh
金额:
$10.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-01 至 2024-07-31
中文摘要
最近发现人类基因组被广泛转录,这改变了我们对基因调控和基因功能的传统看法。这种转录的重要部分涉及长非编码RNA(LncRNA)。已知LncRNA作为RNA基因起作用,并且参与各种生物和细胞过程,如遗传印记、染色质重塑、植物和动物中的基因调控以及脊椎动物中的胚胎发育。毫不奇怪,LncRNA与几种疑难疾病有关,如癌症和糖尿病。虽然一些单独的LncRNA已经得到了很好的研究,但它们的性质和功能仍然没有完全了解。已查明的有30 000多人,这一数字每天都在增加。因此,我们在湿实验室中实验研究单个LncRNA及其功能的能力远远超过了可用数据的绝对数量和多样性,以及数据生成的增长速度。迫切需要计算工具来简化表征已知LncRNA以确定其功能关联的过程。然而,自动化方法无疑会产生大量关于给定lncRNA潜在功能的假设,远远超出任何单个湿实验室的验证能力。这需要一个协作的社区驱动的方法,来自不同领域的研究人员将走到一起,以解决一个关键问题。我们将组织几次研讨会,将有兴趣优先考虑重要问题的研究人员聚集在一起,以进一步推进该领域的研究。这些研讨会活动的目的是建立一个以LncRNA功能注释问题为中心的多元化学者社区,包括LncRNA检测和数据生成,以及LncRNA命名的标准化。这样的社区将汇集来自学术界、政府、工业(特别是医疗保健和制药行业)的计算科学家、分子和结构生物学家、医学科学家和其他人,专注于我们对LncRNA及其功能的理解的关键问题。通过创建讨论和活动成果的公共论坛,这些研讨会将提高人们对研究lncRNA生物学的关键问题和挑战,其功能以及注释和命名标准化等信息共享挑战的认识。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。
英文摘要
The recent discovery that the human genome is extensively transcribed is changing our traditional view of gene regulation, and gene function. A significant part of this transcription involves long non-coding RNAs (LncRNAs). LncRNAs are known to function as RNA genes and are involved in various biological and cellular processes, such as genetic imprinting, chromatin remodeling, gene regulation in both plants and animals, and embryonic development in vertebrates. Not surprisingly, LncRNAs have been implicated in several difficult diseases, such as cancer, and diabetes. Although some individual LncRNAs have been well studied, their nature and functions are still not completely understood. Over 30,000 have been identified, with this number increasing daily. Thus, our ability to experimentally study individual LncRNAs and their functions in the wet-lab is far outpaced by the sheer volume and diversity of available data, and the increasing rate at which the data is being generated. There is an acute need for computational tools to simplify the process of characterizing the known LncRNAs to determine their functional associations. Yet, automated methods will undoubtedly generate an enormous number of hypotheses on the potential functions of a given lncRNA, far beyond the capacity of any individual wet laboratory to verify. This calls for a collaborative community-driven approach, where researchers from various fields will come together to address a critical problem. Several workshops will be organized, bringing together researchers interested in prioritizing issues of importance to furthering research in this area.The aim of these workshop activities is to build a diverse community of scholars centered on the problem of functional annotation of LncRNAs, including LncRNA detection and data generation, and standardization of lncRNA nomenclature. Such a community will bring together computational scientists, molecular and structural biologists, medical scientists, and others, from academia,government, industry (especially healthcare and pharmaceutical industry), to focus on key issues in our improved understanding of LncRNAs and their functions. By creating public forums of the outcomes of discussions and activities, these workshops will raise awareness on key problems and challenges in studying the biology of in LncRNAs, their functions, and information sharing challenges such as annotation, and nomenclature standardization. A highly diverse community of researchers will be encouraged to participate, who could provide a novel perspective to these problems.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.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
A Deep Learning Approach to LncRNA Subcellular Localization Using Inexact q-mers
使用不精确 q-mers 进行 LncRNA 亚细胞定位的深度学习方法
DOI:
10.1109/bibm52615.2021.9669409
发表时间:
2021
期刊:
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM
影响因子:
--
作者:
[Yi, Weijun, Adjeroh, Donald A.]
通讯作者:
Adjeroh, Donald A.
DOI:
10.1109/bibm49941.2020.9313445
发表时间:
2020-12
期刊:
2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
影响因子:
--
作者:
[J. Miller;D. Adjeroh]
通讯作者:
J. Miller;D. Adjeroh
Collaborative Research: CISE-MSI: DP: III: Information Integration and Association Pattern Discovery in Precision Phenomics
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批准号:2318708
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2023
-
负责人:Donald Adjeroh
-
依托单位:
NRT-HDR: Bridges in Digital Health
-
批准号:2125872
-
项目类别:Standard Grant
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资助金额:$300.0万
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财政年份:2021
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负责人:Donald Adjeroh
-
依托单位:
RII Track 2 FEC: Multi-Scale Integrative Approach to Digital Health: Collaborative Research and Education in Smart Health in West Virginia and Arkansas
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批准号:1920920
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项目类别:Cooperative Agreement
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资助金额:$400.0万
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财政年份:2019
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负责人:Donald Adjeroh
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依托单位:
Spokes: MEDIUM: SOUTH: Collaborative: Integrating Biological Big Data Research into Student Training and Education
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批准号:1761792
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项目类别:Standard Grant
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资助金额:$15.0万
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财政年份:2018
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负责人:Donald Adjeroh
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依托单位:
III: Small: Collaborative Research: Social Media Based Analysis of Adverse Drug Events: User Modeling, Signal Reliability, and Signal Validation
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批准号:1816005
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项目类别:Continuing Grant
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资助金额:$27.0万
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财政年份:2018
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负责人:Donald Adjeroh
-
依托单位:
SBP 2015 Outreach Efforts to Increase Diversity and Participation of Minorities
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批准号:1523458
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项目类别:Standard Grant
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资助金额:$1.98万
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财政年份:2015
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负责人:Donald Adjeroh
-
依托单位:
EAGER: Collaborative Research: CRUFS: A Unified Framework for Social Media Analysis of Adverse Drug Events
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批准号:1552860
-
项目类别:Standard Grant
-
资助金额:$14.0万
-
财政年份:2015
-
负责人:Donald Adjeroh
-
依托单位:
SBP 2012 Outreach Efforts to Increase Diversity and Participation of Minorities
-
批准号:1225981
-
项目类别:Standard Grant
-
资助金额:$1.66万
-
财政年份:2012
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负责人:Donald Adjeroh
-
依托单位:
EAGER: Collaborative Research: Computational Public Drug Surveillance
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批准号:1236983
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项目类别:Standard Grant
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资助金额:$8.0万
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财政年份:2012
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负责人:Donald Adjeroh
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依托单位:
U.S.-New Zealand and Australia Collaboration on Research for Data Compression
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批准号:0331896
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项目类别:Standard Grant
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资助金额:$0.78万
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财政年份:2004
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负责人:Donald Adjeroh
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依托单位:
ITR Collaborative Research: Compressed Search and Retrieval for Very Large Text and Image Repositories
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批准号:0312484
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项目类别:Standard Grant
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资助金额:$0.0万
-
财政年份:2003
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负责人:Donald Adjeroh
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依托单位:
Collaborative: Compressed Domain Search for Text and Images by Sorted Contexts
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批准号:0228370
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项目类别:Continuing Grant
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资助金额:$9.0万
-
财政年份:2002
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负责人:Donald Adjeroh
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依托单位:
海外基金