ITR: Computational Techniques for Applied Bioinformatics

ITR:应用生物信息学计算技术

基本信息

  • 批准号:
    0085910
  • 负责人:
  • 金额:
    $ 48.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2000
  • 资助国家:
    美国
  • 起止时间:
    2000-09-01 至 2004-08-31
  • 项目状态:
    已结题

项目摘要

This award provides support for a collaborative project involving two computer scientists and a plant geneticist who will develop new methods, efficient algorithms, and software tools for several important problems in the field of bioinformatics. This supported work includes research into computational paradigms such as quartet methods, interactive systems, and approximation algorithms as applied to the evolutionary analysis of gene sequences, gene duplication, and horizontal transfer events in the genomes of chloroplasts, a DNA-containing organelle found in all plants. Additional studies will examine the information content of genomes by improving and testing a recently developed sequence entropy estimator and a distance metric for genomic sequences. Work in this area will include the application of the improved methods to sequence data from the genomes of mitochondria, viruses, chloroplasts and bacteria. Other efforts will address the important problem of simultaneous multiple sequence alignment and evolutionary tree reconstruction. The multiple sequence alignment approaches to be developed are based on the use of conserved blocks that have few or no gaps, and multiple alignments within a constant band. Work in a fourth area will develop efficient algorithms for computing short and long interspersed nuclear elements (SINES and LINES) in genomic sequences of lengths up to billions of nucleotides. Because of the large amounts of data that must be analyzed, this will require the development or adaptation of appropriate external memory algorithms. Biological, biomedical and pharmaceutical research is undergoing a major revolution as new analytical technologies produce unprecedented amounts of genetic data. The exploration of this information is critically dependent upon the development of advanced computational and software techniques for data analysis, storage and retrieval. From this dependency, a new interdisciplinary research field, bioinformatics (or computational molecular biology) has emerged in recent years. The work supported through this award is expected to make both fundamental and applied contributions to the field. The fundamental research will explore and explicate new ideas and methods for solving algorithmic problems in bioinformatics and the applied research will involve the development and evaluation of software tools in the practice of plant genomics. Although the efforts are aimed at improving the understanding of the evolution of chloroplast genomes, the approaches should be readily extensible to analysis of all other genomes.
该奖项为一个合作项目提供支持,该项目涉及两名计算机科学家和一名植物遗传学家,他们将为生物信息学领域的几个重要问题开发新方法,高效算法和软件工具。这项支持的工作包括研究计算范式,如四重方法,交互式系统和近似算法,应用于基因序列,基因复制和叶绿体基因组中的水平转移事件的进化分析,叶绿体是一种在所有植物中发现的含DNA的细胞器。 其他研究将通过改进和测试最近开发的序列熵估计和基因组序列的距离度量来检查基因组的信息内容。 这一领域的工作将包括应用改进的方法对线粒体、病毒、叶绿体和细菌的基因组数据进行测序。其他努力将解决同时多序列比对和进化树重建的重要问题。待开发的多序列比对方法是基于使用具有很少或没有缺口的保守块,以及恒定带内的多个比对。第四个领域的工作将开发有效的算法,用于计算长度高达数十亿个核苷酸的基因组序列中的短和长散布的核元素(SINES和LINES)。由于必须分析大量数据,这将需要开发或调整适当的外部存储器算法。生物、生物医学和制药研究正在经历一场重大革命,因为新的分析技术产生了前所未有的大量遗传数据。对这些信息的探索在很大程度上取决于用于数据分析、存储和检索的先进计算和软件技术的发展。从这种依赖性出发,近年来出现了一个新的跨学科研究领域,即生物信息学(或计算分子生物学)。通过该奖项支持的工作预计将为该领域做出基础和应用贡献。基础研究将探索和阐明解决生物信息学中算法问题的新思想和方法,应用研究将涉及植物基因组学实践中软件工具的开发和评估。虽然这些努力旨在提高对叶绿体基因组进化的理解,但这些方法应该很容易扩展到所有其他基因组的分析。

项目成果

期刊论文数量(0)
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会议论文数量(0)
专利数量(0)

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Tao Jiang其他文献

Detection of the number of two-dimensional harmonics in additive colored noise
加性有色噪声中二维谐波数量的检测
A Fine-Resolution Snow Depth Retrieval Algorithm From Enhanced-Resolution Passive Microwave Brightness Temperature using Machine Learning in Northeast China
中国东北地区使用机器学习的增强分辨率被动微波亮度温度精细分辨率雪深反演算法
  • DOI:
    10.1109/lgrs.2022.3196135
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    4.8
  • 作者:
    Yanlin Wei;Xiaofeng Li;Lingjia Gu;Xingming Zheng;Tao Jiang;Zhaojun Zheng
  • 通讯作者:
    Zhaojun Zheng
Stochastic low-carbon scheduling with carbon capture power plants and coupon-based demand response
具有碳捕获发电厂和基于优惠券的需求响应的随机低碳调度
  • DOI:
    10.1016/j.apenergy.2017.08.119
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    11.2
  • 作者:
    Xue Li;Rufeng Zhang;Linquan Bai;Guoqing Li;Tao Jiang;Houhe Chen
  • 通讯作者:
    Houhe Chen
NLOS Identification for Wideband mmWave Systems at 28 GHz
28 GHz 宽带毫米波系统的 NLOS 识别
A Novel Homomorphic MAC Scheme for Authentication in Network Coding
网络编码中一种新的同态MAC认证方案
  • DOI:
    10.1109/lcomm.2011.090911.111531
  • 发表时间:
    2011-10
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chi Cheng;Tao Jiang
  • 通讯作者:
    Tao Jiang

Tao Jiang的其他文献

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{{ truncateString('Tao Jiang', 18)}}的其他基金

Extremal Problems on Graphs and Hypergraphs
图和超图的极值问题
  • 批准号:
    1855542
  • 财政年份:
    2019
  • 资助金额:
    $ 48.99万
  • 项目类别:
    Continuing Grant
EAGER: Transcript-Based Differential Expression Analysis for Population Data Without Predefined Conditions
EAGER:在没有预定义条件的情况下对群体数据进行基于转录的差异表达分析
  • 批准号:
    1646333
  • 财政年份:
    2016
  • 资助金额:
    $ 48.99万
  • 项目类别:
    Standard Grant
Extremal problems for sparse hypergraphs and graphs
稀疏超图和图的极值问题
  • 批准号:
    1400249
  • 财政年份:
    2014
  • 资助金额:
    $ 48.99万
  • 项目类别:
    Standard Grant
Collaborative Research: ABI Innovation: Genome-Wide Inference of mRNA Isoforms and Abundance Estimation from Biased RNA-Seq Reads
合作研究:ABI 创新:mRNA 同工型的全基因组推断和有偏差的 RNA-Seq 读数的丰度估计
  • 批准号:
    1262107
  • 财政年份:
    2013
  • 资助金额:
    $ 48.99万
  • 项目类别:
    Standard Grant
III-CXT: Collaborative Research: A High-Throughput Approach to the Assignment of Orthologous Genes Based on Genome Rearrangement
III-CXT:协作研究:基于基因组重排的直系同源基因分配的高通量方法
  • 批准号:
    0711129
  • 财政年份:
    2007
  • 资助金额:
    $ 48.99万
  • 项目类别:
    Continuing Grant
Algorithmic Problems in Haplotyping, Oligonucleotide Fingerprinting,and NMR Peak Assignment
单倍型分析、寡核苷酸指纹图谱和 NMR 峰分配中的算法问题
  • 批准号:
    0309902
  • 财政年份:
    2003
  • 资助金额:
    $ 48.99万
  • 项目类别:
    Standard Grant
Efficient Algorithms for Molecular Sequences, Evolutionary Trees, and Physical Maps
分子序列、进化树和物理图谱的高效算法
  • 批准号:
    9988353
  • 财政年份:
    2000
  • 资助金额:
    $ 48.99万
  • 项目类别:
    Continuing Grant

相似国自然基金

Computational Methods for Analyzing Toponome Data
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    60601030
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