Bioinformatics Core

生物信息学核心

• 批准号: 9306879
• 负责人: Shahid Karim
• 金额: $ 6万
• 依托单位: UNIVERSITY OF SOUTHERN MISSISSIPPI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9306879
• 关键词: Address; Algorithms; Amino Acid Sequence; Applications Grants; Area; Awareness; Bioinformatics; Biological; Biomedical Research; Collaborations; Collection; Competence; Complex; Complex Analysis; Computer software; Consensus; Consultations; Continuing Education; Custom; Cystic Fibrosis Transmembrane Conductance Regulator; Data; Data Analyses; Data Set; Data Storage and Retrieval; Databases; Development; Dimensions; Educational Curriculum; Educational workshop; Exposure to; Extensible Markup Language; Faculty; Gene Expression; Gene Proteins; Generations; Generic Drugs; Genomics; Goals; Graph; Informatics; Institution; Ions; Knowledge; Learning; Literature; Mass Spectrum Analysis; Mentors; Methodology; Methods; Mississippi; Molecular; Ontology; Output; Paper; Pathway interactions; Peer Review; Phylogenetic Analysis; Population Analysis; Procedures; Process; Progress Reports; Protein Structure Initiative; Proteins; Proteomics; PubMed; Research; Research Personnel; Research Project Grants; Resources; Secure; Self-Direction; Sequence Analysis; Series; Services; Structure; Students; System; Systems Biology; Testing; Text; Training; Training and Infrastructure; Travel; Universities; Visit; Visual; analytical tool; base; bioimaging; cohort; computer program; cyber infrastructure; data exchange; data mining; data sharing; design; experience; experimental study; field study; genetic analysis; genome analysis; graduate student; improved; indexing; interdisciplinary collaboration; journal article; literacy; microscopic imaging; online resource; protein aminoacid sequence; protein metabolite; science education; skills; text searching; tool; web site

Bioinformatics Core (Aim #1 and 2) The specific goals of the MS-INBRE Bioinformatics Core are: 1) build on existing interdisciplinary collaborations; 2) create new collaborative efforts between the PUIs and the research intensive universities; 3) train PUI students in bioinformatics; and 4) help address the serious cyberinfrastructure needs in Mississippi. To reach these goals the bioinformatics core will focus on improving bioinformatics awareness and literacy in Mississippi. The Bioinformatics Core will assist the PUI investigators with their scientific needs (Aim #1). Based on past experience (see "Progress Report" section for example), we envision that the following services will meet the scientific needs of PUI investigators: 1) Design and implementation of bioinformatics methods needed for projects. Bioinformatics solutions to research questions often require the integration of multiple bioinformatics methods in a computational pipeline. Increasingly, the use on spreadsheets by research investigators and students to manage and analyze results is also not optimal for comprehensive discovery of biological implications from data. The lack of expertise for these types of bioinformatics solutions could limit the research questions pursued and reduce the overall impact of the research project. Likely common small-scale bioinformatics analysis will include sequence and structure and phylogenetic analysis. Extracting information from literature databases is also a need for research projects that the Core can provide expertise. More complex analysis could include gene, protein and metabolite expression. As an example. Dr. Heda, a PUI investigator at MUW, utilized proteomics to study the cystic fibrosis transmembrane conductance regulator (CFTR). This project will generate large amounts of mass-spectrometry datasets in form of ion spectra that must be assigned to peptide sequences as well as inferences on protein abundances. The core will provide training for Dr. Heda and his students on understanding of the data exchange formats associated with mass spectrometry experiments such as mzML, TraML, mzldentML, mzQuantML and PSI-MI XML. 2) Advise on hardware and software needs for data storage, data sharing and data analysis. Types of data input or outputs associated with MS-INBRE projects include images from microscopes, tables of data, graphs, genomic and protein sequences, molecular pathway diagrams, videos of experiments and audio files. The data storage, sharing and analysis needs of MS-INBRE research projects vary depending on the data type. Thus the solution for each project will be customized. A critical need to facilitate research collaboration among MS-INBRE researchers is the implementation of a cyberinfrastructure for seamless and secure storage of data. In some cases, it is desired to have data storage, analysis and sharing to be accessible off-line and via a website. Visual analytics tools are making it possible for these data processes to be done together with minimal computer programming. 3) Contribute to grant proposals. The Bioinformatics Core will help provide preliminary data appropriate for inclusion in grant proposals. This data generation will be done in consultation with the collaborative research investigator. Standard or customized text for inclusion in the grant proposals will also be provided to investigators. The aim of this effort is to strengthen the research projects by adding the appropriate bioinformatics components. This is particulariy critical for PUI investigators. 4) Other technical services. The Core will provide assistance with the following bioinformatics topics: (1) Genome analysis; (2) Sequence analysis; (3) Phylogenetics; (4) Structural bioinformatics; (5) Gene expression; (6) Genetic and population analysis; (7) Systems biology; (8) Data and text mining; (9) Databases and ontologies and (10) Bioimage Informatics. Bioinformatics Literacy Project (Aim #2). Biomedical research involves the management and analysis of large and complex datasets requiring an understanding of a variety of bioinformatics software and databases. An urgent need identified by the MS-INBRE Bioinformatics Core is the need to build up the expertise of investigators and students at the PUIs in bioinformatics. The Bioinformatics Core has developed several tools that target PUIs. This is a critical need because PUIs do not have significant access or exposure to bioinformatics as an area of study. These tools will contribute to the development ofthe student pipeline into biomedical research. We have developed a Bioinformatics Literacy Project that will begin to address this issue. We believe that full implementation of this project at the PUIs will lead to the training of a large cohort of students in bioinformatics. The training components of this project are: 1) Bioinformatics Test Bank System. In this training infrastructure component, cohorts of trained graduate students at the core director's institution (JSU) read peer-reviewed bioinformatics articles and construct questions along with multiple-choice answers in the bioinformatics research areas. Questions are scored resulting in consensus questions. The Bioinformatics Test Bank system when fully developed will provide a resource for self-directed bioinformatics training, continuing education as well as competency testing. These questions will also be used in the bioinformatics traveling workshops at the PUIs. Ultimately however, the goal ofthe core is to infuse these modules into the science education curricula at the PUIs. 2) Bioinformatics Text Annotation. With a similar goal as above, experienced graduate students will help develop the bioinformatics curriculum by developing tools that facilitate learning. The abstract of a journal article on bioinformatics topics provides concise information about the article. The Sentence Annotation training infrastructure component was implemented to characterize sentences in abstracts by Focus - type of the information conveyed by the statement. Focus dimensions can be classified into three various types: Scientific (S) discussing findings and discovery; Generic (G) stating general knowledge, clarifying the structure ofthe paper, etc.; Methodology (M)�describing a procedure or a method. A database of categorized sentences can be a learning resource for understanding bioinformatics facts. We have developed sentence segmentation algorithm, which splits titte and abstracts for sets of citations indexed in PubMed into sentences. Further, a web resource to retrieve the sentences is available based on keyword and PubMed Identifier (http://genomics.jsums.edu/sentence/bioinformj_pubmed/). 3) Short Bioinformatics Research Projects. Short-term (1-6 months) bioinformatics research projects can help students develop specialized bioinformatics skills. The bioinformatics core is coordinating efforts to develop short-term project ts that students (PUI and others) can engage in remotely from their institution with guidance from the core director. A collection of projects will be used for mentored senior year projects as well as objectives for graduate student theses or dissertation. Short-term projects are envisioned to have a mentoring component that may require an initial visit to JSU for training, however student-initiated projects will also be encouraged. We believe that this activity, once fully developed, will become an important resource for students at the PUIs or other institutions who lack faculty with bioinformatics expertise. 4) Bioinformatics Training Workshops. We have designed a training workshop series to provide research-driven level-defined introductory and advanced training workshops for students and faculty in Mississippi. The following workshops have been developed: a. Introductory Bioinformatics I (Introduction, Sequence Analysis, Databases and Ontologies) b. Introductory Bioinformatics II (Genome Analysis, Phylogenetics, and Structural Bioinformatics) c. Advanced Bioinformatics I (Gene Expression, Genetic and Population Analysis) d. Advanced Bioinformatics II (Systems Biology, Data and Text Mining) These traveling workshops will be conducted at the PUIs so that they reach students who otherwise would not be exposed to bioinformatics as a field of study. They will also be used as a tool to advertise the bioinformatics core services to investigators at the PUIs. We also plan to use these traveling workshops to cultivate interdisciplinary collaborations between the PUIs and research-intensive universities.

生物信息学核心（目标#1和2） MS-INBRE 生物信息学核心的具体目标是：1）建立在现有的跨学科合作基础上； 2) 在 PUI 和研究密集型大学之间开展新的合作； 3）对PUI学生进行生物信息学培训； 4) 帮助解决密西西比州严峻的网络基础设施需求。为了实现这些目标，生物信息学核心将致力于提高密西西比州的生物信息学意识和素养。 生物信息学核心将协助 PUI 研究人员满足其科学需求（目标#1）。 根据过去的经验（例如，参见“进展报告”部分），我们预计以下服务将满足 PUI 研究人员的科学需求： 1）项目所需的生物信息学方法的设计和实现。 研究问题的生物信息学解决方案通常需要在计算管道中集成多种生物信息学方法。研究人员和学生越来越多地使用电子表格来管理和分析结果，这对于从数据中全面发现生物学意义来说也不是最佳选择。缺乏此类生物信息学解决方案的专业知识可能会限制所追求的研究问题并降低研究项目的总体影响。可能常见的小规模生物信息学分析将包括序列和结构以及系统发育分析。从文献数据库中提取信息也是核心可以提供专业知识的研究项目的需要。更复杂的分析可能包括基因、蛋白质和代谢物表达。举个例子。 Heda 博士是 MUW 的 PUI 研究员，利用蛋白质组学研究囊性纤维化跨膜电导调节器 (CFTR)。该项目将生成大量离子谱形式的质谱数据集，这些数据集必须分配给肽序列： 以及对蛋白质丰度的推断。该核心将为 Heda 博士和他的学生提供培训，帮助他们了解与质谱实验相关的数据交换格式，例如 mzML、TraML、mzldentML、mzQuantML 和 PSI-MI XML。 2）就数据存储、数据共享和数据的硬件和软件需求提供建议 分析。与 MS-INBRE 项目相关的数据输入或输出类型包括来自 显微镜、数据表、图表、基因组和蛋白质序列、分子途径图、 实验视频和音频文件。 MS-INBRE的数据存储、共享和分析需求 研究项目因数据类型而异。因此每个项目的解决方案将是 定制。促进 MS-INBRE 研究人员之间的研究合作的一个关键需求是 实施网络基础设施以实现无缝和安全的数据存储。在某些情况下，它是 希望能够通过网站离线访问数据存储、分析和共享。视觉的 分析工具使这些数据处理以最少的时间完成成为可能 计算机编程。 3) 为拨款提案做出贡献。生物信息学核心将帮助提供初步数据 适合纳入赠款提案。该数据生成将与 合作研究调查员。纳入资助提案的标准或定制文本将 也将提供给调查人员。这项工作的目的是通过增加 适当的生物信息学组件。这对于 PUI 调查人员来说尤其重要。 4）其他技术服务。核心将提供以下生物信息学方面的帮助 主题：（1）基因组分析； (2) 序列分析； (3) 系统发育学； (4)结构生物信息学； (5) 基因表达； (6)遗传和群体分析； (7)系统生物学； (8)数据和文本挖掘； (9) 数据库和本体以及 (10) 生物图像信息学。 生物信息学素养项目（目标#2）。生物医学研究涉及管理和 分析大型且复杂的数据集需要了解各种生物信息学 软件和数据库。 MS-INBRE 生物信息学核心确定的迫切需求是 培养 PUI 的研究人员和学生在生物信息学方面的专业知识。生物信息学核心开发了多种针对 PUI 的工具。这是一个至关重要的需求，因为 PUI 没有大量接触或接触生物信息学作为研究领域。这些工具将有助于学生生物医学研究渠道的发展。我们开发了一个生物信息学素养项目，将开始解决这个问题。我们相信该项目的全面实施 PUI 将培训一大批生物信息学学生。培训内容 该项目的组成部分是： 1）生物信息学测试库系统。在这个培训基础设施组成部分中， 在核心主任机构 (JSU) 受过培训的研究生阅读同行评审的生物信息学 生物信息学研究中的文章和构建问题以及多项选择答案 地区。对问题进行评分，得出共识问题。生物信息学测试库系统完全开发后将为自主生物信息学培训、继续教育以及能力测试提供资源。这些问题也将用于 PUI 的生物信息学巡回研讨会。然而，核心的最终目标是将这些模块融入 PUI 的科学教育课程中。 2）生物信息学文本注释。与上述目标相似，经验丰富的毕业生 学生将通过开发促进学习的工具来帮助开发生物信息学课程。关于生物信息学主题的期刊文章的摘要提供了有关该文章的简明信息。句子注释培训基础设施组件的实施是为了按焦点（陈述所传达的信息类型）来表征摘要中的句子。焦点维度可分为三种不同类型：科学（S）讨论发现和发现； Generic (G) 陈述一般知识，阐明论文结构等；方法论 (M)——描述程序或方法。分类句子的数据库可以成为理解生物信息学事实的学习资源。我们开发了句子分割算法，它将 PubMed 中索引的引文集的标题和摘要分割成句子。此外，还可以根据关键字和 PubMed 标识符检索句子的网络资源 （http://genomics.jsums.edu/sentence/bioinformj_pubmed/）。 3) 短期生物信息学研究项目。短期（1-6个月）生物信息学研究 项目可以帮助学生培养专业的生物信息学技能。生物信息学核心正在协调努力开发短期项目，学生（PUI 和其他人）可以在核心主任的指导下从所在机构远程参与。一系列项目将用于指导高年级项目以及研究生论文或论文的目标。 短期项目预计包含指导部分，可能需要初次访问 JSU 进行培训，但也鼓励学生发起的项目。我们相信，这项活动一旦得到充分发展，将成为 PUI 或其他缺乏生物信息学专业教师的机构的学生的重要资源。 4）生物信息学培训研讨会。我们设计了一个培训研讨会系列 为密西西比州的学生和教师提供研究驱动的、级别定义的入门和高级培训研讨会。已举办以下研讨会： 一个。生物信息学导论 I（简介、序列分析、数据库和本体） b.生物信息学入门 II（基因组分析、系统发育学和结构生物信息学） c.高级生物信息学 I（基因表达、遗传和群体分析） d.高级生物信息学 II（系统生物学、数据和文本挖掘） 这些巡回研讨会将在 PUI 举办，以便接触到那些原本不会接触生物信息学这一研究领域的学生。它们还将用作向 PUI 的研究人员宣传生物信息学核心服务的工具。我们还计划利用这些巡回研讨会来培养 PUI 和研究密集型大学之间的跨学科合作。