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Summit on translational bioinformatics最新文献

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Toward the commoditization of translational genomic research: Design and implementation features of the Galaxy genomic workbench. 迈向转化基因组研究的商品化:银河基因组工作台的设计和实现特点。
Summit on translational bioinformatics Pub Date : 2008-03-01
Ross Lazarus, James Taylor, Weiliang Qiu, Anton Nekrutenko
{"title":"Toward the commoditization of translational genomic research: Design and implementation features of the Galaxy genomic workbench.","authors":"Ross Lazarus,&nbsp;James Taylor,&nbsp;Weiliang Qiu,&nbsp;Anton Nekrutenko","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Although there is now plenty of genomic data and no shortage of analysis methods for translational genomic research, many biologists do not have efficient and transparent access to the computational resources they need. No single data resource or analysis application is ever likely to efficiently address all aspects of any individual researcher's needs, so most researchers are forced to manually integrate data and outputs from multiple resources. The inevitable heterogeneity of data formats and of command syntax between data resources and software applications presents a major obstacle, particularly to those biologists lacking practical informatics skills. We describe some design and implementation features of an open-source application that supports the integration of the best available third-party genomics software applications, data and annotation resources into a coherent framework, substantially overcoming many practical challenges associated with actually doing translational genomic research.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"56-60"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041519/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
BioEMR: an integrative framework for cancer research with multiple genomic technologies. 生物emr:一个结合多种基因组技术的癌症研究综合框架。
Summit on translational bioinformatics Pub Date : 2008-03-01
Yu Rang Park, Yun Jung Bae, Ju Han Kim
{"title":"BioEMR: an integrative framework for cancer research with multiple genomic technologies.","authors":"Yu Rang Park,&nbsp;Yun Jung Bae,&nbsp;Ju Han Kim","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>The rapid development of omic technologies facilitate cancer researchers to apply multiple genomic technologies simultaneously. In fact, the complex nature of cancer biology is the reason why we need tools for data integration. Given the complexity of managing multiple technologies and dataset formats, several projects have been introduced including cancer Biomedical Informatics Grid (caGRID) and the Biomedical Research Institute Domain Group (BRIDG) with limited applicability. We introduce an object-oriented data model, Cancer Genomics Object Model (CaGe-OM) for multiple genomics data and Xperanto-CaGe, a web-based application using CaGe-OM with hybrid object-relational mapping technique. The hybrid approach uses objectrelational mapping which is extended to include dynamic structure by using Entity-Attribute-Value (EAV) model. CaGe-OM and Xperanto-CaGe are an attempt to establish a comprehensive framework for integrated storage and interpretation of clinical and multiple genomics data and to facilitate model-level integration of other newly emerging data types. A pilot implementation for the integrated clinical, histo-pathological and genomic information systems is introduced.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"81-4"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041523/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Ontology-anchored Approaches to Conceptual Knowledge Discovery in a Multi-dimensional Research Data Repository. 多维研究数据存储库中概念知识发现的本体锚定方法
Summit on translational bioinformatics Pub Date : 2008-03-01
Philip R O Payne, Tara B Borlawsky, Alan Kwok, Rakesh Dhaval, Andrew W Greaves
{"title":"Ontology-anchored Approaches to Conceptual Knowledge Discovery in a Multi-dimensional Research Data Repository.","authors":"Philip R O Payne,&nbsp;Tara B Borlawsky,&nbsp;Alan Kwok,&nbsp;Rakesh Dhaval,&nbsp;Andrew W Greaves","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Chronic Lymphocytic Leukemia (CLL) is the most common adult leukemia in the U.S., and is currently incurable. Though a small number of biomarkers that may correlate to risk of disease progression or treatment outcome in CLL have been discovered, few have been validated in prospective studies or adopted in clinical practice. In order to address this gap in knowledge, it is desirable to discover and test hypotheses that are concerned with translational biomarker-to-phenotype correlations. We report upon a study in which commonly available ontologies were utilized to support the discovery of such translational correlations. We have specifically applied a technique known as constructive induction to reason over the contents of a research data repository utilized by the NCI-funded CLL Research Consortium. Our findings indicate that such an approach can produce semantically meaningful results that can inform hypotheses about higher-level relationships between the types of data contained in such a repository.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"85-9"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041525/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Mining human phenome to investigate modularity of complex disorders. 挖掘人类现象，研究复杂疾病的模块化。
Summit on translational bioinformatics Pub Date : 2008-03-01
Ranga C Gudivada, Yun Fu, Anil G Jegga, Xiaoyan A Qu, Eric K Neumann, Bruce J Aronow
{"title":"Mining human phenome to investigate modularity of complex disorders.","authors":"Ranga C Gudivada,&nbsp;Yun Fu,&nbsp;Anil G Jegga,&nbsp;Xiaoyan A Qu,&nbsp;Eric K Neumann,&nbsp;Bruce J Aronow","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>A principal goal for biomedical research is to improve our understanding of factors that control clinical disease phenotypes. Among genetically-determined diseases, identical mutations may exhibit substantial phenotype variance by individual and background strain, suggesting both environmental and genetic mutant allele interactions. Moreover, different diseases can share phenotypic features extensively. To test the hypothesis that phenotypic similarities and differences among diseases and disease subvariants may represent differential activation of correlated feature \"disease phenotype modules\", we systematically parsed Online Mendelian Inheritance in Man (OMIM) and Syndrome DB databases using the UMLS to construct a disease - clinical phenotypic feature matrix suitable for various clustering algorithms. Using Cardiovascular Syndromes as a model, our results demonstrate a critical role for representing both phenotypic generalization and specificity relationships for the ability to retrieve non-trivial associations among disease entities such as shared protein domains and pathway and ontology functions of associated causal genes.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"31-5"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041520/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application of Natural Language Processing to VA Electronic Health Records to Identify Phenotypic Characteristics for Clinical and Research Purposes. 自然语言处理在VA电子健康记录中的应用，以识别临床和研究目的的表型特征。
Summit on translational bioinformatics Pub Date : 2008-03-01
Adi V Gundlapalli, Brett R South, Shobha Phansalkar, Anita Y Kinney, Shuying Shen, Sylvain Delisle, Trish Perl, Matthew H Samore
{"title":"Application of Natural Language Processing to VA Electronic Health Records to Identify Phenotypic Characteristics for Clinical and Research Purposes.","authors":"Adi V Gundlapalli,&nbsp;Brett R South,&nbsp;Shobha Phansalkar,&nbsp;Anita Y Kinney,&nbsp;Shuying Shen,&nbsp;Sylvain Delisle,&nbsp;Trish Perl,&nbsp;Matthew H Samore","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Informatics tools to extract and analyze clinical information on patients have lagged behind data-mining developments in bioinformatics. While the analyses of an individual's partial or complete genotype is nearly a reality, the phenotypic characteristics that accompany the genotype are not well known and largely inaccessible in free-text patient health records. As the adoption of electronic medical records increases, there exists an urgent need to extract pertinent phenotypic information and make that available to clinicians and researchers. This usually requires the data to be in a structured format that is both searchable and amenable to computation. Using inflammatory bowel disease as an example, this study demonstrates the utility of a natural language processing system (MedLEE) in mining clinical notes in the paperless VA Health Care System. This adaptation of MedLEE is useful for identifying patients with specific clinical conditions, those at risk for or those with symptoms suggestive of those conditions.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"36-40"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041527/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reverse translational bioinformatics: a bioinformatics assay of age, gender and clinical biomarkers. 逆向翻译生物信息学:年龄，性别和临床生物标志物的生物信息学分析。
Summit on translational bioinformatics Pub Date : 2008-03-01
Amit Fliss, Micha Ragolsky, Eitan Rubin
{"title":"Reverse translational bioinformatics: a bioinformatics assay of age, gender and clinical biomarkers.","authors":"Amit Fliss,&nbsp;Micha Ragolsky,&nbsp;Eitan Rubin","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>In bioinformatics, clinical data is rarely used. Here, we propose using bedsidedata in basic research, via bioinformatics methodologies. To demonstrate the potential of this so called Reverse Translational Bioinformatics approach, classical bioinformatics tools were applied to blood biomarker information attained from a large scale, open-access cross sectional survey. The results of this analysis include a novel classification of blood biomarkers, critical ages in which basic biological processes may shift in humans, and a possible approach to exploring the gender specificity of these shifts. Changes in normal values were also shown to be non-linear, with most of the non-linearity attributed to the shift from growth to maturity. Together, these finding demonstrate that reversed translational bioinformatics may contribute to basic research.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"11-5"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041524/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
GeneRanker: An Online System for Predicting Gene-Disease Associations for Translational Research. GeneRanker:一个用于翻译研究的预测基因-疾病关联的在线系统。
Summit on translational bioinformatics Pub Date : 2008-03-01
Graciela Gonzalez, Juan C Uribe, Brock Armstrong, Wendy McDonough, Michael E Berens
{"title":"GeneRanker: An Online System for Predicting Gene-Disease Associations for Translational Research.","authors":"Graciela Gonzalez,&nbsp;Juan C Uribe,&nbsp;Brock Armstrong,&nbsp;Wendy McDonough,&nbsp;Michael E Berens","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>With the overwhelming volume of genomic and molecular information available on many databases nowadays, researchers need from bioinformaticians more than encouragement to refine their searches. We present here GeneRanker, an online system that allows researchers to obtain a ranked list of genes potentially related to a specific disease or biological process by combining gene-disease (or genebiological process) associations with protein-protein interactions extracted from the literature, using computational analysis of the protein network topology to more accurately rank the predicted associations. GeneRanker was evaluated in the context of brain cancer research, and is freely available online at http://www.generanker.org.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"26-30"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A framework and mechanistically focused, in silico method for enabling rational translational research. 一个框架和机械集中，在硅的方法，使理性的翻译研究。
Summit on translational bioinformatics Pub Date : 2008-03-01
C Anthony Hunt, Sergio Baranzini, Michael A Matthay, Sunwoo Park
{"title":"A framework and mechanistically focused, in silico method for enabling rational translational research.","authors":"C Anthony Hunt,&nbsp;Sergio Baranzini,&nbsp;Michael A Matthay,&nbsp;Sunwoo Park","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>A precondition for understanding if-and-when observations on wet-lab research models can translate to patients (and vice versa) is to have a method that enables anticipating how each system at the mechanism level will respond to the same or similar new intervention. A new class of mechanistic, in silico analogues is described. We argue that, although abstract, they enable developing that method. Building an analogue of each system within a common framework allows exploration of how one analogue might undergo (automated) metamorphosis to become the other. When successful, a concrete mapping is achieved. We hypothesize that such a mapping is, itself, an analogue of a corresponding mapping between the two referent systems. The analogue mapping can help establish how targeted aspects of the two referent systems are similar and different, at the mechanistic level and, importantly, at the systemic, emergent property level. The vision is that the analogues along with the metamorphosis method can be improved iteratively as part of a rational approach to translational research.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"46-50"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041517/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Inter-session reproducibility measures for high-throughput data sources. 高吞吐量数据源的会话间再现性度量。
Summit on translational bioinformatics Pub Date : 2008-03-01
Milos Hauskrecht, Richard Pelikan
{"title":"Inter-session reproducibility measures for high-throughput data sources.","authors":"Milos Hauskrecht,&nbsp;Richard Pelikan","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>High-throughput biological assays such as micro-arrays and mass spectrometry (MS) have risen as potential clinical tools for disease detection. Multiple potential biomarkers can be rapidly and cheaply evaluated for a large number of patients. Typical research and evaluation studies in these fields have focused primarily on data that were generated from samples in a single data-generation session. However, in the clinical setting, new patients screened by the technology will arrive at different times and data will unavoidably come from multiple data-generation sessions. The understanding and assessment of multi-session effects on data generated by the technology is critical for its application to clinical practice. This paper proposes a methodology for measuring and testing the reproducibility of various aspects of high-throughput data across multiple data-generation sessions. We test and demonstrate the framework on mass-spectrometry data obtained from four different data-generation sessions for the same set of samples.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"41-5"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041518/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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