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Summit on translational bioinformatics最新文献

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Facilitating health data sharing across diverse practices and communities. 促进不同做法和社区之间的卫生数据共享。
Summit on translational bioinformatics Pub Date : 2010-03-01
Ching-Ping Lin, Robert A Black, Jay Laplante, Gina A Keppel, Leah Tuzzio, Alfred O Berg, Ron J Whitener, Dedra S Buchwald, Laura-Mae Baldwin, Paul A Fishman, Sarah M Greene, John H Gennari, Peter Tarczy-Hornoch, Kari A Stephens
{"title":"Facilitating health data sharing across diverse practices and communities.","authors":"Ching-Ping Lin,&nbsp;Robert A Black,&nbsp;Jay Laplante,&nbsp;Gina A Keppel,&nbsp;Leah Tuzzio,&nbsp;Alfred O Berg,&nbsp;Ron J Whitener,&nbsp;Dedra S Buchwald,&nbsp;Laura-Mae Baldwin,&nbsp;Paul A Fishman,&nbsp;Sarah M Greene,&nbsp;John H Gennari,&nbsp;Peter Tarczy-Hornoch,&nbsp;Kari A Stephens","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Health data sharing with and among practices is a method for engaging rural and underserved populations, often with strong histories of marginalization, in health research. The Institute of Translational Health Sciences, funded by a National Institutes of Health Clinical and Translational Science Award, is engaged in the LC Data QUEST project to build practice and community based research networks with the ability to share semantically aligned electronic health data. We visited ten practices and communities to assess the feasibility of and barriers to developing data sharing networks. We found that these sites had very different approaches and expectations for data sharing. In order to support practices and communities and foster the acceptance of data sharing in these settings, informaticists must take these diverse views into account. Based on these findings, we discuss system design implications and the need for flexibility in the development of community-based data sharing networks.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"16-20"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041543/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694349","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
An R package for simulation experiments evaluating clinical trial designs. 一个用于评估临床试验设计的模拟实验的R包。
Summit on translational bioinformatics Pub Date : 2010-03-01
Yuanyuan Wang, Roger Day
{"title":"An R package for simulation experiments evaluating clinical trial designs.","authors":"Yuanyuan Wang,&nbsp;Roger Day","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This paper presents an open-source application for evaluating competing clinical trial (CT) designs using simulations. The S4 system of classes and methods is utilized. Using object-oriented programming provides extensibility through careful, clear interface specification; using R, an open-source widely-used statistical language, makes the application extendible by the people who design CTs: biostatisticians. Four key classes define the specifications of the population models, CT designs, outcome models and evaluation criteria. Five key methods define the interfaces for generating patient baseline characteristics, stopping rule, assigning treatment, generating patient outcomes and calculating the criteria. Documentation of their connections with the user input screens, with the central simulation loop, and with each other faciliates the extensibility. New subclasses and instances of existing classes meeting these interfaces can integrate immediately into the application. To illustrate the application, we evaluate the effect of patient pharmacokinetic heterogeneity on the performance of a common Phase I \"3+3\" design.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"61-5"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693646","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
Evaluating the impact of conceptual knowledge engineering on the design and usability of a clinical and translational science collaboration portal. 评估概念知识工程对临床和转化科学合作门户的设计和可用性的影响。
Summit on translational bioinformatics Pub Date : 2010-03-01
Philip R O Payne, Tara B Borlawsky, Robert Rice, Peter J Embi
{"title":"Evaluating the impact of conceptual knowledge engineering on the design and usability of a clinical and translational science collaboration portal.","authors":"Philip R O Payne,&nbsp;Tara B Borlawsky,&nbsp;Robert Rice,&nbsp;Peter J Embi","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>With the growing prevalence of large-scale, team science endeavors in the biomedical and life science domains, the impetus to implement platforms capable of supporting asynchronous interaction among multidisciplinary groups of collaborators has increased commensurately. However, there is a paucity of literature describing systematic approaches to identifying the information needs of targeted end-users for such platforms, and the translation of such requirements into practicable software component design criteria. In previous studies, we have reported upon the efficacy of employing conceptual knowledge engineering (CKE) techniques to systematically address both of the preceding challenges in the context of complex biomedical applications. In this manuscript we evaluate the impact of CKE approaches relative to the design of a clinical and translational science collaboration portal, and report upon the preliminary qualitative users satisfaction as reported for the resulting system.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"41-5"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041529/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693717","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 knowledge extraction framework for biomedical pathways. 生物医学路径的知识提取框架。
Summit on translational bioinformatics Pub Date : 2010-03-01
Sanda Harabagiu, Cosmin Adrian Bejan
{"title":"A knowledge extraction framework for biomedical pathways.","authors":"Sanda Harabagiu,&nbsp;Cosmin Adrian Bejan","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>In this paper we present a novel knowledge extraction framework that is based on semantic parsing. The semantic information originates in a variety of resources, but one in particular, namely BioFrameNet, is central to the characterization of complex events and processes that form biomedical pathways. The paper discusses the promising results of semantic parsing and explains how these results can be used for capturing complex medical knowledge.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694343","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
The human studies database project: federating human studies design data using the ontology of clinical research. 人类研究数据库项目:使用临床研究本体联合人类研究设计数据。
Summit on translational bioinformatics Pub Date : 2010-03-01
Ida Sim, Simona Carini, Samson Tu, Rob Wynden, Brad H Pollock, Shamim A Mollah, Davera Gabriel, Herbert K Hagler, Richard H Scheuermann, Harold P Lehmann, Knut M Wittkowski, Meredith Nahm, Suzanne Bakken
{"title":"The human studies database project: federating human studies design data using the ontology of clinical research.","authors":"Ida Sim,&nbsp;Simona Carini,&nbsp;Samson Tu,&nbsp;Rob Wynden,&nbsp;Brad H Pollock,&nbsp;Shamim A Mollah,&nbsp;Davera Gabriel,&nbsp;Herbert K Hagler,&nbsp;Richard H Scheuermann,&nbsp;Harold P Lehmann,&nbsp;Knut M Wittkowski,&nbsp;Meredith Nahm,&nbsp;Suzanne Bakken","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Human studies, encompassing interventional and observational studies, are the most important source of evidence for advancing our understanding of health, disease, and treatment options. To promote discovery, the design and results of these studies should be made machine-readable for large-scale data mining, synthesis, and re-analysis. The Human Studies Database Project aims to define and implement an informatics infrastructure for institutions to share the design of their human studies. We have developed the Ontology of Clinical Research (OCRe) to model study features such as design type, interventions, and outcomes to support scientific query and analysis. We are using OCRe as the reference semantics for federated data sharing of human studies over caGrid, and are piloting this implementation with several Clinical and Translational Science Award (CTSA) institutions.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"51-5"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041546/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693644","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
An automated approach to calculating the daily dose of tacrolimus in electronic health records. 电子健康记录中计算他克莫司日剂量的自动方法。
Summit on translational bioinformatics Pub Date : 2010-03-01
Hua Xu, Son Doan, Kelly A Birdwell, James D Cowan, Andrew J Vincz, David W Haas, Melissa A Basford, Joshua C Denny
{"title":"An automated approach to calculating the daily dose of tacrolimus in electronic health records.","authors":"Hua Xu,&nbsp;Son Doan,&nbsp;Kelly A Birdwell,&nbsp;James D Cowan,&nbsp;Andrew J Vincz,&nbsp;David W Haas,&nbsp;Melissa A Basford,&nbsp;Joshua C Denny","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Clinical research often requires extracting detailed drug information, such as medication names and dosages, from Electronic Health Records (EHR). Since medication information is often recorded as both structured and unstructured formats in the EHR, extracting all the relevant drug mentions and determining the daily dose of a medication for a selected patient at a given date can be a challenging and time-consuming task. In this paper, we present an automated approach using natural language processing to calculate daily doses of medications mentioned in clinical text, using tacrolimus as a test case. We evaluated this method using data sets from four different types of unstructured clinical data. Our results showed that the system achieved precisions of 0.90-1.00 and recalls of 0.81-1.00.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"71-5"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693648","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
PositionMatcher: A Fast Custom-Annotation Tool for Short DNA Sequences. PositionMatcher:短DNA序列的快速自定义注释工具。
Summit on translational bioinformatics Pub Date : 2010-03-01
Erik Pitzer, Jihoon Kim, Kiltesh Patel, Pedro A Galante, Lucila Ohno-Machado
{"title":"PositionMatcher: A Fast Custom-Annotation Tool for Short DNA Sequences.","authors":"Erik Pitzer,&nbsp;Jihoon Kim,&nbsp;Kiltesh Patel,&nbsp;Pedro A Galante,&nbsp;Lucila Ohno-Machado","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Microarray probes and reads from massively parallel sequencing technologies are two most widely used genomic tags for a transcriptome study. Names and underlying technologies might differ, but expression technologies share a common objective-to obtain mRNA abundance values at the gene level, with high sensitivity and specificity. However, the initial tag annotation becomes obsolete as more insight is gained into biological references (genome, transcriptome, SNP, etc.). While novel alignment algorithms for short reads are being released every month, solutions for rapid annotation of tags are rare. We have developed a generic matching algorithm that uses genomic positions for rapid custom-annotation of tags with a time complexity O(nlogn). We demonstrate our algorithm on the custom annotation of Illumina massively parallel sequencing reads and Affymetrix microarray probes and identification of alternatively spliced regions.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"25-9"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041550/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693712","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
Automated ontological gene annotation for computing disease similarity. 计算疾病相似度的自动本体论基因注释。
Summit on translational bioinformatics Pub Date : 2010-03-01
Sachin Mathur, Deendayal Dinakarpandian
{"title":"Automated ontological gene annotation for computing disease similarity.","authors":"Sachin Mathur,&nbsp;Deendayal Dinakarpandian","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>The annotation of gene/gene products with information on associated diseases is useful as an aid to clinical diagnosis and drug discovery. Several supervised and unsupervised methods exist that automate the association of genes with diseases, but relatively little work has been done to map protein sequence data to disease terminologies. This paper augments an existing open-disease terminology, the Disease Ontology (DO), and uses it for automated annotation of Swissprot records. In addition to the inherent benefits of mapping data to a rich ontology, we demonstrate a gain of 36.1% in gene-disease associations compared to that in DO. Further, we measure disease similarity by exploiting the co-occurrence of annotation among proteins and the hierarchical structure of DO. This makes it possible to find related diseases or signs, with the potential to find previously unknown relationships.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"12-6"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041538/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694348","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
Distributed cognition artifacts on clinical research data collection forms. 临床研究数据收集表上的分布式认知人工制品。
Summit on translational bioinformatics Pub Date : 2010-03-01
Meredith Nahm, Vickie D Nguyen, Elie Razzouk, Min Zhu, Jiajie Zhang
{"title":"Distributed cognition artifacts on clinical research data collection forms.","authors":"Meredith Nahm, Vickie D Nguyen, Elie Razzouk, Min Zhu, Jiajie Zhang","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Cognitive factors have not been studied as a possible explanation for medical record abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms.We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"36-40"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693716","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
Corpus-based Approach to Creating a Semantic Lexicon for Clinical Research Eligibility Criteria from UMLS. 基于语料库的UMLS临床研究资格标准语义词典创建方法。
Summit on translational bioinformatics Pub Date : 2010-03-01
Zhihui Luo, Robert Duffy, Stephen Johnson, Chunhua Weng
{"title":"Corpus-based Approach to Creating a Semantic Lexicon for Clinical Research Eligibility Criteria from UMLS.","authors":"Zhihui Luo,&nbsp;Robert Duffy,&nbsp;Stephen Johnson,&nbsp;Chunhua Weng","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>We describe a corpus-based approach to creating a semantic lexicon using UMLS knowledge sources. We extracted 10,000 sentences from the eligibility criteria sections of clinical trial summaries contained in ClinicalTrials.gov. The UMLS Metathesaurus and SPECIALIST Lexical Tools were used to extract and normalize UMLS recognizable terms. When annotated with Semantic Network types, the corpus had a lexical ambiguity of 1.57 (=total types for unique lexemes / total unique lexemes) and a word occurrence ambiguity of 1.96 (=total type occurrences / total word occurrences). A set of semantic preference rules was developed and applied to completely eliminate ambiguity in semantic type assignment. The lexicon covered 95.95% UMLS-recognizable terms in our corpus. A total of 20 UMLS semantic types, representing about 17% of all the distinct semantic types assigned to corpus lexemes, covered about 80% of the vocabulary of our corpus.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"26-30"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041551/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693713","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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