Summit on translational bioinformatics最新文献

{"title":"Bayesian combinatorial partitioning for detecting interactions among genetic variants.","authors":"Shyam Visweswaran,&nbsp;An-Kwok Ian Wong","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Detecting epistatic (nolinear) interactions among single nucleotide polymorphisms (SNPs) at multiple loci is important in the analysis of genomic data in association studies. We developed a Bayesian combinatorial partitioning (BCP) for detecting such interactions among SNPs that are predictive of disease. When compared with multifactor dimensionality reduction (MDR), a widely used combinatorial partitioning method for detecting interactions, BCP has significantly greater power and is computationally more efficient.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2009 ","pages":"133"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041553/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693831","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}

{"title":"Comorbidity of bipolar disorder with substance abuse: selection of prioritized genes for translational research.","authors":"Raphael D Isokpehi,&nbsp;Sharon A Lewis,&nbsp;Tolulola O Oyeleye,&nbsp;Wellington K Ayensu,&nbsp;Tonya M Gerald","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Bipolar disorder is a highly heritable mental illness. The global burden of bipolar disorder is complicated by its comorbidity with substance abuse. Several genome-wide linkage/association studies on bipolar disorder as well as substance abuse have focused on the identification and/or prioritization of candidate disease genes. A useful step for translational research of these identified/prioritized genes is to identify sets of genes that have particular kinds of publicly available data. Therefore, we have leveraged the availability of links to related resources in the Entrez Gene database to develop a web-based resource for selecting genes based on presence or absence in particular biological data resources. The utility of our approach is demonstrated using a set of 3,399 genes from multiple eukaryotes that have been studied in the context of bipolar disorder and/or substance abuse. A web resource to automate the selection of genes that contain certain database links is available at http://compbio.jsums.edu/bpd.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2009 ","pages":"49-53"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041554/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694059","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}

{"title":"Mining to find the lipid interaction networks involved in Ovarian Cancers.","authors":"Rajaraman Kanagasabai,&nbsp;Kothandaraman Narasimhan,&nbsp;Hong-Sang Low,&nbsp;Wee Tiong Ang,&nbsp;Aaron Z Fernandis,&nbsp;Markus R Wenk,&nbsp;Mahesh A Choolani,&nbsp;Christopher J O Baker","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>The role of lipids in cancer during the genesis, progression and subsequent metastasis stages is increasingly discussed in the scientific literature. This information is discussed in a wide range of journals making it difficult for researchers to track the latest developments. A comprehensive assessment and translation of the lipidome of ovarian cancer, originating from literature, has yet to be made. We illustrate the deployment of semantic technologies; lipid ontology and text mining, in the aggregation and coordination of lipid literature. We provide the first report on the roles and types of lipids involved in ovarian cancer based on the mining of literature and identify key lipid-protein interactions that may point to potential drug discovery targets.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2009 ","pages":"61-5"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041567/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694061","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}

{"title":"Literature Mapping with PubAtlas - extending PubMed with a 'BLASTing interface'.","authors":"D S Parker,&nbsp;W W Chu,&nbsp;F W Sabb,&nbsp;A W Toga,&nbsp;R M Bilder","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>PubAtlas (www.pubatlas.org) is a web service and standalone program providing literature maps for the biomedical research literature. It accepts user-defined sets of terms (PubMed queries) as input, and permits 'BLASTing' of one set against another: for all terms x and y in these sets, deriving the results of the pairwise intersections x AND y. This all vs. all capability extends PubMed with a literature analysis interface. Correspondingly, the basic form of literature map that PubAtlas provides for exploring associations among sets of terms is an interactive tabular display, in heatmap/microarray format.PubAtlas supports development of specialized lexica -- hierarchies of controlled terminology that can represent sets of related concepts or a 'user-defined query language'. PubAtlas also provides historical perspectives on the literature, with temporal query features that highlight historical patterns. Generally, it is a framework for extending the PubMed interface, and an extensible platform for producing interactive literature maps.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2009 ","pages":"90-4"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694503","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}

{"title":"Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease.","authors":"Brett R South,&nbsp;Shuying Shen,&nbsp;Makoto Jones,&nbsp;Jennifer Garvin,&nbsp;Matthew H Samore,&nbsp;Wendy W Chapman,&nbsp;Adi V Gundlapalli","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Background: </strong>Natural Language Processing (NLP) systems can be used for specific Information Extraction (IE) tasks such as extracting phenotypic data from the electronic medical record (EMR). These data are useful for translational research and are often found only in free text clinical notes. A key required step for IE is the manual annotation of clinical corpora and the creation of a reference standard for (1) training and validation tasks and (2) to focus and clarify NLP system requirements. These tasks are time consuming, expensive, and require considerable effort on the part of human reviewers.</p><p><strong>Methods: </strong>Using a set of clinical documents from the VA EMR for a particular use case of interest we identify specific challenges and present several opportunities for annotation tasks. We demonstrate specific methods using an open source annotation tool, a customized annotation schema, and a corpus of clinical documents for patients known to have a diagnosis of Inflammatory Bowel Disease (IBD). We report clinician annotator agreement at the document, concept, and concept attribute level. We estimate concept yield in terms of annotated concepts within specific note sections and document types.</p><p><strong>Results: </strong>Annotator agreement at the document level for documents that contained concepts of interest for IBD using estimated Kappa statistic (95% CI) was very high at 0.87 (0.82, 0.93). At the concept level, F-measure ranged from 0.61 to 0.83. However, agreement varied greatly at the specific concept attribute level. For this particular use case (IBD), clinical documents producing the highest concept yield per document included GI clinic notes and primary care notes. Within the various types of notes, the highest concept yield was in sections representing patient assessment and history of presenting illness. Ancillary service documents and family history and plan note sections produced the lowest concept yield.</p><p><strong>Conclusions: </strong>Challenges include defining and building appropriate annotation schemas, adequately training clinician annotators, and determining the appropriate level of information to be annotated. Opportunities include narrowing the focus of information extraction to use case specific note types and sections, especially in cases where NLP systems will be used to extract information from large repositories of electronic clinical note documents.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2009 ","pages":"1-32"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041557/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694631","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}

{"title":"Artificial Intelligence in Prediction of Secondary Protein Structure Using CB513 Database.","authors":"Zikrija Avdagic,&nbsp;Elvir Purisevic,&nbsp;Samir Omanovic,&nbsp;Zlatan Coralic","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2009 ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694633","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}

{"title":"Development of an agile knowledge engineering framework in support of multi-disciplinary translational research.","authors":"Tara B Borlawsky,&nbsp;Rakesh Dhaval,&nbsp;Shannon L Hastings,&nbsp;Philip R O Payne","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>In October 2006, the National Institutes of Health launched a new national consortium, funded through Clinical and Translational Science Awards (CTSA), with the primary objective of improving the conduct and efficiency of the inherently multi-disciplinary field of translational research. To help meet this goal, the Ohio State University Center for Clinical and Translational Science has launched a knowledge management initiative that is focused on facilitating widespread semantic interoperability among administrative, basic science, clinical and research computing systems, both internally and among the translational research community at-large, through the integration of domain-specific standard terminologies and ontologies with local annotations. This manuscript describes an agile framework that builds upon prevailing knowledge engineering and semantic interoperability methods, and will be implemented as part this initiative.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2009 ","pages":"14-8"},"PeriodicalIF":0.0,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694638","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}

{"title":"A diagram editor for efficient biomedical knowledge capture and integration.","authors":"Bohua Yu,&nbsp;Elvis Jakupovic,&nbsp;Justin Wilson,&nbsp;Manhong Dai,&nbsp;Weijian Xuan,&nbsp;Barbara Mirel,&nbsp;Brian Athey,&nbsp;Stanley Watson,&nbsp;Fan Meng","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Understanding the molecular mechanisms underlying complex disorders requires the integration of data and knowledge from different sources including free text literature and various biomedical databases. To facilitate this process, we created the Biomedical Concept Diagram Editor (BCDE) to help researchers distill knowledge from data and literature and aid the process of hypothesis development. A key feature of BCDE is the ability to capture information with a simple drag-and-drop. This is a vast improvement over manual methods of knowledge and data recording and greatly increases the efficiency of the biomedical researcher. BCDE also provides a unique concept matching function to enforce consistent terminology, which enables conceptual relationships deposited by different researchers in the BCDE database to be mined and integrated for intelligible and useful results. We hope BCDE will promote the sharing and integration of knowledge from different researchers for effective hypothesis development.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"130-4"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29694342","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}

{"title":"PSI: The Dutch Academic Infrastructure for shared biobanks for translational research.","authors":"Jan L Talmon,&nbsp;Maurits G Ros',&nbsp;Dink A Legemate","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Translational research requires large patient populations. A single research institute is not able to build up such a population in a short period of time. The String of Pearls Initiative (in Dutch \"Parelsnoer Initiatief\", PSI) is a joint effort by the eight academic medical centers in the Netherlands to built an infrastructure for joint biobanking as to meet this challenge of establishing large collections of data and samples in relevant medical domains.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"110-4"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693826","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}

{"title":"Construction of Multi-dimensional Arterial Health Status Map based on Molecular and Clinical Measurements, Fuzzy System and Data Cubes.","authors":"Lawrence W C Chan,&nbsp;Iris F F Benzie,&nbsp;Thomas Y H Lau,&nbsp;Yongping Zheng,&nbsp;Alex K S Wong,&nbsp;Y Liu,&nbsp;Phoebe S T Chan","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Atherosclerosis results from inflammatory processes involving biomarkers, such as lipid profile, haemoglobin A1C, oxidative stress, coronary artery calcium score and flow-mediated endothelial response through nitric oxide. This paper proposes a health status coefficient, which comprehends molecular and clinical measurements concerning atherosclerosis to provide a measure of arterial health. An arterial health status map is produced to map the multi-dimensional measurements to the health status coefficient. The mapping is modeled by a fuzzy system embedded with the health domain expert knowledge. The measurements obtained from the pilot study are used to tune the fuzzy system. The inferred arterial health coefficients are stored into the data cubes of a multi-dimensional database. Due to this adaptability and transparency of fuzzy system, the health status map can be easily updated when the refinement of fuzzy rule base is needed or new measurements are obtained.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2008 ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041522/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29693408","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}