2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology最新文献

A Comparison of Computational Approaches in the Molecular Identification of Pathogenic Organisms 病原生物分子鉴定计算方法的比较

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.23

D. Bastola, Scott P. McGrath, S. Bhowmick, I. Thapa

引用次数: 0

Integrating Transcriptome and Proteome Information for the Analysis of Alternative Splicing 整合转录组和蛋白质组信息分析选择性剪接

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.44

J. E. Kroll, J. E. Souza, B. Stransky, G. D. Souza, S. J. Souza

{"title":"Integrating Transcriptome and Proteome Information for the Analysis of Alternative Splicing","authors":"J. E. Kroll, J. E. Souza, B. Stransky, G. D. Souza, S. J. Souza","doi":"10.1109/HISB.2012.44","DOIUrl":"https://doi.org/10.1109/HISB.2012.44","url":null,"abstract":"Summary form only given. Alternative splicing events (AS) are among the most significant factors determining the complexity of multi-cellular organisms. Most, if not all, multi-exonic human genes undergo AS. Many AS events are involved in the etiology of cancer, among many other common human disorders. The emergence of next-generation sequencing offers a unique opportunity to explore the variability generated by AS in an exhaustive way. Furthermore, recent developments in new mass-spectometry platforms have allowed a deeper survey of the human proteome. Here, an analysis of intron retention, the most rare type of AS, was performed integrating transcriptome and proteome data. Intron retention events were evaluated in relation to several features, focusing on whether they had biological significance or whether they were just spurious products from the splicing machinery. For the transcriptome analysis, the following dataset was used: 30,678 RefSeqs, 258,444 mRNAs, 6,987,423 ESTs and 9,565,439 sequences derived from NGS. For the proteome analysis, data from Geiger et al., MCP, 2012 were used. We were able to detect an intron retention event for 48% of all human genes. Confirming a previous publication from our group [1], these events are enriched at the 3'and 5'untranslated regions (UTRs). Retained introns were significantly enriched with coding potential, which supports a biological role for these events. Furthermore, they were enriched for targets of microRNAs, suggesting a role of this type of AS in the regulation of expression induced by these non-coding RNAs. A significant number of events were detected at the proteome level. This information was integrated together with transcriptome data to further explore the role of intron retention in many biological phenomena.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125528555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

InSilico-ChIP: A Coregulation and Evolutionary Conservation Based Transcription Factor and Target Gene Predictor InSilico-ChIP:一个基于协同调节和进化保护的转录因子和靶基因预测因子

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.47

M. Munoz, A. Zambon

{"title":"InSilico-ChIP: A Coregulation and Evolutionary Conservation Based Transcription Factor and Target Gene Predictor","authors":"M. Munoz, A. Zambon","doi":"10.1109/HISB.2012.47","DOIUrl":"https://doi.org/10.1109/HISB.2012.47","url":null,"abstract":"Chromatin Immunoprecipitation followed by high-content sequencing (ChIP-seq) is a powerful approach for identifying bonafide transcription factor (TF) binding sites, however these studies can be difficult, time-consuming and costly. They require ChIP-validated antibodies and a priori knowledge of which TF to pull down. Moreover, to gain further mechanistic insights, transcriptomic data is required to determine if TF binding alters proximal gene expression. Determining regulatory pathways from expression data is not an easy task. The typical result of a gene expression experiment, a set of co-regulated genes, may not include the relevant TF at all. Many such factors become active through mechanisms other than a change in their level of expression. To understand how such a set of genes is co-regulated, it is necessary to find evidence of shared TF binding sites (TFBS). This approach presents its own set of problems. TFBS are identified by short sequences that can exist by chance without being biologically functional. An evolutionary perspective is required to consider only those functionally important sites that are conserved between the promoters of the genes in question and those of their orthologs in related species. Furthermore, the common occurrence of short TFBS makes it necessary to consider only those TFs that are significantly more common in the co-regulated genes than in the genome (or microarray) as a whole. InSilico-ChIP is a precomputed database of evolutionarily conserved TFBS for various species, which accepts a set of genes and quickly returns the conserved TFs that are statistically over-represented in the proximal promoter regions of those genes. It allows new species data to be created using only a whole genome alignment with a related species and gene locations. Several methods of identifying TF binding sites can be used, varying in alignment type, location, conservation restrictions, and TFBS matrices used to analyze the promoter regions.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129366209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Network Approach for Computational Drug Repositioning 一种计算药物重新定位的网络方法

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.26

Jiao Li, Zhiyong Lu

引用次数: 1

Using MapReduce for Large-Scale Medical Image Analysis 基于MapReduce的大规模医学图像分析

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.8

Dimitrios Markonis, Roger Schaer, Ivan Eggel, H. Müller, A. Depeursinge

引用次数: 64

Modelling the Effects of Genetic Changes in Tumour Progression 模拟肿瘤进展中基因变化的影响

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.62

Vanderson Silva, F. Santana, B. Stransky, S. J. Souza

{"title":"Modelling the Effects of Genetic Changes in Tumour Progression","authors":"Vanderson Silva, F. Santana, B. Stransky, S. J. Souza","doi":"10.1109/HISB.2012.62","DOIUrl":"https://doi.org/10.1109/HISB.2012.62","url":null,"abstract":"Tumours can be considered a set of cells that accumulate genetic and epigenetic alterations. According to the Multi-stage Hit theory, the transformation of a normal into a tumour cell involves a number of limiting events that occur in a number of discrete stages (driver mutations). However, not all mutations that occur in the cell are directly involved in the development of cancer and some probably do not contribute in any way (passenger mutations). Moreover, the process of tumour evolution is punctuated by selection of advantageous mutations and clonal expansions. Actually, it is not known how many limiting-events, i.e., how many driver mutations are necessary or sufficient to promote a carcinogenic process. This conjecture should be explored and tested - mathematically and statistically, with the availability of genomic data on databanks. In this work, we explore the model proposed by Bozic and collaborators (2010) that describes the evolution of the tumour according to a Galton-Watson process. Besides, the model gives the relation between the numbers of passenger mutations giving a specific number of driver mutations. We intend to explore some of the model parameters and test some premises about the number of drive mutations and selective advantage, comparing the simulation results with genomic data from colorectal cancer patients. The genomic data was obtained from the DBMutation (http://www.bioinformatics-brazil.org/dbmutation/), a comprehensive database for genomic mutations in cancer. We expect that correlations between driver mutations and the time evolution of tumour process will facilitate the interpretation of genomic information, to make them useful and applicable to clinical oncology.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124634396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatically Extracting Sentences from Medline Citations to Support Clinicians' Information Needs 自动从Medline引文中提取句子以支持临床医生的信息需求

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.22

Siddhartha R. Jonnalagadda, G. Fiol, Richard Medlin, C. Weir, M. Fiszman, Javed Mostafa, Hongfang Liu

{"title":"Automatically Extracting Sentences from Medline Citations to Support Clinicians' Information Needs","authors":"Siddhartha R. Jonnalagadda, G. Fiol, Richard Medlin, C. Weir, M. Fiszman, Javed Mostafa, Hongfang Liu","doi":"10.1109/HISB.2012.22","DOIUrl":"https://doi.org/10.1109/HISB.2012.22","url":null,"abstract":"Online health knowledge resources contain answers to most of the information needs raised by clinicians in the course of care. However, significant barriers limit the use of these resources for decision-making, especially clinicians' lack of time. Existing solutions are less optimal when information needs cannot be met without substantial cognitive effort and time. Objectives: In this study, we assessed the feasibility of automatically generating knowledge summaries for a particular clinical topic composed of relevant sentences extracted from Medline citations. Methods: The proposed approach combines information retrieval and semantic information extraction techniques to identify relevant sentences from Medline abstracts. We assessed this approach in two case studies on the treatment alternatives for depression and Alzheimer's disease. Results: A total of 515 out of 564 (91.3%) sentences retrieved in the two case studies were relevant to the topic of interest. About one third of the relevant sentences described factual knowledge or a study conclusion that can be used for supporting information needs at the point of care. Conclusions: Our proposed technical approach to helping clinicians meet their information needs is promising. The approach can be extended for other knowledge resources and information need types.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130007283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 48

Pre-annotating Clinical Notes and Clinical Trial Announcements for Gold Standard Corpus Development: Evaluating the Impact on Annotation Speed and Potential Bias 为金标准语料库开发预注释临床笔记和临床试验公告:评估对注释速度和潜在偏倚的影响

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.33

T. Lingren, Louise Deléger, Katalin Molnár, Haijun Zhai, J. Meinzen-Derr, M. Kaiser, Laura Stoutenborough, Qi Li, I. Solti

引用次数: 6

Pulmonary Blood Vessels and Nodules Segmentation via Vessel Energy Function and Radius-Variable Sphere Model 基于血管能量函数和半径变球模型的肺血管和结节分割

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.46

Qingxiang Zhu, H. Xiong, Xiaoqian Jiang

{"title":"Pulmonary Blood Vessels and Nodules Segmentation via Vessel Energy Function and Radius-Variable Sphere Model","authors":"Qingxiang Zhu, H. Xiong, Xiaoqian Jiang","doi":"10.1109/HISB.2012.46","DOIUrl":"https://doi.org/10.1109/HISB.2012.46","url":null,"abstract":"To help diagnose the early stage of lung cancer, this paper studies pulmonary nodule and blood vessel detection and segmentation. Owing to the fact that variation in the shape and number of pulmonary blood vessels would reveal the progress of lung cancer, automatic segmentation of pulmonary nodules and blood vessels is desirable for chest computer-aided diagnosis (CAD) systems. The proposed algorithm is composed of four steps: pre-segmentation, structure enhancement, active evolution, and refinement. Through the initial extraction of 3D region growing, the line structure of vessel and blob-like structure of nodule would be enhanced by multi-scale filtering. In particular, the active evolution is devoted to the maximum likelihood estimation with a vessel energy function (VEF) of intensity, gradient, and structure. The VEF aims to shape a precise extraction by adapting all the cue distribution along the vessel region from nodules. Furthermore, a radius-variable sphere model is adopted to refine the contour with the smoothness of radius alone the centerline of the blood vessel. Finally, the proposed scheme is sufficiently evaluated to exceed the existing techniques on lung image database consortium (LIDC) database and DICOM images.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116213274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Small RNA Sequencing in microRNA Research 小RNA测序在微RNA研究中的应用

2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology Pub Date : 2012-09-27 DOI: 10.1109/HISB.2012.34

Hsei-Wei Wang

{"title":"Small RNA Sequencing in microRNA Research","authors":"Hsei-Wei Wang","doi":"10.1109/HISB.2012.34","DOIUrl":"https://doi.org/10.1109/HISB.2012.34","url":null,"abstract":"In this post-genomic era it is clear that the sum of the cellular gene expression state determines the cellular phenotypes. The challenge we now face is to keep up the bioinformatics analysis and to understand the genome blueprint. In our lab we applied and developed bioinformatics and systems biology tools for deciphering cancer and stem cell transcriptome data. Cancer stem-like cells were isolated as colonospheres from primary colon cancer tissues and cell lines and characterized their gene expression patterns and genetic networks. Expanded colon cancer spheres had many features of cancer stem cells, including chemoresistance and radioresistance, the ability to initiate tumor formation, and activation of epithelial-mesenchymal transition (EMT). SNAIL, an activator of EMT, was expressed at high levels by CRC colonospheres. smRNA-Seq and genetic network analyses revealed that SNAIL activates genes and microRNAs, such as IL8 and miR-146a, in colonospheres. Blocking IL-8 or miR-146a expression/activity disrupted SNAIL-induced stem cell-like features of colonospheres. Strategies that disrupt the SNAIL-IL8 and SNAIL-miR146a pathways can be developed to block tumor formation by colon cancer stem-like cells. We also applied our systems on brain tumor research. Atypical teratoid/rhabdoid tumor (AT/RT) is a highly malignant pediatric brain tumor often misdiagnosed as other embryonal brain tumors such as medulloblastoma (MB). AT/RT prognosis is much worse than MB, but the underlying mechanisms are unclear. We deciphered the miRNome patterns of AT/RT and MB by sequencing their small RNA fractions. Novel as well as known miRNAs were found deregulated in tumor cells. miR-221 and miR-222 are oncomiRs that can target several tumor suppressors. Further challenge will be to integrate RNA-seq information with systems biology and cloud computing tools.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125607462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0