2013 8th International Symposium on Health Informatics and Bioinformatics最新文献

Classification of cohesin family using class specific motifs 用类特定基序对黏结蛋白家族进行分类

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661687

Ercument M. Eser, B. Arslan, U. Sezerman

引用次数: 2

Sampling bias in microarray data analysis: A demonstration in the field of reproductive biology 微阵列数据分析中的采样偏差:在生殖生物学领域的演示

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661684

S. Manafi, A. Uyar, A. Bener

{"title":"Sampling bias in microarray data analysis: A demonstration in the field of reproductive biology","authors":"S. Manafi, A. Uyar, A. Bener","doi":"10.1109/HIBIT.2013.6661684","DOIUrl":"https://doi.org/10.1109/HIBIT.2013.6661684","url":null,"abstract":"The actual benefit from high-throughput microarray experiments strongly relies on elimination of all possible sources of biases during both the experimental procedure and data analysis process. Within the context of reproductive biology, microarray based transcriptomic analysis of oocyte and surrounding cumulus/granulosa cells poses significant challenges due to limited amount of samples and/or potential contaminations from adjacent cells. In this study, we investigated the effect of sampling bias on consistency of the microarray differential expression analysis in the field of reproduction. Experiments were conducted on five datasets obtained from publicly available microarray repositories. For each dataset, probe level expression values were extracted and background adjustment, inter-array quantile normalization and probe set summarization were performed according to the Robust Multi-Chip Average algorithm. Genes with a false discovery rate-corrected p value of <;0.05 and [Fold Change] > 2 were considered as differentially expressed. Results demonstrate that both number of replicates and including different subsets of available samples in the analysis alter the number of differentially expressed genes. We suggest that assessment of inter-sample variance prior to differential expression analysis is an important step in microarray experiments and proper handling of that variance may require alternative normalization and/or statistical test methods.","PeriodicalId":433206,"journal":{"name":"2013 8th International Symposium on Health Informatics and Bioinformatics","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128236731","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

Ranking tandem mass spectra: And the impact of database size and scoring function on peptide spectrum matches 串联质谱排序:以及数据库大小和评分功能对肽谱匹配的影响

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661686

Canan Has, Cemal Ulas Kundakci, Aybuge Altay, J. Allmer

{"title":"Ranking tandem mass spectra: And the impact of database size and scoring function on peptide spectrum matches","authors":"Canan Has, Cemal Ulas Kundakci, Aybuge Altay, J. Allmer","doi":"10.1109/HIBIT.2013.6661686","DOIUrl":"https://doi.org/10.1109/HIBIT.2013.6661686","url":null,"abstract":"Proteomics is currently driven by mass spectrometry. For the analysis of tandem mass spectra many computational algorithms have been proposed. There are two approaches, one which assigns a peptide sequence to a tandem mass spectrum directly and one which employs a sequence database for looking up possible solutions. The former method needs high quality spectra while the latter can tolerate lower quality spectra. Since both methods are computationally expensive, it is sensible to establish spectral quality using an independent fast algorithm. In this study, we first establish proper settings for database search algorithms for the analysis of spectra in our gold benchmark dataset and then analyze the performance of ScanRanker, an algorithm for quality assessment of tandem MS spectra, on this ground truth data. We found that OMSSA and MSGFDB have limitations in their scoring functions but were able to form a proper consensus prediction using majority vote for our benchmark data. Unfortunately, ScanRanker's results do not correlate well with the consensus and ScanRanker is also too slow to be used in the capacity it is supposed to be used.","PeriodicalId":433206,"journal":{"name":"2013 8th International Symposium on Health Informatics and Bioinformatics","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121191196","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

Determination of the exact value of the regularization parameter in smoothness priors method with respect to the corresponding cut-off frequencies for designing filters 确定平滑先验法中正则化参数相对于相应截止频率的精确值，用于设计滤波器

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661683

Y. Isler

引用次数: 1

Period-doubling route to chaos in shunting inhibitory cellular neural networks 分流抑制细胞神经网络的倍周期混沌路径

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661682

M. Akhmet, M. O. Fen

引用次数: 0

A genetic algorithm approach to active subnetwork search applied to GWAS data 遗传算法在主动子网搜索中的应用

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661681

Ozan Ozisik, Burcu Bakir-Gungor, B. Diri, O. U. Sezerman

{"title":"A genetic algorithm approach to active subnetwork search applied to GWAS data","authors":"Ozan Ozisik, Burcu Bakir-Gungor, B. Diri, O. U. Sezerman","doi":"10.1109/HIBIT.2013.6661681","DOIUrl":"https://doi.org/10.1109/HIBIT.2013.6661681","url":null,"abstract":"An active subnetwork is a group of interconnected genes that show condition-specific differences. It has been observed that the gene products that have alterations associated with a disease of interest, incline to be part of the subnetworks among the overall interaction network. Hence, the integration of the interaction data with the genotypic data underlying disease states facilitates the separation of the subnetworks perturbed in a given disorder from the rest of the network. In the literature, active subnetwork search is used to discover disease related regulatory pathways, dysregulated genes, functional modules, cancer markers, to classify diseases, and to predict response to treatment. In this study, a genetic algorithm based method is developed for active subnetwork search and applied to WTCCC Rheumatoid Arthritis genome-wide association study dataset. The relevance of the identified subnetworks against the disease is compared in terms of biological pathways. Our results show that the proposed method works well in detecting the significant RA associated subnetworks, and it is also applicable to recognize subnetworks of other complex diseases.","PeriodicalId":433206,"journal":{"name":"2013 8th International Symposium on Health Informatics and Bioinformatics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125721297","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

Development of a social support intervention with a network of caregivers to find wandering Alzheimer's patients as soon as possible: A social computing application in healthcare 通过护理人员网络开发社会支持干预，以尽快发现流浪的阿尔茨海默病患者:医疗保健中的社会计算应用

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661678

Y. Yuce, K. H. Gulkesen

{"title":"Development of a social support intervention with a network of caregivers to find wandering Alzheimer's patients as soon as possible: A social computing application in healthcare","authors":"Y. Yuce, K. H. Gulkesen","doi":"10.1109/HIBIT.2013.6661678","DOIUrl":"https://doi.org/10.1109/HIBIT.2013.6661678","url":null,"abstract":"Locating and securing an Alzheimer's patient who is outdoors and in wandering state is crucial to patient's safety. Although advances in geotracking and mobile technology have made locating patients instantly possible, reaching them while in wandering state may still take time. However, a social network of caregivers may help shorten the time that it takes to reach and secure a wandering AD patient. This study proposes a social computing application in healthcare, which is designed to form and direct a social support network of caregivers for locating and securing wandering AD patients as soon as possible. The proposed system consists of three major components; a tracking device, a middleware and a mobile application. The tracking device has a Subscriber Identity Module for Global System for Mobile Communications Network (GSM) installed on it, and is responsible for communication between an AD patient and the system (e.g. transmission of location updates in varying periods). The middleware employs a supervision mechanism to detect potentially wandering patients, a tracking mechanism to locate a wandering patient and a coordination mechanism to communicate with and direct caregivers to wandering patient. The mobile application is the mediator of the interaction (e.g. necessary communication steps to get involved in the search of a wandering patient) between a caregiver and the system during a wandering patient search session. The communication backbone of the system involves the Internet and a GSM network. The major system component, i.e. middleware, is being implemented using Java. Family caregivers will be interviewed prior to and after the use of the system. In order to find out the impact of the system in terms of depression, anxiety and burden, Center For Epidemiologic Studies Depression Scale, Patient Health Questionnaire and Zarit Burden Interview will be applied to them during these interviews respectively.","PeriodicalId":433206,"journal":{"name":"2013 8th International Symposium on Health Informatics and Bioinformatics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131615367","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: 5

A dynamic Bayesian framwork to learn temporal gene interactions using external knowledge 利用外部知识学习时间基因相互作用的动态贝叶斯框架

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661680

U. Agyuz, S. Isci, C. Ozturk, A. Ademoglu, H. Otu

{"title":"A dynamic Bayesian framwork to learn temporal gene interactions using external knowledge","authors":"U. Agyuz, S. Isci, C. Ozturk, A. Ademoglu, H. Otu","doi":"10.1109/HIBIT.2013.6661680","DOIUrl":"https://doi.org/10.1109/HIBIT.2013.6661680","url":null,"abstract":"One of the main problems in systems biology is learning gene interaction networks from experimental data. This turns out to be a challenging task as the experimental data is sparse and noisy, and network learning algorithms are computationally intense. Bayesian Networks (BN) have become a popular choice for learning such networks as BNs avoid overfitting and are robust to noise. In this paper we build up on our established framework, Bayesian Network Prior, where we incorporate existing biological knowledge in learning gene interaction networks. However, biological phenomena are time-dependent and there is need to extend the static structure of learning approaches to a temporal level. Here, we present a Dynamic BN framework, which learns interaction networks between different time points in time-series data. Both intra and inter networks are learnt and compared to standard DBN learning algorithms. Our results based on synthetic and simulated gene expression data suggest that the proposed method outperforms existing approaches in identifying the underlying network structure. The proposed framework is robust to errors in the incorporated knowledge and can combine various experimental data types together with existing knowledge when learning networks.","PeriodicalId":433206,"journal":{"name":"2013 8th International Symposium on Health Informatics and Bioinformatics","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131494425","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

Use of open linked data in bioinformatics space: A case study 生物信息学空间中开放关联数据的使用:一个案例研究

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-11-14 DOI: 10.1109/HIBIT.2013.6661679

R. Çelebi, Ozgur Gumus, Yeşim AYDIN SON

引用次数: 3

Data mining for microrna gene prediction: On the impact of class imbalance and feature number for microrna gene prediction 微rna基因预测的数据挖掘:类不平衡和特征数对微rna基因预测的影响

2013 8th International Symposium on Health Informatics and Bioinformatics Pub Date : 2013-09-01 DOI: 10.1109/HIBIT.2013.6661685

Muserref Duygu Saçar, J. Allmer

{"title":"Data mining for microrna gene prediction: On the impact of class imbalance and feature number for microrna gene prediction","authors":"Muserref Duygu Saçar, J. Allmer","doi":"10.1109/HIBIT.2013.6661685","DOIUrl":"https://doi.org/10.1109/HIBIT.2013.6661685","url":null,"abstract":"MicroRNAs (miRNAs) are small, non-coding RNAs which are involved in the posttranscriptional modulation of gene expression. Their short (18-24) single stranded mature sequences are involved in targeting specific genes. It turns out that experimental methods are limited and that it is difficult, if not impossible, to establish all miRNAs and their targets experimentally. Therefore, many tools for the prediction of miRNA genes and miRNA targets have been proposed. Most of these tools are based on machine learning methods and within that area mostly two-class classification is employed. Unfortunately, truly negative data is impossible to attain and only approximations of negative data are currently available. Also, we recently showed that the available positive data is not flawless. Here we investigate the impact of class imbalance on the learner accuracy and find that there is a difference of up to 50% between the best and worst precision and recall values. In addition, we looked at increasing number of features and found a curve maximizing at 0.97 recall and 0.91 precision with quickly decaying performance after inclusion of more than 100 features.","PeriodicalId":433206,"journal":{"name":"2013 8th International Symposium on Health Informatics and Bioinformatics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122236302","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: 23