Journal of Data Mining in Genomics & Proteomics最新文献_第8页

A Case Study on Discovery of Novel Citrus Leprosis Virus Cytoplasmic Type 2 Utilizing Small RNA Libraries by Next Generation Sequencing and Bioinformatic Analyses 利用小RNA文库新一代测序和生物信息学分析发现新型柑橘麻风病毒细胞质2型

Journal of Data Mining in Genomics & Proteomics Pub Date : 2016-01-01 DOI: 10.4172/2153-0602.1000129

A. Roy, J. Shao, J. Hartung, W. Schneider, R. Brlansky

{"title":"A Case Study on Discovery of Novel Citrus Leprosis Virus Cytoplasmic Type 2 Utilizing Small RNA Libraries by Next Generation Sequencing and Bioinformatic Analyses","authors":"A. Roy, J. Shao, J. Hartung, W. Schneider, R. Brlansky","doi":"10.4172/2153-0602.1000129","DOIUrl":"https://doi.org/10.4172/2153-0602.1000129","url":null,"abstract":"The advent of innovative sequencing technology referred to as “Next-Generation” Sequencing (NGS), provides a new approach to identify the ‘unknown known’ and ‘unknown unknown’ viral pathogens without a priori knowledge. The genomes of plant viruses can be rapidly determined even when occurring at extremely low titers in the infected host. The method is based on massively parallel sequencing of the population of small RNA molecules 18-35 nucleotides in length produced by RNA silencing host defense. Improvements in chemistries, bioinformatic tools and advances in engineering has reduced the costs of NGS, increased its accessibility, and enabled its application in the field of plant virology. In this review, we discuss the utilization of the Illumina GA IIX platform combined with the application of molecular biology and bioinformatic tools for the discovery of a novel cytoplasmic Citrus leprosis virus (CiLV). This new virus produced symptoms typical of CiLV but was not detected with either serological or PCR-based assays for the previously described virus. The new viral genome was also present in low titer in sweet orange (Citrus sinensis), an important horticultural crop with incomplete genomic resources. This is a common situation in horticultural research and provides an example of the broader utility of this approach. In addition to the discovery of novel viruses, the sequence data may be useful for studies of viral evolution and ecology and the interactions between viral and host transcriptomes.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"19 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76838281","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: 16

Generalized Measure of Dependency for Analysis of Omics Data 组学数据分析的广义依赖度量

Journal of Data Mining in Genomics & Proteomics Pub Date : 2016-01-01 DOI: 10.4172/2153-0602.1000183

Qihua Tan, Martin Tepel, Hans Christian Beck, Lars Melholt Rasmussen, Jacob v. B. Hjelmborg

{"title":"Generalized Measure of Dependency for Analysis of Omics Data","authors":"Qihua Tan, Martin Tepel, Hans Christian Beck, Lars Melholt Rasmussen, Jacob v. B. Hjelmborg","doi":"10.4172/2153-0602.1000183","DOIUrl":"https://doi.org/10.4172/2153-0602.1000183","url":null,"abstract":"J Data Mining Genomics Proteomics ISSN: 2153-0602 JDMGP, an open access journal Volume 7 • Issue 1 • 1000183 As a popular measure of association, the Pearson’s correlation coefficient has been frequently used in omics data analysis e.g. in feature selection process during prediction model building using high dimensional gene expression data [1] and proteomics data [2]. However, Pearson’s correlation coefficient captures only linear relationships which greatly limit its use in situations of nonlinear association. Statistical modeling for dealing with nonlinear patterns can be complicated [3] and requires intensive computation in case of high dimensional data such as microarray data or genome sequence data. In the analysis of omics data, high dimension means that there can be diverse patterns of dependence not limited to linearity. In this situation, the generalized measures of association more adequate than the Pearson’s correlation and capable of capturing both linear and nonlinear correlations are needed. Recently, generalized correlation coefficients have been frequently discussed [4] and their application to large scale genomic data illustrated through microarray gene expression time-course analysis [5].","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"11 1","pages":"1000183"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84274963","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

Proteomics in Medicine 医学中的蛋白质组学

Journal of Data Mining in Genomics & Proteomics Pub Date : 2016-01-01 DOI: 10.4172/2153-0602.1000e126

M. Simonian

引用次数: 2

Comparative Genomics of Salmonella Could Reveal Key Features of Adaptation 沙门氏菌的比较基因组学可以揭示适应的关键特征

Journal of Data Mining in Genomics & Proteomics Pub Date : 2016-01-01 DOI: 10.4172/2153-0602.1000E121

G. Nava, Yajaira Esquivel-Hern, Ez

引用次数: 5

Interpretable Boosted Decision Trees for Prediction of Mortality Following Allogeneic Hematopoietic Stem Cell Transplantation 异体造血干细胞移植后死亡率预测的可解释增强决策树

Journal of Data Mining in Genomics & Proteomics Pub Date : 2016-01-01 DOI: 10.4172/2153-0602.1000184

R. Shouval, A. Nagler, M. Labopin, R. Unger

引用次数: 5

Data Mining and Geo-Engineering 数据挖掘与地球工程

Journal of Data Mining in Genomics & Proteomics Pub Date : 2015-12-17 DOI: 10.4172/2153-0602.C1.001

Luis Sousa

引用次数: 0

In the Race towards a Better Diagnosis and Prognostication of Cancer Patients Long Non-Coding Intergenic RNA's (lincrna's) have found their Place 在对癌症患者进行更好的诊断和预后的竞赛中，长链非编码基因间RNA (lincrna’s)已经找到了自己的位置

Journal of Data Mining in Genomics & Proteomics Pub Date : 2015-10-31 DOI: 10.4172/2153-0602.1000E120

J. Mao, H. Weier

引用次数: 0

Dengue Fever Prediction: A Data Mining Problem 登革热预测:一个数据挖掘问题

Journal of Data Mining in Genomics & Proteomics Pub Date : 2015-10-25 DOI: 10.4172/2153-0602.1000181

K. Shaukat, N. Masood, S. Mehreen, Ulya Azmeen

引用次数: 53

Genome Mining and Transcriptional Analysis of Bacteriocin Genes in Enterococcus faecium CRL1879 粪肠球菌CRL1879细菌素基因的基因组挖掘与转录分析

Journal of Data Mining in Genomics & Proteomics Pub Date : 2015-10-18 DOI: 10.4172/2153-0602.1000180

N. Suárez, J. Bonacina, E. Hebert, L. Saavedra

{"title":"Genome Mining and Transcriptional Analysis of Bacteriocin Genes in Enterococcus faecium CRL1879","authors":"N. Suárez, J. Bonacina, E. Hebert, L. Saavedra","doi":"10.4172/2153-0602.1000180","DOIUrl":"https://doi.org/10.4172/2153-0602.1000180","url":null,"abstract":"Among 151 bacterial isolates from nine artisanal cheeses, Enterococcus faecium CRL 1879 showed antibacterial activity against the food-borne pathogen Listeria monocytogenes. The isolate produced a proteinase K-sensitive compound in the cell free supernatant. Genome analysis demonstrated the presence of enterocin A, enterocin B, enterocin P, enterocin SE-K4-like and enterocin X biosynthetic gene clusters. Nucleotide sequences encoding for a putative two-component bacteriocin were detected using bioinformatics tools, here named enterocin CRL1879αβ. A transcriptional analysis of all bacteriocin genes by quantitative real time PCR analysis (qRT-PCR) revealed the transcription of each enterocin gene at different levels. Finally, analysis of bacteriocin genes distribution in 251 E. faecium bioprojects was performed and compared to those identify in E. faecium CRL1879. The discriminative analysis demonstrated that bacteriocin genes are widely distributed among Enterococcus, independently of the origin of the strain. \u0000The results presented in this paper represent a unique finding since this is the first demonstration of an E. faecium strain isolated from an artisanal cheese with the complete genetic machinery to produce six classes II and one class III bacteriocins.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"32 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2015-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84794603","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: 8

Leveraging Lymphoblastoid Cell Lines for Drug Response Modeling 利用淋巴母细胞样细胞系进行药物反应建模

Journal of Data Mining in Genomics & Proteomics Pub Date : 2015-09-09 DOI: 10.4172/2153-0602.1000179

A. Motsinger-Reif, Daniel M. Rotroff

引用次数: 0