International Journal of Data Mining and Bioinformatics最新文献_第9页

Identifying susceptibility networks for drug-induced non-immune neutropenia. 确定药物诱导的非免疫性中性粒细胞减少的易感性网络。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.066339

Kaushal Desai, David Brott, Xiaohua Hu, Anastasia Christianson

引用次数: 0

The effect of SNPs on expression levels in Nimblegen RNA expression microarrays. snp对Nimblegen RNA表达芯片表达水平的影响。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.068949

Sigrun Helga Lund, Asgeir Sigurdsson, Sigurjon Axel Gudjonsson, Julius Gudmundsson, Daniel Fannar Gudbjartsson, Thorunn Rafnar, Kari Stefansson, Gunnar Stefansson

{"title":"The effect of SNPs on expression levels in Nimblegen RNA expression microarrays.","authors":"Sigrun Helga Lund, Asgeir Sigurdsson, Sigurjon Axel Gudjonsson, Julius Gudmundsson, Daniel Fannar Gudbjartsson, Thorunn Rafnar, Kari Stefansson, Gunnar Stefansson","doi":"10.1504/ijdmb.2015.068949","DOIUrl":"https://doi.org/10.1504/ijdmb.2015.068949","url":null,"abstract":"In this paper the effect of SNPs on expression levels in Nimblegen RNA expression microarrays is investigated. A vast number of replicates of probe pairs representing both alleles of SNPs on 14 loci allows accurate estimation of the difference in signal intensities both within and between probe pairs. The majority of probe-pairs with sufficiently high expression have significant differences in expression levels within the pair and the difference shows concordance with the genotype of the samples. With two or more replicates of each probe, the allele-to-allele variance dominates the error in estimating the difference within the probe-pair, ten replicates are needed for adequate power in calling a true difference within a single probe-pair. Using the expression level of the probe within the probe-pair that has the higher value gives more accurate estimates. When using probes at loci containing known SNP's one should use probes containing both alleles of the SNP.","PeriodicalId":54964,"journal":{"name":"International Journal of Data Mining and Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/ijdmb.2015.068949","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34106976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new algorithm for essential proteins identification based on the integration of protein complex co-expression information and edge clustering coefficient. 基于蛋白质复合体共表达信息和边缘聚类系数的必需蛋白识别新算法。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.069654

Jiawei Luo, Juan Wu

引用次数: 13

Minimum Bayesian error probability-based gene subset selection. 基于最小贝叶斯误差概率的基因子集选择。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.070056

Jian Li, Tian Yu, Jin-Mao Wei

{"title":"Minimum Bayesian error probability-based gene subset selection.","authors":"Jian Li, Tian Yu, Jin-Mao Wei","doi":"10.1504/ijdmb.2015.070056","DOIUrl":"https://doi.org/10.1504/ijdmb.2015.070056","url":null,"abstract":"Sifting functional genes is crucial to the new strategies for drug discovery and prospective patient-tailored therapy. Generally, simply generating gene subset by selecting the top k individually superior genes may obtain an inferior gene combination, for some selected genes may be redundant with respect to some others. In this paper, we propose to select gene subset based on the criterion of minimum Bayesian error probability. The method dynamically evaluates all available genes and sifts only one gene at a time. A gene is selected if its combination with the other selected genes can gain better classification information. Within the generated gene subset, each individual gene is the most discriminative one in comparison with those that classify cancers in the same way as this gene does and different genes are more discriminative in combination than in individual. The genes selected in this way are likely to be functional ones from the system biology perspective, for genes tend to co-regulate rather than regulate individually. Experimental results show that the classifiers induced based on this method are capable of classifying cancers with high accuracy, while only a small number of genes are involved.","PeriodicalId":54964,"journal":{"name":"International Journal of Data Mining and Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/ijdmb.2015.070056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34192167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Condensing position-specific scoring matrixs by the Kidera factors for ligand-binding site prediction. 用Kidera因子凝聚位置特异性评分矩阵，用于配体结合位点预测。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.068954

Chun Fang, Tamotsu Noguchi, Hayato Yamana

引用次数: 3

Automatic extraction of reference gene from literature in plants based on texting mining. 基于文本挖掘的植物文献内参基因自动提取。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.070063

Lin He, Gengyu Shen, Fei Li, Shuiqing Huang

引用次数: 1

A new approach for detecting fungal and oomycete plant pathogens in next generation sequencing metagenome data utilising electronic probes. 利用电子探针检测下一代宏基因组测序数据中真菌和卵菌植物病原体的新方法。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.069422

Andres Espindola, William Schneider, Peter R Hoyt, Stephen M Marek, Carla Garzon

{"title":"A new approach for detecting fungal and oomycete plant pathogens in next generation sequencing metagenome data utilising electronic probes.","authors":"Andres Espindola, William Schneider, Peter R Hoyt, Stephen M Marek, Carla Garzon","doi":"10.1504/ijdmb.2015.069422","DOIUrl":"https://doi.org/10.1504/ijdmb.2015.069422","url":null,"abstract":"Early stage infections caused by fungal/oomycete spores may not be detected until signs or symptoms develop. Serological and molecular techniques are currently used for detecting these pathogens. Next-generation sequencing (NGS) has potential as a diagnostic tool, due to the capacity to target multiple unique signature loci of pathogens in an infected plant metagenome. NGS has significant potential for diagnosis of important eukaryotic plant pathogens. However, the assembly and analysis of huge amounts of sequence is laborious, time consuming, and not necessary for diagnostic purposes. Previous work demonstrated that a bioinformatic tool termed Electronic probe Diagnostic Nucleic acid Analysis (EDNA) had potential for greatly simplifying detecting fungal and oomycete plant pathogens in simulated metagenomes. The initial study demonstrated limitations for detection accuracy related to the analysis of matches between queries and metagenome reads. This study is a modification of EDNA demonstrating a better accuracy for detecting fungal and oomycete plant pathogens.","PeriodicalId":54964,"journal":{"name":"International Journal of Data Mining and Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/ijdmb.2015.069422","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34192169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

CORE: core-based synthetic minority over-sampling and borderline majority under-sampling technique. CORE:基于核的合成少数过采样和边缘多数欠采样技术。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.068952

Chumphol Bunkhumpornpat, Krung Sinapiromsaran

引用次数: 8

A comparative study on network motif discovery algorithms. 网络motif发现算法的比较研究。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.066777

Yusuf Kavurucu

引用次数: 8

Meta-learning framework applied in bioinformatics inference system design. 元学习框架在生物信息学推理系统设计中的应用。

IF 0.3 4区生物学

International Journal of Data Mining and Bioinformatics Pub Date : 2015-01-01 DOI: 10.1504/ijdmb.2015.066775

Tomás Arredondo, Wladimir Ormazábal

引用次数: 3