Applied bioinformatics最新文献_第3页

Prediction of signal peptides using bio-basis function neural networks and decision trees. 基于生物基函数神经网络和决策树的信号肽预测。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605010-00002

Ateesh Sidhu, Zheng Rong Yang

引用次数: 13

MHCPred 2.0: an updated quantitative T-cell epitope prediction server. MHCPred 2.0:一个更新的定量t细胞表位预测服务器。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605010-00008

Pingping Guan, Channa K Hattotuwagama, Irini A Doytchinova, Darren R Flower

{"title":"MHCPred 2.0: an updated quantitative T-cell epitope prediction server.","authors":"Pingping Guan, Channa K Hattotuwagama, Irini A Doytchinova, Darren R Flower","doi":"10.2165/00822942-200605010-00008","DOIUrl":"https://doi.org/10.2165/00822942-200605010-00008","url":null,"abstract":"Unlabelled: The accurate computational prediction of T-cell epitopes can greatly reduce the experimental overhead implicit in candidate epitope identification within genomic sequences. In this article we present MHCPred 2.0, an enhanced version of our online, quantitative T-cell epitope prediction server. The previous version of MHCPred included mostly alleles from the human leukocyte antigen A (HLA-A) locus. In MHCPred 2.0, mouse models are added and computational constraints removed. Currently the server includes 11 human HLA class I, three human HLA class II, and three mouse class I models. Additionally, a binding model for the human transporter associated with antigen processing (TAP) is incorporated into the new MHCPred. A tool for the design of heteroclitic peptides is also included within the server. To refine the veracity of binding affinities prediction, a confidence percentage is also now calculated for each peptide predicted.Availability: As previously, MHCPred 2.0 is freely available at the URL http://www.jenner.ac.uk/MHCPred/Contact: Darren R. Flower (darren.flower@jenner.ac.uk).","PeriodicalId":87049,"journal":{"name":"Applied bioinformatics","volume":"5 1","pages":"55-61"},"PeriodicalIF":0.0,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2165/00822942-200605010-00008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25908652","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: 67

OligoMatcher: analysis and selection of specific oligonucleotide sequences for gene silencing by antisense or siRNA. OligoMatcher:分析和选择用于反义或siRNA基因沉默的特定寡核苷酸序列。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605020-00008

SudhaRani Mamidipalli, Mathew Palakal, Shuyu Li

引用次数: 1

RefSeq refinements of UniGene-based gene matching improve the correlation of expression measurements between two microarray platforms. 基于ungene的基因匹配的RefSeq改进提高了两个微阵列平台之间表达测量的相关性。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605020-00003

Yuan Ji, Kevin Coombes, Jiexin Zhang, Sijin Wen, James Mitchell, Lajos Pusztai, W Fraser Symmans, Jing Wang

{"title":"RefSeq refinements of UniGene-based gene matching improve the correlation of expression measurements between two microarray platforms.","authors":"Yuan Ji, Kevin Coombes, Jiexin Zhang, Sijin Wen, James Mitchell, Lajos Pusztai, W Fraser Symmans, Jing Wang","doi":"10.2165/00822942-200605020-00003","DOIUrl":"https://doi.org/10.2165/00822942-200605020-00003","url":null,"abstract":"Matching genes across microarray platforms is a critical step in meta-analysis. Standard practice uses UniGene to match genes. Numerous studies have found poor correlations between platforms when using UniGene matching. We profiled samples from 33 breast cancer patients on two different microarray platforms (Affymetrix and cDNA) and investigated gene matching. Our results confirmed that UniGene-based matching led to poor correlations of gene expression between platforms. Using RefSeq, a database maintained by the National Center for Biotechnology Information (NCBI), we developed and implemented a new method to refine gene matching. We found that the correlations between gene expression measurements were substantially higher after the RefSeq matching. Our approach differs from previously reported sequence-matching approaches and retains useful expression measurements. It is a sensible approach for matching probes across platforms. We conclude that UniGene alone is insufficient to match genes across platforms. Refined matching based on RefSeq significantly improves the quality of matches.","PeriodicalId":87049,"journal":{"name":"Applied bioinformatics","volume":"5 2","pages":"89-98"},"PeriodicalIF":0.0,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2165/00822942-200605020-00003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"26041958","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: 10

TimeView: for comparative gene expression analysis. TimeView:用于比较基因表达分析。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605010-00005

Mugdha Gadgil, Sarika Mehra, Vivek Kapur, Wei-Shou Hu

引用次数: 3

Simulation study of ratio calculation formulae of two-colour cDNA microarray data. 双色cDNA芯片数据比例计算公式的仿真研究。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605040-00008

Hui Jia, Le Lu, Shiau-Chuen Hng, Jinming Li

{"title":"Simulation study of ratio calculation formulae of two-colour cDNA microarray data.","authors":"Hui Jia, Le Lu, Shiau-Chuen Hng, Jinming Li","doi":"10.2165/00822942-200605040-00008","DOIUrl":"https://doi.org/10.2165/00822942-200605040-00008","url":null,"abstract":"In cDNA microarray image processing, there are different methods for calculating the channel ratios. Standard microarray image analysis software, such as the Axon GenePix Pro, calculate the channel ratio from pixels that define a given spot using different methods (i.e. ratio of means, ratio of medians, mean of ratios, median of ratios, and regression ratio). Ratio values calculated using the different methods will then be listed in an output file. Microarray users have to choose one of the available methods at their own discretion, as no guidelines are provided. Therefore, we aim to address one of the most frequently asked questions by the microarray users: which ratio quantity provided by the image analysis software should be used? In this study, we have evaluated the five different ratio calculation approaches using simulation studies. Our results suggest that in most circumstances the ratio of means appears to be the best approach, particularly when the coefficient of variance (CV) of two-channel pixel intensities are small (<0.5) and channel intensities are large. Conversely, the ratio of medians and the median of ratios are more favourable when the CV is large.","PeriodicalId":87049,"journal":{"name":"Applied bioinformatics","volume":"5 4","pages":"255-66"},"PeriodicalIF":0.0,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2165/00822942-200605040-00008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"26473709","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: 2

AMarge: Automated Extensive Quality Assessment of Affymetrix chips. amrange: Affymetrix芯片的自动化广泛质量评估。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605010-00006

Juan José Lozano, Susana G Kalko

引用次数: 7

WebaCGH: an interactive online tool for the analysis and display of array comparative genomic hybridisation data. webgh:用于分析和显示阵列比较基因组杂交数据的交互式在线工具。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605020-00009

Casey Frankenberger, Xiaolin Wu, Jerry Harmon, Deanna Church, Lisa M Gangi, David J Munroe, Ulises Urzúa

{"title":"WebaCGH: an interactive online tool for the analysis and display of array comparative genomic hybridisation data.","authors":"Casey Frankenberger, Xiaolin Wu, Jerry Harmon, Deanna Church, Lisa M Gangi, David J Munroe, Ulises Urzúa","doi":"10.2165/00822942-200605020-00009","DOIUrl":"https://doi.org/10.2165/00822942-200605020-00009","url":null,"abstract":"Unlabelled: Gene copy number variations occur both in normal cells and in numerous pathologies including cancer and developmental diseases. Array comparative genomic hybridisation (aCGH) is an emerging technology that allows detection of chromosomal gains and losses in a high-resolution format. When aCGH is performed on cDNA and oligonucleotide microarrays, the impact of DNA copy number on gene transcription profiles may be directly compared. We have created an online software tool, WebaCGH, that functions to (i) upload aCGH and gene transcription results from multiple experiments; (ii) identify significant aberrant regions using a local Z-score threshold in user-selected chromosomal segments subjected to smoothing with moving averages; and (iii) display results in a graphical format with full genome and individual chromosome views. In the individual chromosome display, data can be zoomed in/out in both dimensions (i.e. ratio and physical location) and plotted features can have 'mouse over' linking to outside databases to identify loci of interest. Uploaded data can be stored indefinitely for subsequent retrieval and analysis. WebaCGH was created as a Java-based web application using the open-source database MySQL.Availability: WebaCGH is freely accessible at http://129.43.22.27/WebaCGH/welcome.htmContact: Xiaolin Wu (forestwu@mail.nih.gov) or Ulises Urzúa (uurzua@med.uchile.cl).","PeriodicalId":87049,"journal":{"name":"Applied bioinformatics","volume":"5 2","pages":"125-30"},"PeriodicalIF":0.0,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2165/00822942-200605020-00009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"26044074","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: 6

Modeling oligonucleotide microarray signals. 寡核苷酸微阵列信号建模。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605030-00003

Yongqing Zhang, Antonio Ferreira, Cheng Cheng, Yongchun Wu, Jiong Zhang

引用次数: 2

Alternative mRNA polyadenylation can potentially affect detection of gene expression by affymetrix genechip arrays. 替代mRNA聚腺苷化可以潜在地影响检测基因表达affymetrix基因芯片阵列。

Applied bioinformatics Pub Date : 2006-01-01 DOI: 10.2165/00822942-200605040-00007

Veera D'mello, Ju Y Lee, Clinton C MacDonald, Bin Tian

引用次数: 16