共查询到20条相似文献,搜索用时 31 毫秒
1.
Background
With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. 相似文献2.
Background
Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our aim was to develop a software program that could facilitate the combining of data from heterogeneous sources, and thus allow researchers to perform genomic cross-platform/cross-species studies and to use existing experimental data for compendium studies. 相似文献3.
Background
Biological studies involve a growing number of distinct high-throughput experiments to characterize samples of interest. There is a lack of methods to visualize these different genomic datasets in a versatile manner. In addition, genomic data analysis requires integrated visualization of experimental data along with constantly changing genomic annotation and statistical analyses. 相似文献4.
Background
Biologists often conduct multiple but different cDNA microarray studies that all target the same biological system or pathway. Within each study, replicate slides within repeated identical experiments are often produced. Pooling information across studies can help more accurately identify true target genes. Here, we introduce a method to integrate multiple independent studies efficiently. 相似文献5.
Rok Kosir Jure Acimovic Marko Golicnik Martina Perse Gregor Majdic Martina Fink Damjana Rozman 《BMC molecular biology》2010,11(1):60
Background
Circadian rhythms have a profound effect on human health. Their disruption can lead to serious pathologies, such as cancer and obesity. Gene expression studies in these pathologies are often studied in different mouse strains by quantitative real time polymerase chain reaction (qPCR). Selection of reference genes is a crucial step of qPCR experiments. Recent studies show that reference gene stability can vary between species and tissues, but none has taken circadian experiments into consideration. 相似文献6.
Annie Glatigny Hervé Delacroix Thomas Tang Nicolas François Lawrence Aggerbeck Marie-Hélène Mucchielli-Giorgi 《BMC bioinformatics》2009,10(1):1-12
Background
In cancer studies, it is common that multiple microarray experiments are conducted to measure the same clinical outcome and expressions of the same set of genes. An important goal of such experiments is to identify a subset of genes that can potentially serve as predictive markers for cancer development and progression. Analyses of individual experiments may lead to unreliable gene selection results because of the small sample sizes. Meta analysis can be used to pool multiple experiments, increase statistical power, and achieve more reliable gene selection. The meta analysis of cancer microarray data is challenging because of the high dimensionality of gene expressions and the differences in experimental settings amongst different experiments. 相似文献7.
Background
Gene expression studies increasingly compare expression responses between different experimental backgrounds (genetic, physiological, or phylogenetic). By focusing on dynamic responses rather than a direct comparison of static expression levels, this type of study allows a finer dissection of primary and secondary regulatory effects in the various backgrounds. Usually, results of such experiments are presented in the form of Venn diagrams, which are intuitive and visually appealing, but lack a statistical foundation. 相似文献8.
9.
Validation of internal control for gene expression study in soybean by quantitative real-time PCR 总被引:3,自引:0,他引:3
Background
Normalizing to housekeeping gene (HKG) can make results from quantitative real-time PCR (qRT-PCR) more reliable. Recent studies have shown that no single HKG is universal for all experiments. Thus, a suitable HKG should be selected before its use. Only a few studies on HKGs have been done in plants, and none in soybean, an economically important crop. Therefore, the present study was conducted to identify suitable HKG(s) for normalization of gene expression in soybean. 相似文献10.
11.
Ki-Yeol Kim Dong Hyuk Ki Ha Jin Jeong Hei-Cheul Jeung Hyun Cheol Chung Sun Young Rha 《BMC bioinformatics》2007,8(1):218
Background
With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Such systematic differences present a substantial obstacle to the analysis of microarray data, resulting in inconsistent and unreliable information. Therefore, one of the most pressing challenges in the field of microarray technology is how to integrate results from different microarray experiments or combine data sets prior to the specific analysis. 相似文献12.
13.
Hans-Ulrich Klein Christian Ruckert Alexander Kohlmann Lars Bullinger Christian Thiede Torsten Haferlach Martin Dugas 《BMC bioinformatics》2009,10(1):422
Background
Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. 相似文献14.
15.
Mark D Robinson David P De Souza Woon Wai Keen Eleanor C Saunders Malcolm J McConville Terence P Speed Vladimir A Likić 《BMC bioinformatics》2007,8(1):419
Background
Gas chromatography-mass spectrometry (GC-MS) is a robust platform for the profiling of certain classes of small molecules in biological samples. When multiple samples are profiled, including replicates of the same sample and/or different sample states, one needs to account for retention time drifts between experiments. This can be achieved either by the alignment of chromatographic profiles prior to peak detection, or by matching signal peaks after they have been extracted from chromatogram data matrices. Automated retention time correction is particularly important in non-targeted profiling studies. 相似文献16.
Background
Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. 相似文献17.
Background
The proteomics literature has seen a proliferation of publications that seek to apply the rapidly improving technology of 2D gels to study various biological systems. However, there is a dearth of systematic studies that have investigated appropriate statistical approaches to analyse the data from these experiments. 相似文献18.
Francesca Demichelis Paolo Magni Paolo Piergiorgi Mark A Rubin Riccardo Bellazzi 《BMC bioinformatics》2006,7(1):514
Background
Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA) experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples. 相似文献19.
Matthew E Ritchie Dileepa Diyagama Jody Neilson Ryan van Laar Alexander Dobrovic Andrew Holloway Gordon K Smyth 《BMC bioinformatics》2006,7(1):261-16
Background
Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or "filtered" from further analysis to avoid misleading results. 相似文献20.
Geert Zegels Geert AA Van Raemdonck Edmond P Coen Wiebren AA Tjalma Xaveer WM Van Ostade 《Proteome science》2009,7(1):17-16