Gene Expression Databases and Data Mining

Anderle, Pascale; Duval, Manuel; Drăghici, Sorin; Littlejohn, Timothy G.; Medrano, Juan F.; Vilanova, David; Roberts, Matthew

doi:10.2144/mar03anderle

Cited by 28 publications

(18 citation statements)

References 34 publications

(27 reference statements)

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“…It contains high-throughput experimental data from functional research assessing conditional gene expression changes (32). It is a powerful tool to search the functional connection of novel proteins.…”

Section: Discussionmentioning

confidence: 99%

Analysis for Carom complex signaling and function by database mining

Liu¹,

Xiong²,

Thomas³

et al. 2016

Front Biosci

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Carom is a novel protein that regulates membrane curvature and transmits pathophysiological signaling. The tissue expression of Carom is unclear and its functional role and signaling are unknown. We employed a group of combined database mining strategies and established a working model of Carom signaling. We identified 26 Carom partners and established their expression profiles in human and mouse tissues. We classified three tiers of tissues for Carom/partner expression and found lymph node was the tier 1 tissue expressing Carom and most of its partners. Using GEO database, we discovered that four conditions (hypoxia, endometriosis, PPARγ deletion and iPSC reprogramming) altered Carom/partner expression in endothelial cells. We identified 26 Carom partner signalings by Ingenuity pathway analysis. Ten of the 26 pathways and three genes (ITSN1, UBC and HSPA5) were reported to be regulated in the above four conditions. Paired induction of Carom/ITSN1 elevation was associated with pathological angiogenesis. Whereas, paired reduction of Carom/HSPA5 or UBC was associated with iPSC generation. These results provide an insight on identifying Carom complex model and predicting its functional implications.

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Section: Discussionmentioning

confidence: 99%

Analysis for Carom complex signaling and function by database mining

Liu¹,

Xiong²,

Thomas³

et al. 2016

Front Biosci

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“…Additional academic and commercial software packages that are currently available for microarray analysis are shown in Table 1. Packages that are principally available as web tools or desktop applications are shown in Section 1 of the table, while Section 2 shows software that also possess databases for the storage of microarray data (reviewed in2, 17). In addition, statistical software can be tailored for the analysis of microarray data (listed in Section 3 of Table 1); e.g.…”

Section: Local Packagesmentioning

confidence: 99%

“…There are two major types of informatics solutions that are required for the management of microarray data: (a) software, usually installed locally, that allows storage, querying and analysis of data captured on‐site2, 17, 19; and (b) databases that act as repositories for publicly available data and, in particular, published data2, 9, 18, 19, 25, 30, 35, 40. In this article, we shall briefly address the local packages by giving a list of the main ones that are currently available, and then we shall concentrate on the latter databases by giving details about how to use them and what data they contain.…”

Section: Introductionmentioning

confidence: 99%

Navigating public microarray databases

Penkett

Bähler

2004

Comp Funct Genom

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With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources.

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“…Many machine learning and the data mining technologies have recently been introduced in the field of analyzing the microarray data to process many subsets of genes simultaneously Aizenberg et al 2002;Ooi and Tan 2003;Anderle et al 2003;Wren et al 2004). It is obvious that there is not a feasible approach to evaluate all the possible subsets of genes in a given dataset consisting of several thousands of genes.…”

Section: Introductionmentioning

confidence: 99%

Gene expression studies with DGL global optimization for the molecular classification of cancer

2010

Soft Comput

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This paper combines a powerful algorithm, called Dongguang Li (DGL) global optimization, with the methods of cancer diagnosis through gene selection and microarray analysis. A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is proposed and applied to two test cancer cases, colon and leukemia. The study attempts to analyze multiple sets of genes simultaneously, for an overall global solution to the gene's joint discriminative ability in assigning tumors to known classes. With the workable concepts and methodologies described here an accurate classification of the type and seriousness of cancer can be made. Using the orthogonal arrays for sampling and a search space reduction process, a computer program has been written that can operate on a personal laptop computer. Both the colon cancer and the leukemia microarray data can be classified 100% correctly without previous knowledge of their classes. The classification processes are automated after the gene expression data being inputted. Instead of examining a single gene at a time, the DGL method can find the global optimum solutions and construct a multi-subsets pyramidal hierarchy class predictor containing up to 23 gene subsets based on a given microarray gene expression data collection within a period of several hours. An automatically derived class predictor makes the reliable cancer classification and accurate tumor diagnosis in clinical practice possible.

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Gene Expression Databases and Data Mining

Cited by 28 publications

References 34 publications

Analysis for Carom complex signaling and function by database mining

Analysis for Carom complex signaling and function by database mining

Navigating public microarray databases

Gene expression studies with DGL global optimization for the molecular classification of cancer

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