... analysis for geneexpression data: a survey,” IEEE Transactions on Knowledge and Data Engineering, vol 16, no 11, pp 1370–1386, 2004 [2] M H Asyali, D Colak, O Demirkaya, and M S Inan, Geneexpression ... sampled geneexpression time-series data, ” Fuzzy Sets and Systems, vol 152, no 1, pp 49–66, 2005 [10] R Balasubramaniyan, E H¨ llermeier, N Weskamp, and J u K¨ mper, “Clustering of geneexpressiondata ... Scale factor 1 1 0.25 0.25 1 0.25 0.25 Table 2: Standard deviation vectors for clusters in “low-noise” sample datasets Table 4: Subcluster replicates and total vector sizes for “high-noise” datasets...
... temporal geneexpressiondata are readily available, methods and strategies for analysis of these complex data sets are still emerging Because the unique feature of temporal geneexpressiondata ... extract expression patterns in temporal geneexpressiondata with continuous wavelet analysis It has been demonstrated that the application of wavelet transformation to gene temporal expressiondata ... by SAS and Matlab 3.1 RESULT AND ANALYSIS The variation of geneexpression profile A large data set was generated from a unique geneexpression experiment where activity of the promoter of the...
... data SSM on undersampled data SSM on interpolated data CoD on original data CoD on undersampled data CoD on interpolated data Edges inferred fnew flost 14 —— 12 —————— 2 on whether these frameworks ... each geneGene symbol Change point I Change point II Change point III Bmp7 Rara Pax2 Gata3 Gata2 Gdf11 Npnt Cd44 Pgf Pbx1 Ret 6 ——— 5 — 10 11 12 — 10 12 11 11 12 10 12 16 15 12 18 20 16 15 — 20 ... Consider N geneexpression profiles, g (1) , g (2) , , g (N) ∈ RT , T being the length of each gene s temporal expression profile (as obtained from microarray expression) The jth time instant of gene...
... multidimensional geneexpressiondata which have been subjected to clustering algorithms We first compared heatmaps obtained on two different data matrices: the matrix of discretized smoothed geneexpression ... time series geneexpression data, ” Bioinformatics, vol 21, supplement 1, pp i159–i168, 2005 [7] C D Giurcˇ neanu, I Tˇ bus, and J Astola, “Clustering time a a ¸ series geneexpressiondata based ... clustering geneexpression data, ” Bioinformatics, vol 17, no 9, pp 763–774, 2001 [21] H Chipman, T J Hastie, and T Tibshirani, “Clustering microarray data, ” in Statistical Analysis of Gene Expression...
... M2 M2 ———————— 57 AML BM — M2 F B133 60 AML BM — M2 M B141 31 50 AML AML BM BM —— M4 M4 —— B142 54 AML BM — M4 F 36 30 AML AML BM BM —— M5 M5 —— B211 Samples B132 63 AML PB —— F B212 ... BM —— M 65 AML BM —— M 35 38 61 32 AML AML AML AML BM BM BM BM ———— M1 M1 M1 M1 ———— B131 58 34 28 37 51 29 33 53 AML AML AML AML AML AML AML AML BM BM BM BM BM BM BM BM ———————— ... B-cell B-cell B-cell B-cell B-cell B-cell B-cell B-cell B-cell B-cell B-cell ——————————————————— F F F F F F F F F F F F F F F F F F F A113 17 16 21 45 22 25 24 47 49 ALL ALL...
... their expression level The cDNA microarray experiments provide the data and a “genomic” viewpoint on geneexpression There exist two different types of geneexpressiondata to reconstruct gene ... measurement of each gene This means that the more number of genes a particular gene regulates, the more important this gene is In geneexpression analysis, a gene is considered as a factor causing ... Technology 14 1.4.1 Pre-processing step on raw data Arising from Step of the overall analysis process is the geneexpressiondata The quality of geneexpressiondata strongly depends on the equiments...
... meaning from high throughput data ExpressionPlot offers the geneexpression community an easy-to-use tool for automated analysis of geneexpression and RNA processing data The back end offers a ... (FASTQ files) or Affymetrix array data (CEL files), completed alignments (BAM files), or tables of geneexpression values and changes generated by other back ends Once data are pre-processed, the webbased ... plot changes in geneexpression and RNA processing, browse hyperlinked tables of changed genes and splicing events, generate read plots from a genomic view, compare different datasets (including...
... plant geneexpressiondata BMC Syst Biol 2007, 1:37 Shimamura T, Imoto S, Yamaguchi R, Fujita A, Nagasaki M, Miyano S: Recursive regularization for inferring gene networks from time-course geneexpression ... time-course geneexpressiondata Biostatistics 2007, 8:507-525 Shiraishi Y, Kimura S, Okada M: Inferring cluster-based networks from differently stimulated multiple time-course geneexpressiondata ... high if gene- gene relationships were considered, but the presented approach is based on cluster centroid expression profiles, which in turn represent the expression trend of sets of genes and...
... 10-4 Lung enrichment, microarray data (P-value) 10-5 0.4 Figure Identification of putative microvessel-enriched miRNAs using public expressiondata (a) Table of datasets included in the analysis ... compendia with microarray data from mouse tissues, including lung [17,18], were downloaded from the NCBI GeneExpression Omnibus repository To ensure consistent mapping between datasets, clone/probe ... 2009, (a) Dataset Mature miRNAs n/a Landgraf et al small RNA sequence library 429 65 Thompson et al microarray dataset 115 Beuvink et al microarray dataset 136 Annotation: 0.1 miRBase r10.1 Expression: ...
... human genes We used 2,000 genes with the highest minimal intensity across the samples selected by [25] SRBCT The SRBCT data [5] contains gene- expressiondata from cDNA microarrays of 2308 genes ... acute myeloid leukemia (AML) with the expression levels of 7,129 genes Colon The Colon data contains expression levels of 40 tumor and 22 normal colon tissues The data was analyzed with an Affymetrix ... simulated data We used a noisy version of the simulated data in [23] The original data assumes three different normal distributions for both insignificant genes (null cases) and significant genes...
... here treat one geneexpression as a random variable, and construct the distribution of the gene expressions of gene i We then choose a subset of genes whose distributions of the gene expressions ... three geneexpressiondata sets containing missing values and compared the overlapped degree between the gene clusters for incomplete data sets and the ones for complete data sets These three data ... (WDCM) for clustering geneexpressiondata It is based on the idea that a group of genes tend to be clustered together if the distributions of gene expressions of these genes belong to the common...
... markers from heterogeneous collections of samples of DNA microarray data of geneexpression We have applied this method to a highly heterogeneous set of stem cell geneexpression data, with the objective ... NCBI gene annotation data [ftp://ftp.ncbi.nih.gov /gene/ DATA/ gene2 go.gz] Tavazoie S, Hughes JD, Campbell MJ, Cho RJ, Church GM: Systematic determination of genetic network architecture Nat Genet ... methodology that uses large heterogeneous geneexpression datasets to identify genes that can function as markers In summary, we examine the distribution of expression values of each probe set...
... by transcription factors We consider a data set with genes, the expression levels of which are measured using material from patients Note that the data consists of both the geneexpression measurements ... subsequent text We have geneexpressiondata for both genes from cancer patients and censored survival data from the same patients It is known that expression of PPARD influences expression of ADFP ... other genes by changing their expression level Each interaction was then of the form gene A → gene B, which we write as A → B, representing that the expression of gene A influences the expression...
... the total number of detected genes Hence, controlling the FDR may be a reasonable strategy The non-Normality of gene- expressiondata hampers the ranking of the gene- expression effects for their ... analysis of appropriately transformed gene- expression data, either using Least Squares (LS, [12]) with homogeneous or heterogeneous error variance (heterogeneous error variance implies that a ... for any non-normality of the transformed gene- expressiondata [8] However, which of these methods is most appropriate for the analysis of gene- expressiondata is not clear The aim of this study...
... for the B-cell lymphoma data (Table 2) Robust clusters are therefore valuable for allowing a rapid 'drilling down' in a gene- expression dataset to groups of genes whose coexpression pattern is ... the gene- expressiondata for a single clustering algorithm [19] We have therefore designed a similar strategy to identify the consistently clustered gene- expression profiles in microarray datasets ... contigency table by: Synthetic datasets − ( x − µ )T Σ −1 ( x − µ ) e 2 N = ∑ ∑ Countij = reviews The second dataset consists of a series of 26 arrays (1,987 filtered genes) measuring gene- expression...
... in the down-regulation of geneexpression The absolute geneexpression levels and the predicted miRNA regulation are anti-correlated The overall decrease in the geneexpression of the transcripts ... samples at the probe-level from microarray datasets (Table 1) downloaded from the GeneExpression Omnibus (GEO) database [101] The Novartis geneexpression atlas includes 79 samples, each having ... Additional data file 1) A similar trend is observed when comparing the datasets of transcripts encoding ordered and Table miRNA targeting of disordered proteins with different gene expression...
... 34 149 43 34 Table 2.1: GeneExpression Datasets coded in Standard C Datasets: We use four popular geneexpression datasets for experimental studies The four datasets were clinical data on ALL-AML ... be applied to other high-dimensional databases besides geneexpressiondata Experiments on synthetic data, geneexpressiondata and benchmark biological data are done to show the effectiveness ... instances, which is usually quite small TopkRGS runs on discretized geneexpressiondata Dataset: the geneexpression dataset (or table) D consists of a set of rows, R={r1 , , rn } Let I={i1 , i2...
... 3.3.2 32 Missing Data Estimation for Gene Microarray ExpressionDataGeneexpression microarray experiment can generate data sets with multiple missing expression values [TCS+ 01] Two data sets we ... xij is the expression value of gene i in sample j x¯ik is the mean expression value in class k for gene i n is the total number of samples x¯i is the general mean expression value for gene i si ... 33 biological area, including geneexpressiondata analysis and protein classification According to [Aas01], let y ˜ be the geneexpression vector to be the geneexpression vector to be classified...