high dimensional visualization support for data mining gene expression data
A gene expression database for the molecular pharmacology of cancer pptx
... compounds and measured gene expression levels The gene expression profiles show considerable coherence, in that cells clustered on the basis of their expression profiles for 1,376 genes and 40 targets ... correlation coefficients (one for each gene and target) for each nature genetics • volume 24 • march 2000 article © 2000 Nature America Inc • http://genetics.nature.com Table • Database of drugs analysed ... –0.248; for comparison, that calculated from Fisher’s z-transform was very similar, –0.620 to –0.204 When we stratified the data by subtracting the mean log values for drug sensitivity and gene expression...
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báo cáo hóa học:" Research Article Impact of Missing Value Imputation on Classification for DNA Microarray Gene Expression " ppt
... which the log-transformed gene expression data are represented by a true signal plus multiple sources of additive noise There are other models proposed for gene expression data, including a multiplicative ... Following the model above, we generate synthetic gene expression datasets for the true signal, S, and the observed expression values, X In addition, the dataset with MVs XMV is generated by identifying ... follow the same two basic steps (1) For each target gene yi , K genes with expression profiles most similar to the target gene are selected to form the candidate gene set Ci = [x p1 , x p2 , ,...
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Báo cáo y học: "An annotated cDNA library and microarray for large-scale gene-expression studies in the ant Solenopsis invicta" pot
... al.: Gene ontology: tool for the unification of biology The Gene Ontology Consortium Nat Genet 2000, 25:25-29 Cameron SA, Mardulyn P: Multiple molecular data sets suggest independent origins of highly ... possible that a subset of the 23 ant-bee gene pairs was permissive for sociality to evolve or is important for social behavior Behavior genes To identify candidate genes that might be involved in the ... ab initio Proteins, Ensembl Fgenesh FGENESH00000037205 FGENESH 00000037219 ab initio Proteins, Softberry Fgenesh S.C_Group11.13000016A ab initio Proteins, Softberry Fgenesh++ S.C_Group11.13000019B...
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Báo cáo sinh học: "Association of repeatedly measured intermediate risk factors for complex diseases with high dimensional SNP data." pot
... contains information about repeatedly measured common characteristics that contribute to cardiovascular diseases (CVD), together with genetic data of about 50,000 SNPs These data were provided for participants ... the genetic analysis workshop 16 (GAW16) The second dataset is the REGRESS dataset [4], which contains information about lipid profiles together with about 100 SNPs located in candidate genes ... was performed to study common characteristics that contribute to cardiovascular diseases (CVD) Besides information about these risk factors, the study contains information about genetic data of...
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Báo cáo y học: "Classification methods for the development of genomic signatures from high-dimensional data" potx
... on gene- expression data [1] They are then used on two different data sets [6,17] to predict which breast cancer patients would benefit from adjuvant chemotherapy based on gene- expression data ... patients with AML The gene expression levels were measured by Affymetrix high- density oligonucleotide arrays containing 6,817 human genes Before performing normalization, the data were preprocessed ... base-10 logarithmic transformation The data were then summarized by 72 mRNA samples and 3,571 genes [3] Table shows performance of classification algorithms for the leukemia data, based on 20 repetitions...
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Data mining methodologies for gene expression analysis application to strain improvement
... Novel data- mining methods suitable for gene expression data mining are proposed and validated using artificial and real expression datasets In the following sections, gene expression data generation ... time-course gene expression data analysis 1.4 Challenges in Gene Expression Data- mining Though gene expression data provides the state of a cell by measuring the expres- sion levels of almost all its genes, ... ith Gene in expression data k Number of PCs used for modeling expression data MD Mahalanobis Distance n Number of genes pi Loading vectors of PCA Pi p-value of gene i S Covariance matrix of gene...
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Statistical Machine Learning for High Dimensional Data
... problems are high dimensional But often, the relevant information is effectively low dimensional Nonparametricity Make the weakest possible assumptions Preview: Graphs on Equities Data Preview: ... Regression • High dimensional regression • Sparsity • The lasso • Some extensions 20 High Dimensional Linear Regression Now suppose p is large We even might have p > n (more covariates than data points) ... error is generalization like variance • Decomposition holds more generally, even for classification 13 Linear Regression Try to find the best linear predictor, that is, a predictor of the form:...
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Statistical Machine Learning for High Dimensional Data Lecture 2
... Topics • Undirected graphical models • High dimensional covariance matrices • Sparse coding 31 High Dimensional Covariance Matrices Let X = (X1 , , Xp ) (for example, p stocks) Suppose we want ... regression coefficients Fan, Fan and Lv (2008) study this in the high dimensional setting 39 Topics • Undirected graphical models • High dimensional covariance matrices • Sparse coding 40 Sparse Coding ... Provides high dimensional, nonlinear representation • Sparsity enables codewords to specialize, isolate “features” • Overcomplete basis, adapted to data automatically • Frequentist form of topic...
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Statistical Machine Learning for High Dimensional Data Lecture 3
... 1936) is classical method for finding correlations between components of two random vectors X ∈ Rp and Y ∈ Rq Sparse versions have been proposed for high dimensional data (Witten & Tibshirani, ... one -dimensional nonparametric regression function R: glm But what if p is large? 24 Sparse Additive Models Ravikumar, Lafferty, Liu and Wasserman, JRSS B (2009) Additive Model: Yi = High dimensional: ... Recent work has studied properties and high dimensional scaling of reduced rank regression where nuclear norm min(p,q) B ∗ := σj (B) j=1 as convex surrogate for rank constraint (Yuan et al., 2007;...
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Data Preparation for Data Mining- P3
... the data set for mining to best expose the information contained in it to the mining tool Indeed, the whole purpose for mining data is to transform the information content of a data set that ... transforming information The concept of information is crucial to data mining It is the very substance enfolded within a data set for which the data set is being mined It is the reason to prepare the data ... Transformations and Difficulties—Variables, Data, and Information Much of this discussion has pivoted on information—information in a data set, information content of various scales, and transforming...
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Data Preparation for Data Mining- P4
... bias Determining data structure Building the PIE Surveying the data Modeling the data 3.3.1 Stage 1: Accessing the Data The starting point for any data preparation project is to locate the data This ... fashion • Data format For decades, data has been generated and collected in many formats Even modern computer systems use many different ways of encoding and storing data There are media format ... preparation activities Data Issue: Representative Samples A perennial problem is determining how much data is needed for modeling One tenet of data mining is “all of the data, all of the time.”...
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Data Preparation for Data Mining- P5
... original information This additional information actually forms another data stream and enriches the original data Enrichment is the process of adding external data to the data set Note that data enhancement ... data comes from, what is in the data, and what issues remain to be established—in other words, to determine the general quality of the data This forms the foundation for all preparation and mining ... between variables also needs to be considered In every data mining application, the data set used for mining should have some underlying rationale for its use Each of the variables used should have...
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Data Preparation for Data Mining- P6
... numerating the alphas, but also for conducting the data survey and for addressing various problems and issues in data mining Becoming comfortable with the concept of data existing in state space ... confidence is justified for the instances available In a small data set, selecting a 99.99% confidence level forces the sampling method to take all of the data, since such a high confidence of capture ... standard deviation of the sample For large numbers of instances, which will usually be dealt with in data mining, the difference is miniscule.) There is another formula for finding the value of the...
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Data Preparation for Data Mining- P7
... 0.8769 Forward 0.4940 0.4923 Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark Forward 0.6988 0.7692 Forward 0.4940 0.4462 Forward 0.6988 0.7538 Forward 0.4940 0.3231 Forward ... Zalapski Forward 37 Patrick Poulin Reserve 55 Igor Ulanov Forward 26 Martin Rucinsky Defense 43 Patrice Brisebois Forward 28 Marc Bureau Forward 27 Shayne Corson Defense 52 Craig Rivet Forward ... variables This transformation is no more than a convenience, but making such a transformation allows many properties of unit state space to be immediately known For instance, in a two -dimensional unit...
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Data Preparation for Data Mining- P8
... the same dimensionality From here, the principle is to rotate the shape in its high- dimensional form, projecting it into a lower-dimensionality space until the minimum stress level for the projection ... Translating the information discovered there into insights about the data, and the objects the data represents, forms an important part of the data survey in addition to its use in data preparation ... with putting data into the multitable structures called “normal form” in a database, data warehouse, or other data repository.) During the process of manipulation, as well as exposing information,...
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Data Preparation for Data Mining- P9
... least harm to the information content of the data set Yet it still leaves some information exposed for the mining tools to use when values outside those within the sample data set are encountered ... are dimensions in the data Thus a three -dimensional data set could have a maximum of eight possible MVPs as shown in Table 8.1 TABLE 8.1 Possible MVPs for a three -dimensional data set Pattern number ... work.) Third, and very important for maximum information exposure, the individual variable distributions are transformed This transformation makes the between-variable information far more accessible...
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Tài liệu Data Preparation for Data Mining- P10 docx
... Series Data Series data differs from the forms of data so far discussed mainly in the way in which the data enfolds the information The main difference is that the ordering of the data carries information ... replacing missing values for data sets of modest dimensionality (tens and very low hundreds of inputs), but building such networks for moderate- to high- dimensionality data sets is problematic ... series data set so that it can be accurately and completely characterized Find methods for manipulating the unique features of series data to expose the information content to mining tools Series data...
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Tài liệu Data Preparation for Data Mining- P11 pdf
... variable data set required on one mining project Another reason that high dimensionality presents difficulties for mining tools is that as the dimensionality increases, the size (multidimensional ... to data, the demonstration software has no specific routines for preparing displacement series data Data visualization is a broad field in itself, and there are many highly powerful tools for ... transform accomplishes this The second transform subtracts the mean of the transformed variable from each transformed value, and divides the result by the standard deviation The formula for this...
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Tài liệu Data Preparation for Data Mining- P12 pptx
... than data preparation? Data preparation concentrates on transforming and adjusting variables’ values to ensure maximum information exposure Data surveying concentrates on examining a prepared data ... nomenclature A function can be expressed as a formula, just as the formula for determining the value of the logistic function is For convenience, this whole formula can be taken as a given and represented ... Compressed Dimensionality Data When the miner and domain expert have a high degree of confidence that the training data set for the compression model is fully representative of the execution data, ...
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Tài liệu Data Preparation for Data Mining- P13 pptx
... “information.” This book mentions “information” in several places “Information is embedded in a data set.” “The purpose of data preparation is to best expose information to a mining tool.” “Information ... that mining is not designed to extract information Data, or the data set, enfolds information This information describes many and various relationships that exist enfolded in the data When mining, ... term “information” is used in data mining Data possesses information only in its latent form Mining provides the mechanism by which any insight potentially present is explicated Since information...
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