[PDF] Top 20 Clustering Gene Expression Time Series Data
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Clustering Gene Expression Time Series Data
... different time points. Clustering is the process of grouping data with similar character into the same class or the same ...of clustering is that objects in the same cluster have high ... See full document
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Clustering Time Series Data by SOM for the Optimal Hedge Ratio Estimation
... financial time series and have been widely used for forecasting volatility and for estimating portfolio ...with time series ...the time series to be stationary; thus, the price ... See full document
6
Inferring S-system Models of Genetic Networks from a Time-series Real Data Set of Gene Expression Profiles
... microarray data in ...from gene expression profiles to discover more delicate and substantial ...the gene reconstruction ...single data set is comparable to that of iTEA using two real ... See full document
6
Artificial Neural Network Prediction for Cancer Survival Time by Gene Expression Data
... The results shows ANN can predict survival time from Microarray data gene expression and the prediction made by the proposed neural models show a good agreement with the measurements.[r] ... See full document
1
Social trend tracking by time series based social tagging clustering
... collects data from ...as time series by the vec- tor space model. The corpus covers data created in 2008, including 3842 distinct web pages and 2707 distinct ...hierarchical clustering ... See full document
11
An Embedded Gene Selection Method for Gene Expression Data
... on clustering analysis and classification accuracy. In clustering analysis, the purpose of clustering is to analyze the gene groups that show a correlated pattern of the gene ... See full document
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A clustering time series model for the optimal hedge ratio decision making
... return series. All eight series show signi ficant skewness, kurtosis, and Jarque –Bera (JB) statistics, implying non- normal distributions with fatter ...futures data are in TWI and FTSE 100, ... See full document
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An expert system to identify co-regulated gene groups from time-lagged gene clusters using cell cycle expression data
... of time series gene expression data can provide us with the opportunity to find co-regulated genes that show a similar expression patterns under a contiguous subset of ... See full document
2
An expert system to identify co-regulated gene groups from time-lagged gene clusters using cell cycle expression data
... certain time lag. That is to say, there is a transcriptional time lag whereby the regulator gene takes time to express its protein product and a further delay occurs as the target gene ... See full document
12
Categorical Time-Series Data Classification base on Sequential Pattern
... with time sequence property like time-series gene expression ...new data mining method, namely Classify-By- Sequence (CBS), for classifying large time-series ... See full document
7
Improved binary PSO for feature selection using gene expression data
... for gene expression data classification ...simplified gene (fea- ture) selection and reduced the total number of genes (features) ...11 gene expression data test problems, ... See full document
5
Discovering monotonic stemness marker genes from time-series stem cell microarray data
... synthetic data sets and two stem cell differentiation data sets: embryonic stem cell neurogenesis (ESCN) and embryonic stem cell vasculogenesis (ESCV) data ...monotonic gene selection ...from ... See full document
18
Design of an Integrated and Effective Platform for Gene Expression Data Mining
... 【Abstract】 Gene expression data mining is an important issue in bioinformatics research and applications since it can effectively help discover the functions of genes in high throughput ...for ... See full document
14
An efficient method for mining cross-timepoint gene regulation sequential patterns from time course gene expression datasets
... of data mining, especially for the data- base ...the time-stamp ordered transaction. Therefore, once the potential gene regulations occurred in a period of time, it could be identi- ... See full document
12
Inference of Biological Pathway from Gene Expression Profiles by Time Delay Boolean Networks
... complex gene regulatory ...experimental data such as DNA sequences, protein sequence, and RNA expression profiles makes it possible to study interactions and regulations among genes or other ... See full document
8
Identifying Regulatory Targets of Cell Cycle Transcription Factors Using Gene Expression and ChIP-chip Data
... Since co-expressed genes are not necessarily co-regulated and vice versa [21], it is important to develop a method that can identify co-regulated genes that are not co-expressed. TRIA has the ability to do this task. ... See full document
6
Interpretable gene expression classifier with an accurate and compact fuzzy rule base for microarray data analysis
... UPGMA) clustering based on Euclidean distances squared by EPCLUST (Parkinson et ...microarray data analysis and development of inexpen- sive diagnostic ... See full document
12
Reducing the Variation of Gene Expression Patterns: A Grey Model Approach Applied to Microarray Data Classification
... a series of supervised statistical ...discriminating gene is larger than ...and time consuming so limit the number of samples, and therefore make variations within a class become more accentuated ... See full document
7
Clustering on demand for multiple data streams
... conventional time series clustering algorithms to the raw streams with the desired window sizes is not practical in the streaming environment because there is not enough space for the storage of ... See full document
4
Mining Time Series Data with Fuzzy Association Rules
... Rules Data mining can be applied to discover the useful patterns and rules by exploring and analyzing a large quantity of ...of data from customer surveys, health studies, market examinations, item banks ... See full document
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