Tag: Mining

Diurnal 2.0 – Mining and Viewing Diurnal and Circadian Microarray data for Arabidopsis thaliana, poplar, and rice

Diurnal 2.0

:: DESCRIPTION

Diurnal is a web-based tool for accessing the diurnal and circadian genome-wide expression results of genes from several array experiments conducted on common model plants. The expression patterns of particular loci or array probes can be looked up under a variety of different conditions. For each condition, every expression pattern has been modeled using a periodic pattern, which has then been used to estimate the phase of peak expression.

::DEVELOPER

Mockler Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation:

The DIURNAL project: DIURNAL and circadian expression profiling, model-based pattern matching, and promoter analysis.
Mockler TC, Michael TP, Priest HD, Shen R, Sullivan CM, Givan SA, McEntee C, Kay SA, Chory J.
Cold Spring Harb Symp Quant Biol. 2007;72:353-63. doi: 10.1101/sqb.2007.72.006.

SMK 2011v4 – Mining Low-support Discriminative Patterns from Dense and High-dimensional Data

SMK 2011v4

:: DESCRIPTION

SMK (SupMaxK , a family of anti-monotonic measures) aims at the efficient discovery of discriminative patterns from biological data with high density and high dimensionality (e.g. Gene Expression data, and SNP data), and especially for the discovery of those patterns with relatively low-support but high discriminative power (e.g. odds ratio, information gain, p-value etc), which complements existing discriminative pattern mining algorithms.

::DEVELOPER

Data mining for biomedical informatics at the UMN

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Matlab

:: DOWNLOAD

 SMK

:: MORE INFORMATION

Citation

Gang Fang, Gaurav Pandey, Wen Wang, Manish Gupta, Michael Steinbach and Vipin Kumar
Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data
IEEE Transaction on Knowledge and Data Engineering (TKDE).2012 (vol. 24 no. 2)pp. 279-294

PAM 2.1 – Prediction and Survival Analysis for Genomic Expression Data Mining

PAM 2.1

:: DESCRIPTION

PAM (Prediction Analysis for Microarrays) is a class prediction and survival analysis software for genomic expression data mining

::DEVELOPER

Rob Tibshirani

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

  PAM

:: MORE INFORMATION

Citation:

Tibshirani, Hastie, Narasimhan and Chu (2002):
“Diagnosis of multiple cancer types by shrunken centroids of gene expression”
PNAS 2002 99:6567-6572