:: DESCRIPTION
WIFA is a novel method referred to as the wavelet-based identification of focal genomic aberrations.
::DEVELOPER
Data Mining & Computational Biology Lab
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2011 May 11;12:146. doi: 10.1186/1471-2105-12-146.
Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays.
Hur Y1, Lee H.
:: DESCRIPTION
HaMMLET is a fast Forward-Backward Gibbs sampler for Bayesian inference on Hidden Markov Models (HMM). It uses the Haar wavelet transform to dynamically compress the data based on the current variance sample in each iteration.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Fast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet Compression.
Wiedenhoeft J, Brugel E, Schliep A.
PLoS Comput Biol. 2016 May 13;12(5):e1004871. doi: 10.1371/journal.pcbi.1004871.
:: DESCRIPTION
PeakLink (PL) uses information in both the time and frequency domain as inputs to a non-linear support vector machine (SVM) classifier. The PL algorithm first uses a threshold on retention time to remove candidate corresponding peaks with excessively large elution time shifts, then PL calculates the correlation between a pair of candidate peaks after removing noise through wavelet transformation. After converting retention time and peak shape correlation to statistical scores, an SVM classifier is trained and applied for differentiating corresponding and non-corresponding peptide peaks.
::DEVELOPER
:: SCREENSHOTS
N/A
::REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2014 Sep 1;30(17):2464-70. doi: 10.1093/bioinformatics/btu299. Epub 2014 May 9.
PeakLink: a new peptide peak linking method in LC-MS/MS using wavelet and SVM.
Ghanat Bari M, Ma X, Zhang J.
