:: DESCRIPTION
MDL is a software of Minimum Description Length for the detection of phylogenetics breakpoints
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Cécile Ané
Detecting Phylogenetic Breakpoints and Discordance from Genome-Wide Alignments for Species Tree Reconstruction
Genome Biol Evol (2011) 3 246-258.
:: DESCRIPTION
QuantiSNP is an analytical tool for the analysis of copy number variation using whole genome SNP genotyping data. In its first implementation it was developed for data arising from Illumina® platforms
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Reference:
Nucleic Acids Res. 2007;35(6):2013-25. Epub 2007 Mar 6.
QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data.
Colella S, Yau C, Taylor JM, Mirza G, Butler H, Clouston P, Bassett AS, Seller A, Holmes CC, Ragoussis J.
:: DESCRIPTION
FRED is a framework for T-cell epitope detection that offers consistent, easy, and simultaneous access to well established prediction methods for MHC binding and antigen processing. FRED can handle polymorphic proteins and offers analysis tools to combine, benchmark, or compare different methods. It is implemented in Python in a modular way and can easily be extended by user defined methods.
DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Feldhahn, M, Dönnes, P, Thiel, P, and Kohlbacher, O (2009).
FRED – A Framework for T-cell Epitope Detection
Bioinformatics, 25(20):2758-9.
:: DESCRIPTION
ASP is a program to predict accurate splice sites on genomic sequences of several organisms
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Accurate splice site prediction using support vector machines.
Sonnenburg S, Schweikert G, Philips P, Behr J, Rätsch G.
BMC Bioinformatics. 2007;8 Suppl 10:S7.
:: DESCRIPTION
SADMAMA (Significance Assessment of the Difference in MAtrix MAtches / SM) was originally designed to address the question of whether one set of sequences has more and/or better binding sites of a particular transcription factor than the other. The binding sites are modeled as matches to a, possibly gapped, position weight matrix (PWM) which is presumed to be known.
:: DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Uri Keich et al.
Computational detection of significant variation in binding affinity across two sets of sequences with application to the analysis of replication origins in yeast
BMC Bioinformatics 2008, 9:372 doi:10.1186/1471-2105-9-372
:: DESCRIPTION
OMWSA (optimized moving window spectral analysis) is a new method and a visualization tool for detecting DNA repeats in a 2D plane of location and frequency by using optimized moving window spectral analysis.
::DEVELOPER
Hong Yan , Signal Processing Lab at City University of Hong Kong
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Liping Du, Hongxia Zhou and Hong Yan
OMWSA: detection of DNA repeats using moving window spectral analysis
Bioinformatics (2007) 23 (5): 631-633.
:: DESCRIPTION
SearchRepeats searches for exact non overlapping repeats in nucleotidic (DNA) sequences and outputs these repeats in a text report.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Fast Discerning Repeats in DNA Sequences with a Compression Algorithm
Rivals, M. Dauchet, J-P. Delahaye, O. Delgrange
Extended abstract in the 8th Workshop on Genome and Informatics (GIW97)
Tokyo, 12-13 Dec 1997
:: DESCRIPTION
MEDUSA (Motif Element Detection Using Sequence Agglomeration) is an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data. We use a modern large-margin machine learning approach, based on boosting, to enable feature selection from the high-dimensional search space of candidate binding sequences while avoiding overfitting.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Learning regulatory programs that accurately predict differential expression with MEDUSA.
Kundaje A, Lianoglou S, Li X, Quigley D, Arias M, Wiggins CH, Zhang L, Leslie C.
Ann N Y Acad Sci. 2007 Dec;1115:178-202. Epub 2007 Oct 12.
:: DESCRIPTION
GPCRHMM predicts G protein-coupled receptors from amino acid sequence.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Markus Wistrand*, Lukas Käll* and Erik L.L. Sonnhammer.
A general model of G protein-coupled receptor sequences and its application to detect remote homologs.
Protein Science, 15 (3):509-21, Mars 2006.
:: DESCRIPTION
sequenceLDhot is further R code for implementing a penalised likelihood approach for detecting hotspots using the output of sequenceLDsr
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Paul Fearnhead, and Nick G.C. Smith
“A novel method with improved power to detect recombination hotspots from polymorphism data reveals multiple hotspots in human genes”
American Journal of Human Genetics, 77 781-794..
