:: DESCRIPTION
Piet provides some segmentation tools, using fused lasso, group fused lasso and generalized fused lasso (GFL), for analysis of individual or multiple sequences of CNV data.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Z. Zhang, K. Lange, C. Sabatti (2012)
Reconstructing DNA copy number by joint segmentation of multiple sequences
:: DESCRIPTION
The DiNAMO software implements an exhaustive algorithm to detect over-represented IUPAC motifs in a set of DNA sequences. It has two modes: scanning mode, where all windows are parsed, or fixed-position mode, where only motifs occurring at a specific position in the sequences are taken into account.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Saad C, Noé L, Richard H, Leclerc J, Buisine MP, Touzet H, Figeac M.
DiNAMO: highly sensitive DNA motif discovery in high-throughput sequencing data.
BMC Bioinformatics. 2018 Jun 11;19(1):223. doi: 10.1186/s12859-018-2215-1. PMID: 29890948; PMCID: PMC5996464.
:: DESCRIPTION
The OMiMa (the Optimized Mixture Markov model) System is a computational tool for identifying functional motifs in DNA or protein sequences. OMiMa System is based on the Optimized Mixture of Markov models that are able to incorporate most dependencies within a motif. Most important, OMiMa is capable to adjust model complexity according to motif dependency structures, so it can minimize model complexity without compromising prediction accuracy. OMiMa uses our fast Markov chain optimization method, the Directed Neighbor-Joining (DNJ), which makes OMiMa more computationally efficent.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Weichun Huang, David M Umbach, Uwe Ohler, Leping Li.
Optimized mixed Markov models for motif identification.
BMC Bioinformatics 2006, 7:279
:: DESCRIPTION
Chromatin Cutter simulates the distribution of DNA in a gel electrophoresis study of Yeast chromatin cut by enzymes. It lets you specify the fraction of nucleosomes that are unwrapped (wrapped ones have inaccessible DNA). It lets you specify the variance in the distribution of nucleosomes around their mean distance. It lets you specify the number of cuts per unit length (enzyme concentration). It plots the effects of these on the log number of base pairs, which matches the gel electrophoresis mass distribution.
::DEVELOPER
CISMM (Computer Integrated Systems for Microscopy and Manipulation)
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
HelixMC is a software package for Monte-Carlo (MC) simulations of DNA/RNA helices using the base-pair level model. It provides a powerful tool to understand the flexibility of DNA/RNA helices through numerical simualtions.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
PLoS Comput Biol. 2014 Aug 7;10(8):e1003756. doi: 10.1371/journal.pcbi.1003756. eCollection 2014.
Blind predictions of DNA and RNA tweezers experiments with force and torque.
Chou FC, Lipfert J, Das R
:: DESCRIPTION
TfReg implements the calculation of Peyrard-Bishop style Hamiltonians to obtain some physical properties of DNA and RNA duplexes. The method uses the transfer matrix technique for the calculation of the classical partition function. Also, TfReg calculates the regression of experimental versus predicted melting temperatures using the equivalent melting index.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2013 May 15;29(10):1345-7. doi: 10.1093/bioinformatics/btt133. Epub 2013 Mar 16.
TfReg: calculating DNA and RNA melting temperatures and opening profiles with mesoscopic models.
Weber G.
:: DESCRIPTION
The web-server iDNA-Methyl is according to its genetic codes by combining its trinucleotide composition (TNC) and the pseudo amino acid components (PseAAC) of the protein translated from the DNA sample. And by means of the approach of optimizing training datasets for predicting DNA methylation sites. Rigorous cross-validations on a set of experiment-confirmed datasets have indicated that these new predictors remarkably outperformed their counterparts in the existing prediction methods
::DEVELOPER
:: SCREENSHOTS
n/a
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition.
Liu Z, Xiao X, Qiu WR, Chou KC.
Anal Biochem. 2015 Jan 14. pii: S0003-2697(14)00569-7. doi: 10.1016/j.ab.2014.12.009.
:: DESCRIPTION
DisoRDPbind predicts the RNA-, DNA-, and protein-binding residues located in the intrinsically disordered regions.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder.
Peng Z, Kurgan L.
Nucleic Acids Res. 2015 Oct 15;43(18):e121. doi: 10.1093/nar/gkv585.
:: DESCRIPTION
Multi-VORFFIP is a structure-based, machine learning, computational method designed to predict protein-protein, protein-peptide, protein-DNA and protein-RNA binding sites. M-VORFFIP integrates a wide and heterogeneous set of residue- and environment-based information using a two-step Random Forest ensemble classifier.
VORFFIP (Voronoi Random Forest Feedback Interface Predictor) is structure-based computational method for prediction of protein binding sites.
::DEVELOPER
Bioinformatics Lab :: IBERS :: Aberystwyth University
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2012 Jul 15;28(14):1845-50. doi: 10.1093/bioinformatics/bts269. Epub 2012 May 4.
A holistic in silico approach to predict functional sites in protein structures.
Segura J1, Jones PF, Fernandez-Fuentes N.
BMC Bioinformatics. 2011 Aug 23;12:352. doi: 10.1186/1471-2105-12-352.
Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams.
Segura J1, Jones PF, Fernandez-Fuentes N.
