:: DESCRIPTION
GraphProt can be used for modeling binding preferences of RNA-binding proteins from high-throughput experiments such as CLIP-seq and RNAcompete.
::DEVELOPER
Chair for Bioinformatics Freiburg
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Genome Biol. 2014 Jan 22;15(1):R17. [Epub ahead of print]
GraphProt: modeling binding preferences of RNA-binding proteins.
Maticzka D, Lange SJ, Costa F, Backofen R.
:: DESCRIPTION
MultiTF-PPI is a probabilistic protein-protein interaction guided method for competitive transcription factor binding prediction.
::DEVELOPER
Computational systems biology group
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
NetMHCII predicts binding of peptides to HLA-DR, HLA-DQ, HLA-DP and mouse MHC class II alleles using articial neuron networks.
Predictions can be obtained for 14 HLA-DR alleles covering the 9 HLA-DR supertypes, six HLA-DQ, six HLA-DP, and two mouse H2 class II alleles.
The prediction values are given in nM IC50 values, and as a %-Rank to a set of 1,000,000 random natural peptides. Strong and weak binding peptides are indicated in the output.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2009 Sep 18;10:296.
NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction.
Nielsen M, Lund O.
:: DESCRIPTION
BaalChIP ( Bayesian Analysis of Allelic imbalances from ChIP-seq data) corrects for the effect of background allele frequency on the observed ChIP-seq read counts jointly analyses multiple ChIP-seq samples across a single variant.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Genome Biol, 18 (1), 39 2017 Feb 24
BaalChIP: A probabilistic framework for reconstructing intra-tumor phylogenies
I. de Santiago, W. Liu, K. Yuan, M. O’Reilly, CS. Chilamakuri, B. Ponder, K. Meyer, F. Markowetz
:: DESCRIPTION
CCmiR is a software for competitive and cooperative microRNA binding prediction
::DEVELOPER
Hu Lab – Data Integration and Knowledge Discovery @ UCF
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Bioinformatics. 2018 Jan 15;34(2):198-206. doi: 10.1093/bioinformatics/btx606.
CCmiR: a computational approach for competitive and cooperative microRNA binding prediction.
Ding J, Li X, Hu H.
:: DESCRIPTION
mCrossBase is a database of RNA-binding protein (RBP) binding motifs and crosslink sites defined jointly from CLIP data using a novel algorithm mCross
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Feng et al. (2019),
Modeling the in vivo specificity of RNA-binding proteins by precisely registering protein-RNA crosslink sites.
Mol Cell. 74:1189-1204.E6.
:: DESCRIPTION
BETA is a software package that integrates ChIP-seq of transcription factors or chromatin regulators with differential gene expression data to infer direct target genes. BETA has three functions: (1) to predict whether the factor has activating or repressive function; (2) to infer the factor’s target genes; and (3) to identify the motif of the factor and its collaborators which might modulate the factor’s activating or repressive function.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Wang, S., Sun H, Ma J, Zang C, Wang C, Wang J, Tang Q, Meyer CA, Zhang Y, Liu XS.(2013)
Target analysis by integration of transcriptome and ChIP-seq data with BETA.
Nature protocols, 8(12), 2502-2515.
:: DESCRIPTION
The BEESEM program is designed for transcription factor binding motif discovery using HT-SELEX data.
::DEVELOPER
Stormo Lab in Department of Genetics, Washington University
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2017 Aug 1;33(15):2288-2295. doi: 10.1093/bioinformatics/btx191.
BEESEM: estimation of binding energy models using HT-SELEX data.
Ruan S, Swamidass SJ, Stormo GD
:: DESCRIPTION
TAPPred is an on-line service for predicting binding affinity of peptides toward the TAP transporter. The Prediction is based on cascade SVM, using sequence and properties of the the amino acids
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bhasin,M. and Raghava, G.P.S. (2004)
Analysis and prediction of affinity of TAP binding peptides using cascade SVM.
Protein Sci.,13 (3),596-607.
:: DESCRIPTION
nHLAPred allow to predict binding peptide for 67 MHC Class I alleles. This also allow to predict the proteasome cleavage site and binding peptide that have cleavage site at C terminus (potential T cell epitopes).
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bhasin M. and Raghava G P S (2006)
A hybrid approach for predicting promiscuous MHC class I restricted T cell epitopes;
J. Biosci. 32:31-42.
