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PAnDA is an algorithm for the prediction of direct and indirect TF binding events.
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Run mode Default mode is recommended for majority of users. The expert mode enables the selection of specific motifs databases and expression level thresholds in cell lines of interest. Please see Tutorial for detailed description.
Default mode Expert mode
Human cell lines
A549 (lung carcinoma epithelial cell) AG04450 (fetal lung fibroblast) BJ (skin fibroblast) GM12878 (B-lymphocyte, lymphoblastoid) H1-hESC (embryonic stem cells) HUVEC (umbilical vein endothelial cells) HeLa-S3 (cervical carcinoma) HepG2 (hepatocellular carcinoma) K562 (leukemia) MCF-7 (mammary gland, adenocarcinoma) NHEK (epidermal keratinocytes) SK-N-SH_RA (neuroblastoma cell line differentiated w/ retinoic acid)
Motifs databases
JASPAR CORE (2014) Jolma (2013) Uniprobe (2011) Wang (2012) SeAMotE (2014) All
Cofactors expression threshold (quantiles)
0.1 0.2 0.3 0.4 0.5
Mediated Cofactors expression threshold (quantiles)
Machine learning method
Support Vector Machine (linear function) Support Vector Machine (radial based function) Random Forest K-nearest neighbors Adaptive Boosting
Interaction databases (STRING)
STRING (confidence score: 0.7) STRING (confidence score: 0.8) STRING (confidence score: 0.9) none
Interaction databases (BioGRID)
BioGRID (co-localization, co-purification, FRET, Two-hydrid) BioGRID (FRET, Two-hydrid) none
Upload protein sequence(s) (FASTA format)
Upload DNA sequence(s) (FASTA format)
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