The AmphoraNet metagenomic phylotyping tool

The AmphoraNet uses 31 bacterial and 104 archaeal protein coding marker genes for metagenomic phylotyping. Most of these are single copy genes, therefore AmphoraNet is suitable for estimating the quantitative taxonomic composition of bacterial and archaeal communities from metagenomic shotgun sequencing data.


    Csaba Kerepesi, Daniel Banky, Vince Grolmusz: AmphoraNet: The Webserver Implementation of the AMPHORA2 Metagenomic Workflow Suite, Gene, 2014, Vol. 533 No. 2. pp. 538-540; http://dx.doi.org/10.1016/j.gene.2013.10.015

3D Brownian motion simulator

The Brownian 3D Brownian motion simulator program, can estimate the meeting time and the dockig ratio of nanoparticles to a target spot in microarrays. It is the only 3D Brownian motion simulator we are aware of.


    Arpad Toth, Daniel Banky, and Vince Grolmusz: Mathematical modeling and computer simulation of Brownian motion and hybridization of nanoparticle-bioprobe-polymer complexes in the low concentration limit, Molecular Simulation, Vol. 38, No. 1. pp. 66-71, DOI: 10.1080/08927022.2011.602217.
    Arpad Toth, Daniel Banky, and Vince Grolmusz: 3D Brownian Motion Simulator for High-Sensitivity Nano-Biotechnological Applications, IEEE Transactions on Nanobioscience, Vol. 10, No. 4. pp. 248-249, doi: 10.1109/TNB.2011.2169331. p. 2

The SwissAlign Webserver

The SwissAlign Webserver is a lightning-fast implementation of the Smith-Waterman sequence alignment algorithm for protein sequences deposited in the SwissProt subset of the UniProt database.


    Ivan, G., Banky, D., Grolmusz, V.: Fast and Exact Sequence Alignment with the Smith-Waterman Algorithm: The SwissAlign Webserver, arXiv:1309.1895 September 7, 2013


ProtDict is a UniProt-based Protein dictionary, capable of finding UniProt entries based on AC numbers, SwissProt IDs, EC numbers, 3 types of gene names, and 100 different types of database cross references.


The PDB Structural Decomposition Tool repairs and decomposes files from the Protein Data Bank PDB formats. With our program, protein-ligand complexes are identified reliably, missing residues and atoms in chains are handled properly. Placeholders are inserted into chains for missing residues/atoms. Ligands are identified without using the HET-atom labels, properly handling modified residues and small artifacts, due to crystallization protocols. CONECT records of the ligand-atoms are computed automatically.


    Szabadka, Z., Grolmusz, V.: High Throughput Processing of the Structural Information of the Protein Data Bank, Journal of Molecular Graphics and Modeling 25 (2007) pp. 831-836.
    Szabadka, Z., Grolmusz, V.: Building a Structured PDB: The RS-PDB Database. Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, Aug. 30-Sept 3, 2006., pp. 5755-5758.
    Gabor Ivan, Zoltan Szabadka, Vince Grolmusz: On the asymmetry of the residue compositions of the binding sites on protein surfaces; Journal of Bioinformatics and Computational Biology, Vol. 7. No. 6. (2009) pp. 931-938.
    Gabor Ivan, Zoltan Szabadka, Vince Grolmusz: Cysteine and Tryptophan Anomalies Found when Scanning all the Binding Sites in the Protein Data Bank, International Journal of Bioinformatics Research and Applications, Vol. 6, No. 6, 2010, pp. 594-608.


The Nascent is a protein-protein physical interaction network construction tool based on gene names. Our program searches for proteins of source organism which are in physical interaction by the IntAct database. Then those proteins are assigned to their respective gene names. We use these gene names to make a correspondence between the source and the target organisms making a predicted protein-protein physical interaction network for the target organism.


    Daniel Banky, Rafael Ordog, Vince Grolmusz: NASCENT: An automatic protein interaction network generation tool for non-model organisms. Bioinformation Vol. 3 No. 8. pp. 361-363 (2009)