Minerva Gen*NY*Sis Center for Excellence in Cancer Genomics
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Igor B. Kuznetsov

Software developed in our lab

BIAS: software and web-server for the identification of user-defined types of
compositional bias in biological sequences

Source code and binaries: http://lcg.rit.albany.edu/bias/

DP-Bind: a web-server for sequence-based prediction of
DNA-binding residues in DNA-binding proteins

The server uses a protein sequence to run three prediction methods and calculates a consensus prediction: http://lcg.rit.albany.edu/dp-bind/

CFP: a web-server for the identification of protein segments with
high backbone flexibility

The server uses a protein sequence to identify potential conformationally flexible segments:

FlexPred: a web-server for predicting residue positions involved in
conformational switches in proteins

The server accepts either a protein sequence or a PDB file to predict residue positions involved in conformational switches:

NAT2PRED: a web-server for predicting the human
N-AcetylTransferase-2 acetylator phenotype

The server predicts the activity level of the human N-AcetylTransferase-2 (NAT2) based on the combination
of single nucleotide polymorphisms (SNPs) observed in the NAT2 gene:

PR2ALIGN: software and a web-server for pair-wise alignment of amino acid sequences by using weighted profiles of biochemical properties

This web-server finds an optimal global alignment of two amino acid sequences by utilizing weighted profiles of their biochemical properties instead of a single similarity matrix:

SAP-DB: The Database of Structurally Ambivalent Peptides

This on-line database has been compiled by performing an exhaustive search of all the Protein Databank (PDB) structures and contains peptides of length five or longer that adopt two or more significantly different backbone conformations in different proteins:

Software resources

Commercial: MatLab, C/C++ development tools, Perl development tools, Web-development and publishing tools, Statistica, SAS, SPSS, S-Plus, TransFac, GeneSpring, PathwayStudio.

Public domain: R, BioConductor, BioPerl, libSVM, numerical analysis packages, PHP, Python, Apache, SQL, etc.

Hardware resources

The Cancer Research Center has state-of-the-art high-performance computational facilities dedicated to bioinformatics research and development. These facilities include personal workstations running Windows/Linux operating systems and the following Linux servers:

  • Two 4x4-processor 64GB RAM DELL PowerEdge servers
  • Five 2x4-processor 16GB RAM DELL PowerEdge servers
  • Two 4x2-processor 16GB RAM DELL PowerEdge servers
  • Two 2x2-processor 4GB RAM DELL PowerEdge servers
  • DELL high-performance computing cluster that has 16 compute nodes and a head node. Each node has two IntelXeon processors and 4 Gb RAM.
  • The servers are connected to a shared network file system, backed up daily, and run Condor batch job submission system.
  • We also have an unlimited access to hundreds of CPUs on shared high-performance Linux clusters maintained by the UAlbany Research IT Department and the New York State Grid.

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