CisSearch TM
Software Program Package
About the team
CisSearch™ package developed by our team in the frames of START program is written with C++ and at present it is an application with graphic interface that can handle different types of data: DNA sequences, homologues, microarray analyses, signal transduction pathways. It is developed for Windows.
The research team was formed in 2001 and it has published more than 20 articles about the methods of prediction of gene regulatory peculiarities.
The team combines enthusiasm and energy of youth with high professionalism and experience.
Everybody in the team have higher education, experience in developing and implementation of software and participation in large projects.
Implementation means:
Our team has developed several algorithms and technologies that search special sites (cis-elements) responsible for binding of specific proteins (Transcription Factors) with regulatory fragments of a gene. These data solves a number of problems of genome analysis and drug development.
The software package is orientated on the mass-user. So the biologist unconversant with a programming can processes the necessary data and also there is a set of libraries for researchers which can be used by bioinformatics department of biotechnological companies.
At present there are a few of available programs searching cis-elements, but in comparison with CisSearch™ they are simplified very much, solve only local problems and have high false positives and false negatives. In the program package a few methods are realized that consider different biological particularities (promoter evaluation, composite regulation, context effect, profile expression, signal transduction pathways) and also the instrument for data testing and comparison of methods, that lets the user to choose the best variant for cis-elements search using the fullest extent of available data.
The program is so functional that it could be used not only by the experts but also by not very experienced PC users. The design requirements are minimal. The attention was focused on getting the maximum of recognition quality and functionality. Quality of recognition is estimated by two parameters: false positives and false negatives. The less of these mistakes, the higher recognition quality is. The false positives and false negatives are estimated by searching of cis-elements and comparing with the cis-elements, confirmed experimentally and put in the data base.
If you are interested in this product please contact: sales@biorainbow.com