Bioinformatics is the key competence of our company.
Bioinformatics implies solving the complicated tasks on modeling live systems, new knowledge mining and development of the program complexes filled with intellectual algorithms.
Our team successfully solves tasks in bioinformatics since 2003. This includes next-generation sequencing data processing, microarray analysis, promoter analysis and classification, prediction of transcription factors (TF) binding sites, miRNA and ncRNA data analysis, spatial structure of RNA and proteins prediction, gene networks and cellular signals transduction modeling.
By the present moment it has been accumulated experience in solving various applied and theoretical tasks in bioinformatics using both own and the borrowed algorithms in the field of signal processing and signal search, tools for knowledge mining, modeling of physical and chemical characteristics of molecules and organisms, solutions for systems of the differential equations.
Cooperation with scientific research institutes of the Siberian Branch of the Russian Academy of Science and University is a source of fresh ideas while cooperation with experimenters of the USA and Germany, suppliers of the advanced up-to-date databases, allows to be well informed about the latest achievements of a science and technology.
Deep Sequencing Data Management system (property of St.Laurent Institute, USA) – system of programs, databases and scripts for next-generation sequencing data alignment, digital gene expression analysis, alternative splicing and RNA editing events detection, since 2010.
Some graphical modules for Pathway Studio software (property of Ariadne Genomics Inc.), since 2010.
Libraries of genes and proteins interactome for some species (property of Ariadne Genomics Inc.), 2010-2011.
Software package ExPlain (property of BIOBASE GmbH) for processing the genetic information and search of key molecules-targets with the purpose of development of new medical products, since 2003.
The ExPlain is an online product integrating databases and the newest algorithms. Using ExPlain, you can explore and understand:
• Biological interpretation of the large-scale data: gene expression microarrays, proteomics data, ChIP-on-chip;
• Statistical data analysis, graphical interpretation;
• Functional classifications according to GO terms, diseases terms, tissue/organ expression, and signaling pathways;
• Mapping of putative transcription factor binding sites on gene promoters;
•Construction of promoter modules which are combinations of individual binding sites. CMAs can suggest transcription factors involved in the combined regulation of genes showing similar expression patterns in microarray experiments;
• Identification of Key Molecules upstream of these promoter modules that might be responsible for the coordinated regulation of your genes and thus become future targets for experimental study;
, since 2005
C. Elegans, free-living soil nematode, is one of the model organisms, widely used and extensively studied by biologists. It is the only organism for which neural network architecture – positions of its neurons and connections between them - is almost completely known. Its nervous system consists of 302 neurons, over 5000 synapses, more than 2000 neuromuscular junctions and these elements are invariant for individuals of the same sex. Simulation of C. Elegans nervous system seem to be one of the most actual and necessary task. Small size of neural network will allow us to make calculations in reasonable time using modern computers. Besides the model of the nervous system model, it is very important to develop the model of organism's body including muscles and receptors in three dimensional physical environment, which will provide sensory input and feedback to the working nervous system and allow to observe organism's behavior.
At the present moment 3D-simulator of C. Elegans muscular system has been realized, which includes, as a real muscular system, 4 longitudinal groups of muscles, which can be affected by signals from motoneurons of the nervous system. For calculations of dynamical physical model we take into account the supporting force, the friction force, the muscle tension, gravity and the resistance of medium. Also the C++ classes for loading and simulating given neural network are realized. Also now we have released a special mode for neural network visualization, which allow to select neurons in 3D scene to display information about them, such as name, incoming connections from other neurons and axon and its branches, leading to other neurons.
We plan to add more functionality, which will allow edit neuron and dendrites properties, such as their weights and threshold values.
(property of St.Laurent Institute, USA) – a web based application integrating algorithms, pipelines and user ncRNA data for complex analysis, since 2008.
in cooperation with St.Laurent Institute, USA and Georges Washington University, USA, since 2007.
(property of Oklahoma Medical Research Foundation), 2005-2006.
In 2005-2006 a small project on recognition of mutations in Celegans genome was done in collaboration with Oklahoma Medical Research Foundation. Given a small fragment of genome. The software should determine the mutations: deletions, insertions, substitutions. Mutations average lenghts are around 100 bp. On the base of wu-blast we implemented a program that determine positions of given mutations. Also program determines different properties and database matches.