Our main research areas

Annotation tRNA-derived fragments

Metagenome identification of tRNA-derived fragments

Several studies have been initiated towards functional characterization of non-coding RNA molecules, derived from tRNA (tRFs) in a variety of model organisms. However, a global perspective of the biogenesis of this interesting group of ncRNAs is largely missing.

Using Arabidopsis thaliana as a model organism, we aim at identification and characterization of the components involved in tRNA and microRNA biogenesis pathways that may play a role in generation of tRFs. We are presenting our results of a global, high-throughput characterization of small RNA fragments originating from Arabidopsis tRNA and tRNA-like genomic sequences.

Transcriptome-wide RNA structure dynamics

Development of NGS-based methods for tracking of RNA structure-dependent regulation of gene expression

In recent years RNA is emerging as the key regulator of gene expression. In most of known cases, the regulatory function fulfilled by RNA molecule is highly dependent on the accommodated secondary and tertiary structure.

The aim of the project is to develop both, the experimental and computational methods for identification of novel RNA-based regulatory mechanisms, relying solely on dynamic changes in RNA structure. Our research focuses on high throughput, transcriptome-wide approaches based on NGS technology.

Annotation of proteins domains

Identification of Trp(W)-containing motifs binding Argonautes and deadenylation complexes.

These domains are unstructured and can evolve beyond the amino acid sequence recognition while retaining functional activity in different protein families from a wide range of organisms. This makes the W-domains hard to define and carry any comparative studies using classical bioinformatics methods.

The goal of this projects is to develop methods for identification of protein domains that are composed of extremely divergent sequences and still perform equate molecular function in cell. We have developed an composition-based algorithm and web application for AGO-binding sites discovery, which outperforms standalone programs.

Integrated genomics of maize

Revealing the molecular mechanisms underlying the differential herbicide resistance of maize lines

Maize is one of the most important crops in world's economy. In order to increase the production, the genetically modified lines are used, which feature increased resistance to herbicides. However similar levels of resistance can be acquired by plants in non-GMO manner, which is of special interest lately, considering public acceptance of GMO.

Within this project we are looking for genetic and molecular mechanism which could lead to gaining the herbicide resistance without introduction of foreign genes into plant system. We are trying to achieve the goal by multi-level analysis of two maize lines obtained with classical breeding methods which reveal substantial differences in glyphosate susceptibility. Our main scope is the computational analysis of the genome, epigenome and transcriptome sequencing data obtained from both lines.

Database & software development

Built with passion & intuitiveness in mind

Design a solution

Superimpose a logical structure upon the biological data on the basis of relationships between the different data elements.


Software development

Create a set of tools that allows for retrival and management of the biological information.


Web application

Present a user-friendly, intuitively graphical interface providing the user with best viewing experience of the website features.