We have built a model of plant defence signalling response. It consists of 175 components and 524 reactions and is currently the most detailed model of salicylic acid, jasmonic acid and ethylene related signalling pathways available. The qualitative model was already used as hypothesis generator, two hypotheses are now being tested in the lab. The model also enables simulations and simple quantitative analysis which represents the basis for further more comprehensive analysis of plant defence signalling.
COBISS.SI-ID: 26363431
We have studied plant responses to pathogen attack on the level of gene expression using both DNA microarrays and quantitative real-time PCR. The results of these studies gave new insights into the physiology of interactions of potato wits its agronomically most important virus (PVYNTN ). We have confirmed several existing hypotheses and owing to systems biology approach we also got the overall picture of pathogen’s influence on energy equilibrium as well as on the dynamics of defence mechanisms in plant (Baebler et. al 2011 and KOGOVŠEK, et al. Aggressive and mild Potato virus Y isolates trigger different specific responses in susceptible potato plants. Plant Pathol., 2010 [COBISS.SI-ID 2254415], JCR IF: 2.237)
COBISS.SI-ID: 2492751
A robust system for reliable analysis of transcriptomics data was developed using data from our own DNA-microarray reuslts and will enable correct interpretation of omics data. Moreover tool for transcriptome data visualisation in the context of biological pathways was improved and adapted for our experimental systems. Data mining tool RelSets was also applied to complement standard statistical analysis tools (Rotter et al., 2010, COBISS.SI-ID 2210383).
COBISS.SI-ID: 27756761
We propose an approach to support modelling of plant defence response to pathogen attacks. Such models are currently built manually from expert knowledge, experimental results, and literature search, which is a very time consuming process. Manual model construction can be effectively complemented by automated model extraction from biological literature. This work focuses on the construction of triplets in the form of subject-predicate-object extracted from scientific papers, which are used by the Biomine automated graph construction and visualisation engine to create the biological model. The approach was evaluated by comparing the automatically generated graph with a manually developed Petri net model of plant defence. This approach to automated model creation was explored also in a bisociative setting. The emphasis is not on creative knowledge discovery, but rather on specifying and crossing the boundaries of knowledge of individual scientists. This could be used to model the expertise of virtual scientific consortia.
COBISS.SI-ID: 25940263