We have developed an interactive web application called dictyExpress (www.ailab.si/dictyexpress), which offers a complex gene expression data analytics in a easy-to-use graphical interface. The methods behind dictyExpress and the design of the application was done in collaboration with Baylor College of Medicine. dictyExpress is directly linked from D. discoideum's genome home page (www.dictybase.org) and is in frequent use by researchers worldwide since October 2009.
COBISS.SI-ID: 7219028
Gene expression data sets is a typical and very rich source of information for systems biology research. Typically, they include many records (at least few thousands genes and possibly many different experiments). The data often includes much noise. Integration of this data with other data and knowledge sources, which are in systems biology in abundance, is a must for any data analytics. Paper discusses the developments in this field and outlines the directions for future research.
COBISS.SI-ID: 6188372
We have developed a new rule-based clustering algorithm (RBC) that is able to infer the common promoter structure of co-expressed genes. RBC is based on the beam-search algorithm CN2 and the clustering-tree algorithm. Our extension allows the identification of overlapping groups of genes, and it implements a heuristic that drastically reduces the search space. We have applied RBC to model the promoter structure and gene expression of D. discoideum, which was included in the organism’s reference database (www.dictyBase.org) and published in a joint publication.
COBISS.SI-ID: 6916180
Kin discrimination determines the cooperation and survival of social amoebas D. discoideum under starvation. We have modeled the relation between two highly polymorphic genes (lagB1 and lagC1) that play a crucial role in kin discrimination. The predictive model was built from sequence of polymorphic alleles in both genes and from strain segregation among 29 strains. The findings reveal the evolutionary origin of kin discrimination and provide an insight into the mechanisms of social recognition and immunity.
COBISS.SI-ID: 7027796
A new and improved method for image acquisition and data analysis using high-content microscopy on a genome-wide level in yeast is described in the article. The method is based on confocal microscopy using an automated microscope which enables analysis of app. 1000 samples per day. In the proof-of-concept study we confirmed the identity of all 17 known genes required for peroxisome biogenesis, which took 15 years to complete using more traditional approaches.
COBISS.SI-ID: 22360871