Application of Graph Clustering and Visualisation Methods to Analysis of Biomolecular Data

In this paper we present an approach based on integrated use of graph clustering and visualisation methods for semi-supervised discovery of biologically significant features in biomolecular data sets. We describe several clustering algorithms that have been custom designed for analysis of biomolecular data and feature an iterated two step approach involving initial computation of thresholds and other parameters used in clustering algorithms, which is followed by identification of connected graph components, and, if needed, by adjustment of clustering parameters for processing of individual subgraphs.

Characteristic Topological Features of Promoter Capture Hi-C Interaction Networks

Current Hi-C technologies for chromosome conformation capture allow to understand a broad spectrum of functional interactions between genome elements. Although significant progress has been made into analysis of Hi-C data to identify the biologically significant features, many questions still remain open. In this paper we describe analysis methods of Hi-C (specifically PCHi-C) interaction networks that are strictly focused on topological properties of these networks. The main questions we are trying to answer are: (1) can topological properties of interaction networks for different cell types alone be sufficient to distinguish between these types, and what the most important of such propert…

Graph-based network analysis of transcriptional regulation pattern divergence in duplicated yeast gene pairs

The genome and interactome of Saccharomyces cerevisiae have been characterized extensively over the course of the past few decades. However, despite many insights gained over the years, both functional studies and evolutionary analyses continue to reveal many complexities and confounding factors in the construction of reliable transcriptional regulatory network models. We present here a graph-based technique for comparing transcriptional regulatory networks based on network motif similarity for gene pairs. We construct interaction graphs for duplicated transcription factor pairs traceable to the ancestral whole-genome duplication as well as other paralogues in Saccharomyces cerevisiae. We c…

Nicotiana tabacum L. hloroplastu izmantošanas iespējas cilvēku cilmes šūnu barotņu bagātināšanai un cilmes šūnu proliferācijas un morfoloģisko izmaiņu novērtējums

Lai izvērtētu izolētu tabakas hloroplastu potenciālu kā cilmes šūnu barotni bagātinošu līdzekli, FM-55-P cilvēka melanomas šūnas tika inkubētas 2 dienas ar izolētiem hloroplastiem, kas tika pievienoti šūnu kultūrai kā barotnes atšķaidījums vai kā hloroplastu piedeva. Tika noskaidrots, ka hloroplastu piedeva barotnei neizraisa ievērojamu proliferācijas samazinājumu salīdzinot ar barotnes atšķaidījumu un ka hloroplastu piedevas klātbūtnē melanocīti vairāk atraujas no kultūras virsmas bez šūnu nāves pazīmēm. Hloroplasti barotnē šķietami sadalījās un tika iekļauti melanocītu citoplazmā visos pievienošanas variantos. Izolētu hloroplastu ietekme uz melanomas šūnu kultūru tika vērtēta kā neizteikt…

Cilvēka 14. hromosomas proteasomu gēnu polimorfismu asociāciju ar multiplo sklerozi izpēte Latvijas populācijā

Proteasomālo gēnu polimorfismi ir autoimūnu slimību riska faktori. Lai novērtētu potenciālus multiplās sklerozes (MS) biomarķierus Latvijas populācijā, veicām proteasomālo gēnu PSMA6 un PSMC6 polimorfismu genotipēšanu 280 pacientiem ar MS diagnozi, ko salīdzinājām ar iepriekš ievāktiem datiem no 305 kontrolēm ar mērķi izpētīt iespējamo asociāciju starp šo lokusu polimorfismiem un MS. Tālākā analīzē kombinācijā ar iepriekšējiem PSMA3 polimorfismu genotipēšanas datiem atradām divus klīniski nozīmīgus multi-lokusu genotipus un trīs klīniski nozīmīgus haplotipus. Daļai pētīto polimorfismu novērojām no alēlēm atkarīgas alternatīvas DNS sekundārās struktūras. PSMA6 rs1048990 polimorfisma minorajā…

Graph-based characterisations of cell types and functionally related modules in promoter capture Hi-C Data

Topological structure analysis of chromatin interaction networks.

Abstract Background Current Hi-C technologies for chromosome conformation capture allow to understand a broad spectrum of functional interactions between genome elements. Although significant progress has been made into analysis of Hi-C data to identify biologically significant features, many questions still remain open, in particular regarding potential biological significance of various topological features that are characteristic for chromatin interaction networks. Results It has been previously observed that promoter capture Hi-C (PCHi-C) interaction networks tend to separate easily into well-defined connected components that can be related to certain biological functionality, however, …

Network motif-based analysis of regulatory patterns in paralogous gene pairs

Current high-throughput experimental techniques make it feasible to infer gene regulatory interactions at the whole-genome level with reasonably good accuracy. Such experimentally inferred regulatory networks have become available for a number of simpler model organisms such as S. cerevisiae, and others. The availability of such networks provides an opportunity to compare gene regulatory processes at the whole genome level, and in particular, to assess similarity of regulatory interactions for homologous gene pairs either from the same or from different species. We present here a new technique for analyzing the regulatory interaction neighborhoods of paralogous gene pairs. Our central focu…