Department of Bioinformatics – BiGCaT

BiGCaT Science Cafe


Schedule 2017

Date Time Room Presenter Topic Abstract Slides
26 Oct 16:00-17:00 Nasim Sangani
12 Oct 16:00-17:00 Ryan Miller
28 Sep 16:00-17:00 Martina Summer-Kutmon
14 Sep 16:00-17:00 Samar Tareen
Summer break
13 Jul 16:00-17:00 UNS50/3.142A Mirella Kalafati
29 Jun 16:00-17:00 UNS50/4.140a Amadeo Muñoz García New insights into the innate immune effects of vitamin D: a meta-analysis of transcriptomics data at pathway level Abstract  Slides
01 Jun 16:00-17:30 UNS50/4.140a Elisa Cirillo The system biology concept applied to a secondary analysis of Body Mass Index GWAS data Abstract  Slides
18 May 16:00-17:30 UNS50/4.140a Denise Slenter A (FAIR) new view on dataset MTBLS1 Abstract Slides
04 May 16:00-17:30 UNS50/4.140a Marvin Martens The future of regulatory risk assessment Abstract Slides
13 Apr 16:00-17:30 UNS50/4.140a Ilona Liesenborghs Challenges to see patterns in reused data; Identifying molecular pathways that characterize the trabecular meshwork tissue of the eye. Abstract Slides
12 Jan 16:00-17:30 UNS50/4.140a Friederike Ehrhart Rett syndrome – a meta study on human raw transcriptomics data Abstract Slides

Schedule 2016
Previous schedule


Abstracts

29 June 2017 – Amadeo Muñoz García

Title: New insights into the innate immune effects of vitamin D: a meta-analysis of transcriptomics data at pathway level

In the last decade a wide range of studies have highlighted a role for vitamin D in human immune responses, but the precise mechanisms by which vitamin D achieves these effects is much less clear. Recent reports have documented regulation of gene expression in immune cells by the active form of vitamin D, 1,25-dihydroxyvitamin D (1,25D), using candidate gene or unbiased genomic screening strategies to provide cell model-specific data. The current study utilised existing gene expression databases from multiple related monocyte models (the THP-1 monocytic cell line (THP-1), monocyte-derived dendritic cells (DCs), and monocytes) to provide a broader perspective on common gene regulatory pathways associated with innate immune responses to 1,25D. A bioinformatic workflow incorporating pathway analysis using Pathvisio and WikiPathways was utilised to compare each set of gene expression data based on pathway level context. Using this strategy, pathways related to the TCA cycle, oxidative phosphorylation and ATP synthesis and metabolism were shown to significantly regulated by 1,25D in each of the repository models (Z scores 3.52 – 8.22). Common regulation by 1,25D was also observed for pathways associated with apoptosis and the regulation of apoptosis (Z scores 2.49 – 3.81). In contrast to the primary culture DC and monocyte models, the THP-1 myelomonocytic cell line showed strong regulation of pathways associated with cell proliferation and DNA replication (Z scores 6.1 – 12.6). VDR expression is common to multiple immune cell types and thus pathway analysis of gene expression using data from multiple related models provides an inclusive perspective of the immunomodulatory impact of vitamin D. In particular, analyses presented here support a fundamental role for active 1,25D as a pivotal regulator of immunometabolism.

 

01 June 2017 – Elisa Cirillo

Title: The system biology concept applied to a secondary analysis of Body Mass Index GWAS data

Elisa’s talk will explain the current project related to the secondary analysis of BMI GWAS study. She will give an overview of three different projects that combined several types of data (SNPs associated to BMI, pathways, eQTLS and epigenetics information) in order to elucidate the genetic influence of SNPs in obesity.

18 May 2017 – Denise Slenter

Title: A (FAIR) new view on dataset MTBLS1

Metabolights is a database where metabolomic datasets can be stored with the intention that other researchers can (re)use them. In order to test how FAIR (https://www.nature.com/articles/sdata201618) this database is, we performed a review on the first dataset entered in here (MTBLS1), in the hopes of obtaining a new view on this dataset.

 

4 May 2017 – Marvin Martens

Title: The future of regulatory risk assessment.

In order to decrease costs, lower the animal use and iprove the overall effectiveness of regulatory risk assessment, Adverse Outcome Pathways (AOPs) emerged to fascilitate the descision making in risk assessment. This presentation will serve as an explanation on the concept of AOPs, explaining their general layout, purpose and creation. Besides, the project of Marvin will be introduced on the topic of AOPs.

 

13 April 2017 – Ilona Liesenborghs

Title: Challenges to see patterns in reused data; Identifying molecular pathways that characterize the trabecular meshwork tissue of the eye.

Ilona would like to discuss the research she is currently performing on 16 different gene expression datasets of healthy eye tissue (more specified, the trabecular meshwork): the methods, the problems we experienced in analysing and combining the data, the ‘solutions’ and the preliminary results.

12 January 2017 – Friederike Ehrhart

Title: Rett syndrome – a meta study on human raw transcriptomics data

Rett syndrome is a rare disorder causing severe intellectual and physical disability. The cause of the disorder is a mutation in one single gene, methyl-CpG binding protein 2 (MECP2). This gene is a multifunctional regulator of gene transcription, translation and epigenetic transcriptional regulation. Purpose of the study was to investigate changed gene expression in human cells with an impaired MECP2 gene to identify the downstream effects. For this we used raw transcriptomics data from five previously published studies. We extracted information about changed gene expression for each of the twelve experimental subgroups and identified the genes and biological pathways which are overlappingly affected by an impaired MECP2 gene using a hypothesis free data-driven approach. We checked the changed gene expression of known downstream targets of MECP2 and found rarely significant changes in the different experimental groups. There were no genes which are changed in all experimental groups but we identified a set of genes which are significantly changed in several transcriptomics datasets but not mentioned in the context of Rett syndrome before. Using pathway and network approaches (including network extension) we found that these genes are involved in several processes and molecular pathways which are known to be affected in Rett syndrome. We suspect these genes to be the links between gene and phenotype pathways.