We are very pleased to announce that Dr. Alfonso Valencia will be the guest speaker of our upcoming Sven Furberg Seminar in Bioinformatics and Statistical Genomics on Thursday November 22nd at 1.00pm (note the new time!) in room 230, Inst. for Media og Kommunikasjon, Forskningsparken (https://www.mn.uio.no/ifi/english/research/networks/clsi/seminars/dr.-alfonso-valencia.html).
 
Dr. Alfonso Valencia, Group Leader and Director of the Life Sciences Department of the Barcelona Supercomputing Center, will present the lecture "Networks based approaches in biology and biomedicine."
 
Meeting Dr. Valencia
If you want to meet Dr. Alfonso Valencia, please book a time slot at https://doodle.com/poll/eqrwee9qmcst6ebc and send an email to anthony.mathelier@ncmm.uio.no.
 
Abstract
The representation of biological objects as networks has become a full filed of research on its own. In this talk, I will present three different areas of research in which my group is developing and applying network based methods.

In the first area, we study comorbidities, defined as the presence of one or more additional diseases co-occurring with a primary disease or disorder. Large direct comorbidity networks have been previously constructed based on the presence of disease identifiers (ICD codes) in HER by the Barabasi and Brunak’s groups. We also know about disease relations from population studies. We have proposed a different approach to the study of comorbidity based on the comparison of gene expression profiles. Using this approach, we have described some of the potential molecular basis of the relations between central nervous system disorders (CNSd) and cancer.
More recently, we have analyzed the gene expression profiles of thousands of individuals classified in 133 diseases with information available in public databases. The resulting network connects pairs of patients with a significant overlap between genes, positively if they are deregulated in the same direction and negatively if they are oppositely-regulated. This gene expression-based network has a significant similarity with the ones produced by the Barabasi and Brunak groups. The clustering of the patient based comorbidity network, reveals that patient-subgroups labelled with the same disease tag can have very different - and even opposite- relations with groups of patients with other diseases. These specific relations between groups can be interpreted in terms of direct and inverse comorbidity relations specific of groups of patients, moving the study from the general concept of disease comorbidity to specific relations between groups of patients within each specific disease.

In the second application of network methods, we processed heterogeneous ChIP-Seq information to build a comprehensive genome co-localization network of Chromatin Related Proteins (CRPs), histone marks and DNA modifications in mouse embryonic stems cells. In this network, co-localization preferences can be translated into specific of “mESC Chromatin States”, such as active regions or enhancers. The study of the properties of the “co-localization” network points to the 5hmC DNA modifications, as the key component in the organization of the mouseESC network. The importance of 5hmC, as organizer of the epigenetic network, was reinforced by the evolutionary analysis of the protein components of the network. There, 5hmC acts as a mediator in the co-evolution of the CRPs protein components of the mESC network.
We then investigated the mESC Epigenetic Properties and Chromatin States, by analysing them in the context of the structure of the chromatin in the cell nucleus. The results revealed interesting properties of the organization of the mESC epigenetic control system, in line with the emerging models of gene expression control and chromatin organization, and support the role of 5hmC as a factor present in a significant number of interactions related with active transcription in mouse embryonic stems cells.

Finally, in the third network based approach we analysed the potential consequences at the introduction of chimeric proteins product of chromosomal translocations in protein interaction networks, with particular focus in the implications for the connectivity of oncogenes and tumor suppressors.
 
More information at https://www.mn.uio.no/ifi/english/research/networks/clsi/seminars/dr.-alfonso-valencia.html.
 
Looking forward to seeing you all at the seminar.

Best
Anthony Mathelier

Dr. Alfonso Valencia