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Seminars, events & talks

Thursday, 10th March, 2016, 12:00

Evolutionary Genomics

"The evolution of antisense gene expression"

Abstract: The advent of high­throughput genomic technologies has revealed that the transcriptome is more complex than initially thought. There are thousands of loci that transcribe transcripts that lack long conserved ORFs. Antisense transcripts or natural antisense transcripts are an intringuing class of RNAs transcribed from the opposite strand of a known gene. While some of these genes are reported to be functional, most of them are likely to be byproducts of the high transcriptional activity of the genome. We use deep strand­specific RNA sequencing to quantify and characterize the presence of antisense genes in human, finding that antisense transcription is widespread and that a high proportion of protein­coding genes are associated to antisense transcripts. We classify the age of antisense genes using homology searches against the transcriptomes assembled in chimpanzee, macaque and mouse. Birth and turnover of antisense genes is common in the primate lineage, being most of those genes non­coding and non­functional. We further find evidences of new translated proteins in some of those antisense genes, indicating that, from an evolutionary perspective, these transcripts are not useless, as they provide the 'raw material' for the evolution of new molecular functions mapper"

Speaker: Jorge Ruiz Orera - Evolutionary Genomics group of GRIB (IMIM-UPF)

Room Aula room 473.10 (4th floor)

Friday, 26th February, 2016, 11.00-12.00

Computational Biophysics

Deep Neural Networks and Reinforcement Learning for Building Intelligent Machines.

The goal of Artificial Intelligence (AI) is to build machines that can display complex behavior, such as for example reaching human level performance in some tasks. The Machine Learning approach to achieve this goal is to provide the machine with a powerful mathematical framework and data from which complex behaviors can be learned. In this talk, I will introduce deep neural networks and reinforcement learning, which are considered two of the most promising mathematical frameworks solving difficult tasks in many different domains, and discuss their strengths and challenges.

Speaker: Dr. Silvia Chiappa, Senior Researcher at Google Deep Mind, UK.

Room Charles Darwin Room

Monday, 7th December, 2015

Integrative Biomedical Informatics

DisGeNET: a discovery platform for translational bioinformatics

SWAT4LS International Conference 2015 in Cambridge, UK:

Speaker: Nuria Queral Rosinach, IBI Group, GRIB

Thursday, 3rd December, 2015, 12:00

Functional Genomics

"Umbilical cord gene expression reveals the molecular architecture of the fetal inflammatory response in extremely preterm newborns"

The fetal inflammatory response (FIR) in placental membranes to an intrauterine infection often precedes premature birth raising neonatal mortality and morbidity. However, the precise molecular events behind FIR still remain largely unknown, and little has been investigated at gene expression level. We collected publicly available microarray expression data profiling umbilical cord (UC) tissue derived from the cohort of Extremely Low Gestational Age Newborns (ELGANs) and interrogate them for differentially expressed (DE) genes between FIR and non-FIR affected ELGANs. We found a broad and complex FIR UC gene expression signature, changing up to 19% (3,896/20,155) of all human genes at 1% false discovery rate (FDR). Significant changes of a minimum 50% magnitude (1,097/3,896) affect the upregulation of many inflammatory pathways and molecules, such as cytokines, toll-like receptors, and calgranulins. Remarkably, they also include the downregulation of neurodevelopmental pathways and genes, such as fragile-X mental retardation 1 (FMR1), contactin 1 (CNTN1) and adenomatous polyposis coli (APC). The FIR expression signature in UC tissue contains molecular clues about signaling pathways that trigger FIR, and it is consistent with an acute inflammatory response by fetal innate and adaptive immune systems, which participate in the pathogenesis of neonatal brain damage.

Speaker: Robert Castelo - Functional Genomics Group, GRIB (IMIM-UPF)

Room Aula room 473.10 (4th floor)

Tuesday, 1st December, 2015

Integrative Biomedical Informatics

DisGenet RDF&SPARQL: how to use + modeling challenges

Upcoming PhD course on Semantic Web technologies offered by SIB in Geneva. We are pleased to announce that a lecture on DisGeNET-RDF developed in the IBI group is included in the course "Using the Semantic Web for faster (Bio-)Research", Geneva 30 November till 3 December 2015. Accessing and using existing public data is a hassle, yet it is crucial for designing good experiments. This 4 day course, co-organized by SIB and CUSO/Staromics, will teach PhD students on how to use semantic web technologies for their own research. It includes an in-depth exploration of Semantic Web concepts such as RDF (data modelling), SPARQL (asking questions on your data), OWL (reasoning for deducing new facts about your data) The course will teach you how to use these technologies in your day to day research, as well as how you can share your data with the rest of the world.

Speaker: Núria Queralt Rosinach, IBI Group (GRIB)

Friday, 20th November, 2015, 11.00-12.00

Evolutionary Genomics

Comparative genomics of bats: the secret of extended longevity?

Of all mammals, bat possess the most unique and peculiar adaptations that render them as excellent models to investigate the mechanisms of extended longevity and potentially halted senescence. Indeed, they are the longest-lived mammals relative to their body size, with the oldest bat caught being 41 years old, living approx. 9.8 times longer than expected. Bats defy the 'rate-of-living' theories that propose a positive correlation between body size and longevity as they use twice the energy as other species of considerable size, but live far longer. The mechanisms that bats use to avoid the negative physiological effects of their heightened metabolism and deal with an increased production of deleterious Reactive Oxygen Species (ROS) is not known, however it is suggested that they either prevent or repair ROS damage. Bats also appear to have resistance to many viral diseases such as rabies, SARS and Ebola and have been shown to be reservoir species for a huge diversity of newly discovered viruses. This suggests that their innate immunity is different to other mammals, perhaps playing a role in their unexpected longevity. Here the potential genomic basis for their rare immunity and exceptional longevity is explored across multiple bat genomes and divergent 'ageing' related markers. A novel blood based population-level transcriptomics approach is developed to explore the molecular changes that occur in an ageing wild population of bats to uncover how bats 'age' so slowly compared with other mammals. This can provide a deeper understanding of the causal mechanisms of ageing, potentially uncovering the key molecular pathways that can be modified to halt, alleviate and perhaps even reverse this process in man.

Speaker: Emma Teeling, School of Biology and Environmental Science, University College Dublin, Ireland

Room Ramón y Cajal Room

Thursday, 12th November, 2015, 12:00

Evolutionary Genomics

"Linneage specific genes and evolutionary innovation in mammals"

The birth of new genes de novo from previously non-genic genomic regions is increasingly being recognized as an important mechanism of evolutionary innovation. However, these genes, which do not have homologues outside the species or taxon, remain poorly characterized. Here we used 68 complete genome sequences from different mammalian species to obtain the first global census of protein coding gene families likely to have originated in the past 200 Million years of mammalian evolution.

Speaker: JOSE LUIS VILLANUEVA - Evolutionary Genomics, GRIB

Room Aula room 473.10 (4th floor)

Thursday, 12th November, 2015, 12:00

Integrative Biomedical Informatics

"Uncovering disease mechanisms through network biology in the era of next generation sequencing"

Characterizing the behavior of disease genes in the context of biological networks has the potential to shed light on disease mechanisms, and produce new candidate disease genes and therapeutic targets. Previous studies addressing the network properties of disease genes have produced seemingly contradictory results. We have explored the causes of these seeming discrepancies and assessed the relationship between disease genes' network roles and their tolerance to deleterious germline variants in human populations leveraging on: different interactome resources, a comprehensive catalog of disease genes and exome variation data. We found that the most salient network features of disease genes are driven by cancer genes and that genes related to different types of diseases play network roles whose centrality is inversely correlated to their tolerance to likely deleterious germline mutations. This proved to be a network multiscale signature, including global, mesoscopic and local network centrality features. Cancer driver genes, the most sensitive to deleterious variants, occupy the most central positions, followed by dominant disease genes and then by recessive disease genes, which are tolerant to variants and isolated within their network modules.

Speaker: JANET PIÑERO Biomedical Informatics, GRIB

Room Aula room 473.10 (4th floor)

Thursday, 5th November, 2015, 12:00

Integrative Biomedical Informatics

DisGeNET: a discovery platform for translational bioinformatics (PRBB Computational Genomic Seminars)

In this talk I will present the DisGeNET Discovery Platform for the dynamical exploration and analysis of human diseases and their genes. The platform consists of a comprehensive knowledge base of over 400,000 gene-disease associations arising from both expert-curated databases and information extracted from the scientific literature using text mining, with special attention paid to the explicit provenance of the association. The DisGeNET platform provides a set of analysis tools designed to facilitate and foster the study of the molecular underpinning of human diseases. The talk will also illustrate the semantic knowledge representation of DisGeNET, and how to explore and analyze the data using different tools with special emphasis on harnessing the data using Semantic Web technologies.

Speaker: Núria Queralt Rosinach, IBI Group (GRIB)

Room Aula room 473.10 (4th floor)

Thursday, 5th November, 2015, 12.00-13.00

Computational Biophysics

The Virtual Human: In Silico Methods for Personalised Medicine

The era of personalised medicine offers at once a huge opportunity and a major challenge to computational science. The potential impact centres around our ability to marshall substantial quantities of patient data and to use them to perform predictive, mechanistic modelling and simulation in order to deliver therapies and to enhance clinical decision making, on time scales which are far shorter than those usually considered in the context of academic research and development activities. Secure access to personal data, as well as to powerful computational resources, is essential. I shall provide a couple of examples which illustrate the current state of the art. One addresses clinical decision support in the context of blood flow within neurovascular pathologies; the other is concerned with patient specific drug discovery and treatment. We shall discuss the underlying e-infrastructure requirements, including data, compute and networks, and reflect on the potential for cloud and other forms of e-infrastructure provision to meet the anticipated future demand for resources.

Speaker: Peter V. Coveney, Department of Chemistry, UCL.

Room Charles Darwin Room



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