Tools
Wednesday, 27th April, 2016, 12:00
Characterization of DNA sequence variants that affect pre-mRNA processing in multiple cancer types
In our lab we study alterations in splicing in multiple cancer types. These splicing alterations occur through somatic mutations in cis in introns and exons or through other mechanisms in trans. We recently published the largest analysis to date of the splicing alterations in cancer (Sebestyen et al. 2016) that includes an exhaustive analysis of the mutations, copy number variations and expression changes in RNA binding proteins and how these impact alternative splicing in multiple cancer. Our previous work lead us to some open ended question about mutations that affect splicing in cis. Therefore, currently we are developing a method for identifying and characterizing significantly mutated regions (SMRs) inside genes from whole genome sequencing (WGS) data and their impact on RNA processing in multiple tumors. I will be presenting some preliminary results about this project.
Speaker: Babita Singh - Computational Genomics group of GRIB (IMIM-UPF)
Room Aula room 473.10 (4th floor)
Wednesday, 30th March, 2016, 12:00
"Using protein regions to analyze cancer mutation profiles"
Speaker: Eduard Porta-Pardo - Sanford Burnham Prebys Medical Discovery Institute Bioinformatics, Genomics, Cancer, La Jolla, CA, USA
Room Aula room 473.10 (4th floor)
Wednesday, 16th March, 2016, 12:00
"Extracting biological data from the Science Literature"
Abstract: The scientific literature constitutes a rich and diverse source of information essential for any research line in life sciences. The volume of scientific publications is growing year by year generating a large accumulation of literature, due to the constant developments and advances in the biomedical domain. Text Mining (TM) emerges to address the need generated by the continuous growth of scientific literature in the biomedical domain. In this talk I will give an overview of TM and how it can help us to find relevant information from a large set of documents. I will present the BeFree System, a text mining tool developed as part of my PhD thesis and its application to different projects related to investigating the genetic basis of diseases, the therapeutic and undesired effects of drugs, and the effect of drugs in the environment.
Speaker: Alex Bravo - Integrative Bioinformatics group of GRIB (IMIM-UPF)
Room Aula room 473.10 (4th floor)
Wednesday, 9th March, 2016, 12:00
"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)
Thursday, 25th February, 2016, 11.00-12.00
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
Sunday, 6th December, 2015
DisGeNET: a discovery platform for translational bioinformatics
SWAT4LS International Conference 2015 in Cambridge, UK:
Speaker: Nuria Queral Rosinach, IBI Group, GRIB
Wednesday, 2nd December, 2015, 12:00
"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)
Monday, 30th November, 2015
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)
- Related links
- More details on the website course:
Thursday, 19th November, 2015, 11.00-12.00
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
Wednesday, 11th November, 2015, 12:00
"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)
