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Seminars, events & talks

Thursday, 15th September, 2016, 12.30 - 13.30

Computational Biophysics

Redesigning Drug Design of kinase inhibitors

Drug design lags far behind other engineering disciplines in lacking predictive, quantitative models that allow small-molecule therapeutics to be designed, rather than fortuitously discovered. While many challenges exist to building these models, our laboratory uses cycles of computational predictions coupled to experimental measurements to rapidly generate data that can be used to improve rigorous, quantitative approaches to small molecule design based on alchemical free energy calculations.  In this talk, we describe how this process can be done cheaply in an automated manner by inverting the drug discovery problem, and describe our first few steps toward this goal in the design of selective kinase inhibitors.
 

Speaker: John Chodera, Assistant Faculty Member, Computational Biology Memorial Sloan-Kettering Cancer Center, NYC, USA

Room Xipre Room (173.06-183.01), PRBB Building

Sunday, 4th September, 2016, 13:30 - 17:00 (half day tutorial)

Integrative Biomedical Informatics

Tutorial at ECCB 2016 - DisGeNET: a discovery platform to support translational research on human diseases

Recent technological breakthroughs have produced an unprecedented increase in the amount of data on the genetic determinants of diseases. To unveil the molecular mechanisms that underlie diseases and to support drug discovery projects, it is necessary to place these data in the context of the current biomedical knowledge. Despite the large volume of information available, its analysis and interpretation are hindered because it is annotated using different criteria and vocabularies and fragmented across different resources. Furthermore, a large fraction of data on diseases is only available as free text in biomedical publications. To overcome these difficulties we have developed DisGeNET (Piñero et al, 2015), a discovery platform that contains information on human diseases and their genes. In this tutorial we will provide an overview of the main features of DisGeNET, and then introduce the suite of tools that the platform offers to support translational research.  The tutorial includes a hands-on session organized around case studies that will illustrate how to use these tools. Materials will be made available via the DisGeNET website. Target audience: the tutorial is aimed at a variety of audiences: bioinformaticians, systems biology users, biologists, and healthcare practitioners.

Speaker: Laura I. Furlong and Janet Piñero - IBI group of GRIB (IMIM-UPF)

Room 15th European Conference on Computational Biology - The Hague, Netherlands - World Forum Convention Center

Monday, 30th May, 2016, 12:00

Integrative Biomedical Informatics

Making big sense from big data in toxicology

Scientific Sessions PRBB Organizer: PRBB_CRG Conferences. Hosts: Esther Barreiro & Ferran Sanz 

Speaker: Prof. Thomas Hartung, Center for Alternatives to Animal Testing, Doerenkamp-Zbinden Foundation. Evidence-based Toxicology, Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health. Baltimore, USA.

Room Marie Curie Room (Charles Darwin Sq.) PRBB.

Thursday, 12th May, 2016, 12:00

Functional Genomics

A population-level analysis of mutations affecting 5'ss splicing

Wild-type processing of RNA transcripts by the splicing machinery is a fundamental step in the gene expression pathway. Mutations affecting this step can produce aberrant splicing with deleterious effects that ultimately lead to disease. Mutation databases curating the scientific literature store an increasing number of single nucleotide variants (SNVs) inducing aberrant splicing involved in disease. Yet, this increase is far below the current growth rate of genetically profiled diseased individuals. This results in many SNVs of unknown effect. In this context, understanding the deleterious effects of SNVs on 5'ss splicing becomes extremely important to attempt a sensible prioritization of such SNVs. Population-level allele frequencies constitute a valuable resource to gather understanding of mutation processes. We have used the last release of the 1000 Genomes and the ExAC catalogs of human variation to characterize mutations that affect 5'ss splicing and attempt a sensible prioritization of such SNVs.

Speaker: Pau Puigdaval - Functional Genomics Group, GRIB (UPF-IMIM)

Room Aula room 473.10 (4th floor)

Wednesday, 4th May, 2016, 14:00

Biomedical Genomics

Tumour genomes shed light into mutational processes and cancer vulnerabilities

Speaker: Núria López-Bigas - Head of the Computational Genomics group of GRIB (IMIM-UPF)

Room Sala Marie Curie - Ground floor - PRBB

Friday, 29th April, 2016, 11.00 - 12.00

Computational Biophysics

Incremental Unsupervised Training of Deep Architectures

After a brief introduction to deep architectures and their typical supervised and unsupervised training approaches, the talk focuses on incremental strategies (at the base of natural learning). We will present our experience on incremental training of both CNN (Convolutional Neural Networks) and HTM (Hierarchical Temporal Memory). In particular a recently proposed semi-supervised tuning strategy (exploiting time coherence) proved to be very effective in conjunction with HTM, sometimes approaching supervised training accuracy.

Speaker: Davide Maltoni, University of Bologna (Dept. of Computer Science and Engineering - DISI)

Room Xipre Seminar (173.06)

Thursday, 28th April, 2016, 12:00

Computational Genomics

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)

Thursday, 31th March, 2016, 12:00

Biomedical Genomics

"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)

Thursday, 17th March, 2016, 12:00

Integrative Biomedical Informatics

"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)

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)



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