Tools
Thursday, 21th March, 2013, 11:00-12:00
High-resolution mapping of trans-acting associations in eQTL networks
Speaker: Inma Tur
Room Room Aula (473.10 - 4th floor)
Thursday, 7th March, 2013, 11:00
Unraveling the mechanisms of tumorigenesis
Speaker: Abel Gonzalez-Perez & David Tamborero - Biomedical Genomics, GRIB-UPF
Room Aula (473.10)
Friday, 7th December, 2012, 12:00 - 13:00
Pathway driven prediction of mutation impact in cancer
Josh Stuart, from the Systems Biology Group of the University of California, Santa Cruz, USA, uses data-driven approaches to identify and characterize genetic networks, investigates how they've evolved, and then uses them to simulate and predict cellular behavior. His approach is to design computational models and algorithms that integrate highthroughput molecular biology datasets to predict cellular- and organism-level phenotypes. He particularly focuses on elucidating altered signalling pathways in cancer cells that initiate and drive tumorgenesis and is developing models to predict the impact of mutations in human tissue and a patient's response to treatment. Speaker's list of publications: http://www.ncbi.nlm.nih.gov/pubmed?term=joshua%20stuart
Speaker: Josh Stuart, Systems Biology Group-University of California, Santa Cruz, USA
Room Marie Curie Room
Thursday, 8th March, 2012, 11:00
Structure and age jointly influence rates of protein evolution
What factors determine a protein's rate of evolution are still under debate. Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate. We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group – including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate, and younger proteins, despite of being less designable, are evolving faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and also more robust to mutations, than younger ones. Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution.
Speaker: Macarena Toll - Biomedical Informatics, GRIB (IMIM - UPF)
Room Aula
Thursday, 1st March, 2012, 11:00
Troublemakers in cancer: a tale of usual suspects and novel villains
The expansion of the catalogs of somatic alterations in cancer accelerate as new laboratories release the sequences of cohorts of samples of different tumor types. One of the key challenges posed by this growth is the identification of driver alterations, genes and pathways among all the alterations found in several patients with the same disease. Traditionally, likely driver mutations for instance are identified either by their recurrence or by their impact on protein function. On the other hand, genes and pathways are prioritized according to the recurrence of alterations that they bear in such groups of samples, however this approach have some known limitations. We have developed an approach to improve the capability of known tools to assess the functional impact of somatic mutations, based on correcting their scores by the baseline tolerance of their bearing proteins. Also, we have developed a method to uncover cancer drivers based on the detection of the bias towards the accumulation of variants with high functional impact across several tumor samples. We present the results of applying this method to several cancer datasets and show that very different pathways to tumorigenesis prevail in each of them.
Speaker: Abel Gonzalez-Perez - Biomedical Informatics, UPF
Room Aula
Wednesday, 11th January, 2012, 12:00
Cracking the cancer code, a bioinformatics journey
Nuria Lopez-Bigas obtained her PhD for work on the molecular causes of hereditary deafness at the group of Xavier Estivill. After a postdoc on computational genomics at the European Bioinformatics Institute (with Christos Ouzounis) and at the CRG (with Roderic Guigó), she established her laboratory at the University Pompeu Fabra in 2006. In 2011 she was appointed ICREA research professor. Thanks to the advance of genomic technologies it is currently possible to obtain a comprehensive catalog of genomic alterations in cancer cells. However the identification of alterations directly involved in the development of the tumor is challenging. Nuria Lopez-Bigas current research focuses on the development of computational approaches to analyse cancer genomic data with the objective to identify genes and pathways driving tumorigenesis.
Speaker: Nuria López-Bigas, GRIB (IMIM - UPF)
Room Auditorium PRBB
Thursday, 17th November, 2011, 11:00-12:00
Co-Alterations in Human Cancer
Big efforts are being made to reveal the alterations that have occurred in the genomes of cancerous cells. Especially the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) will contribute by collecting data in a standardized way and make it publicly available. With the already available data, an abundance of alterations of different types have been found – some so-called driver alterations that drive the cell towards its cancerous state and some passenger alterations that are a by-product of the cancer development. It is an ongoing challenge to discriminate driver from the passenger mutations even though a variety of methods have been proposed up to this day. These include methods based on recurrence of alterations (RBM) across a cohort of samples and sequence based methods (SBM) that assess the impact of mutations on the functionality of the protein product. We are working on how to detect the coaltered pairs that are candidates for having a synergistic effect. We hypothesize that some driver alterations may only have their driver effect when occurring with a certain other driver alteration – synergistic drivers. This could be reflected by either the strict co-occurrence of the driver alterations along the samples and/or similar expression patterns of reporter genes of the candidate drivers.
Speaker: Michael P. Schroeder
Room 473.10_Aula
Tuesday, 21th June, 2011
Course on Bioinformatics for Integrative Genomics
We are pleased to announce that registration for the Course on Bioinformatics for Integrative Genomics for June 21th- 22th at UPF facilities is now open.The course is organized by the Biomedical Genomics lab of GRIB (IMIM-UPF). The objective of the course is to provide theoretical and practical expertise in the field of bioinformatics for integrative genomics. Attendees will learn how to handle and analyze genomic data to answer specific questions using tools developed in the Biomedical Genomics lab: IntOGen, Gitools and Condel. Registration is free, but limited places available. We strongly recommend you to register asap. To register: send a CV and a motivation letter to Melquíades Calzado(mcalzado@imim.es).
Speaker: Biomedical Genomics lab of GRIB (IMIM-UPF)
Room UPF facilities
Friday, 6th May, 2011, 11:00
Thesis of Alice Ledda: “Distribution and evolution of short sequence tandem repeats in eukaryotic genomes”
We investigated the use of next generation sequencing data, from the 1000 Genomes Pilot Projects, to quantify microsatellite variability in the human population and discover putative new loci involved in trinucleotide repeat expansion diseases. We analysed microsatellites phylogenetic conservation to learn about the role of selection in shaping microsatellite evolution. The first study concluded that in vertebrate lineages amino acid tandem repeats were more conserved than similar sequences located in non-coding regions. This lead us to the conclusion that evolution was preserving repeats in protein-coding regions. In a second stage we analzed the conservation of microsatellites in different genomic regions, comparing them with the conservation of microsatellite in intergenic region. We concluded that selection was not preserving microsatellites only in exons but also in other genomic regions.
Room room Josep Marull, Dr. Aiguader 80.
Wednesday, 26th January, 2011, 12:00 pm
Analysis and manipulation of phylogenomic data using ETE
ETE is a python programming library that assists in the automated manipulation, analysis and visualization of phylogenetic trees. It allows to read trees in Newick format and operate with them as very intuitive python objects, providing advanced methods to locate nodes, browse tree topology, annotate branches, or manipulate node connections. In addition, ETE provides a fully customizable system for tree visualization. Users can visualize trees interactively or write their own python functions to create tree images in PDF or SVG format. Although ETE is mainly focused on phylogenetic analysis (i.e. connectors to the phylomeDB database, orthology and paralogy detection, tree reconciliation) it can be also used to deal with any type of data that can be represented as a hierarchical tree. For instance, microarray clustering results are phylogenetic profiles are well supported. Starting from version 2.1, ETE will provide a new module to add interactive phylogenetic trees within web pages (see http://phylomedb.org/?q=search_tree&seqid=Phy00085K5_HUMAN for an example) and support for the PhyloXML and NeXML formats. Some ETE examples can be found at http://ete.cgenomics.org/examples With this short tutorial I will introduce the most basic functionality and the potential use of the different ETE modules. A comprehensive practical course on ETE and related tools is scheduled by the beginning of March 2011.
Speaker: Jaime Huerta Cepas. Comparative Genomics Group. Bioinformatics & Genomics Programme. CRG
Room room 470 Sem 2
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