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Seminars, events & talks

Thursday, 28th November, 2013, 11:00

Computational RNA Biology

"Alteration of alternative splicing and RNA binding proteins across multiple tumors"

Current cancer genomics projects apply high-throughput technologies to discover recurrent genetic variations in patient samples. These efforts are crucial to describe the genetic diversity of cancer and to classify into novel subtypes for improved prognosis and therapeutics. These genome-scale studies focus mostly on the detection of alterations of the DNA and the expression of genes. However, alterations in Alternative Splicing (AS), which hold important signatures that can provide novel prognostic and therapeutical strategies, have not been yet thoroughly characterized. We have used RNA sequencing data from The Cancer Genome Atlas (TCGA) project for hundreds of tumor samples and paired normal tissues to study the splicing changes and differential expression of Splicing Factors (SFs) and RNA binding proteins (RBPs) in 13 different cancer types. We find new proteins and splicing events that are recurrently altered in tumors. Additionally, by using correlations, we detect possible association of RBPs and events, suggesting splicing regulatory modules. Our analysis indicates that different cancers present similar alterations, suggesting a general path for cells towards cancer by concurrent splicing alterations. This analysis provides useful information to elucidate the impact of alternative splicing in the functional dynamics of cell transformation in multiple cancer types and may help uncovering novel therapeutic strategies.

Speaker: Eduardo Eyras - Computacional Genomics group of GRIB (IMIM - UPF)

Room Aula (473.10)

Thursday, 9th February, 2012, 11:00

Computational RNA Biology

Development and analysis of a chordate and plant orthologous promoter database

Speaker: Endre Sebestyen. Regulatory Genomics Group- GRIB

Room Aula

Wednesday, 18th January, 2012, 12:00h

Computational RNA Biology

Understanding RNA through massively parallel sequencing (RNA in the ENCODE project)

The unfolding of the instructions encoded in the genome is triggered by the transcription of DNA into RNA, and the subsequent processing of the resulting primary RNA transcripts into functional mature RNAs. RNA is thus the first phenotype of the genome, mediating all other phenotypic changes at the organism level caused by changes in the DNA sequence. While current technology is too primitive to provide accurate measurements of the RNA content of the cell, the recent development of Massively Parallel Sequencing Instruments has dramatically increased the resolution with which we can monitor cellular RNA. Using these instruments, the ENCODE project has surveyed the RNA content of multiple cell lines and subcellular compartments. The results of these surveys underscore pervasive transcription, as well as great RNA heterogeneity between and within cells. Comparison of RNA surveys with other genome wide epigenetic surveys—such as those of binding sites for Transcription Factors, or of Histone modifications—reveals a very tightly coupling between the different pathways involved in RNA processing, transcription and splicing in particular.

Speaker: Roderic Guig├│, CRG

Room Auditorium PRBB

Thursday, 26th May, 2011, 11:00

Computational RNA Biology

An integrative approach for epigenetic data analysis

"High-Throughput sequencing (HTS) has revolutionized the study of gene regulation and expression.
However, there is a strong need for methods that facilitate the integration of multiple datasets to build predictive models. We present a computational framework to analyze and integrate epigenetic data, which allows the development of predictive models of gene regulation. Within this framework, we provide tools to carry out analysis of HTS data from DNA-protein binding, RNA-protein binding and RNA expression assays.
In particular, we have developed a method that can effectively characterize significant changes in epigenetic patterns genome-wide, including promoters, enhancers and genic regions. Furthermore, we provide a tool for building predictive models based on Machine Learning (ML) from multiple datasets. Using the published datasets, we show that our ML methodology allows us to predict the expression change from chromatin properties with 95% accuracy. Additionally, our tools allow the integration of a variety of input datasets and the application of many different ML methods. We finally discuss how this computational framework can be applied to the study of the epigenetic changes in cancer."

Speaker: Eduardo Eyras - Computational Genomics, UPF

Room 473.10 PRBB

Thursday, 5th May, 2011, 11:00 AM

Computational RNA Biology

Pyicos: a versatile toolbox for regulatory genomics"

A revolution is taking place in the study of gene regulation: High-throughput sequencing has become the basis of various techniques, like ChIP-Seq, RNA-Seq, CLIP-Seq, and new techniques evolve constantly. But do we need a new specialized tool to analyze each data type? Not necessarily! We propose Pyicos (, a generic tool that can adapt to various data types, by providing operations that are typically required for their manipulation and analysis. Pyicos is open-source and its input are genomic positions obtained from the mapper of choice. We show the high accuracy of Pyicos by comparing it to methods, specifically designed for the analysis of ChIP-Seq, RNA-Seq or CLIP-Seq data. With its flexibility and suitability for integration, Pyicos provides a convenient basis for the study of gene regulation.

Speaker: Sonja Althammer - Biomedical Informatics, UPF

Room 473.10_Aula

Thursday, 14th April, 2011, Thu, Apr 14, 2011 11:00 AM - Thu, Apr 14, 2011 12:00 PM

Computational RNA Biology


Speaker: Larry Stanton - Deputy director of GIS Singapore

Room 473.10 PRBB

Wednesday, 20th October, 2010, 11:00

Computational RNA Biology

Analyzing Chip-Seq mapped reads with Pyicos and bash: Command-line real time examples.

When provided with some files with mapped reads coming from a Chip-Seq experiment, lots of the work has already been done. Extracting the biological information from them should be an easy job, right? Surprisingly, lots of bioinformaticians are finding that the methods and software packages proposed for the analysis of this kind of data doesn’t fit their particular needs. Because these experiments have gone through a long process and they commonly targets a particular Protein-DNA interactions, this last step normally takes longer than expected. Moreover, the technical difficulties of dealing with read files that can be on the Gigabyte-Scale, the different formats used by different laboratories and tools and the novelty of the field are extra headaches for the researcher performing this kind of analysis. This seminar is designed as an introduction where I will work in real-time with a sample dataset, showing how to use bash and Pyicos, a novel toolbox for the analysis of mapped reads coming from Deep Sequencing experiments.

Speaker: Juan Gonzalez-Vallinas-Regulatory Genomics Group, GRIB

Room PRBB room 173.06-183.01 (Xipre)

Thursday, 20th May, 2010, Thu, May 20, 2010 11:00 AM

Computational RNA Biology

"Predicting Alternative Splicing in Yeast"

Speaker: Mireya Plass Host lab: Eduardo Eyras, Computational Genomics, UPF

Room Room 473.10 AULA - 4th floor

Thursday, 28th May, 2009, 11:00

Computational RNA Biology

Gut Microbiota 'Transplantation' and High-throughput sequencing

Speaker: Chaysavanh Manichanh - Institut de Recerca Vall d'Hebron

Room 473.10 - PRBB

Thursday, 12th February, 2009, 11:00

Computational RNA Biology

Alignment-free analysis of protein sequences using machine learning techniques

Speaker: Thomas Lingner - Department of Bioinformatics, G├Âttingen University

Room room 473.10-PRBB

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