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Seminars, events & talks

Thursday, 6th June, 2019

De novo proteins in evolution and disease

Speaker: Mar Albà, Evolutionary Genomics - GRIB (IMIM/UPF)

Room Institut d'Estudis Catalans, Carrer del Carme, 47, Barcelona

Wednesday, 29th May, 2019, 09:30

III Retreat de l'IMIM

El dimecres 29 de maig tindrà lloc a l'Auditori del PRBB el III Retreat de l'IMIM. Amb aquesta iniciativa es vol donar visibilitat als projectes més rellevants que s'estan desenvolupant a cada Programa de Recerca, tot esperant que això sigui font de noves sinèrgies i d'intercanvi científic entre els diferents grups per a millorar la nostra competitivitat científica. És per aquest motiu que agrairíem us reservéssiu tota la jornada per assistir-hi, i així poder conèixer en què estan treballant els diferents grups de l'IMIM, fora del programa de recerca del que formeu part.el III Retreat de l'IMIM. Amb aquesta iniciativa es vol donar visibilitat als projectes més rellevants que s'estan desenvolupant a cada Programa de Recerca, tot esperant que això sigui font de noves sinèrgies i d'intercanvi científic entre els diferents grups per a millorar la nostra competitivitat científica. És per aquest motiu que agrairíem us reservéssiu tota la jornada per assistir-hi, i així poder conèixer en què estan treballant els diferents grups de l'IMIM, fora del programa de recerca del que formeu part.

Room Auditori del PRBB

Thursday, 9th May, 2019, 12.00

ResMarkerDB: a database of biomarkers of response to antibody therapy in breast and colorectal cancer

The clinical efficacy of therapeutic monoclonal antibodies for breast and colorectal cancer has greatly contributed to the improvement of patients' outcomes by individualizing their treatments. However, primary or acquired resistance may occur. Although several databases characterize biomarkers of drug response, there is a need of resources that offer this information to the user in a harmonized manner to support research and development of new alternative treatments. ResMarkerDB was developed as a comprehensive resource of biomarkers of drug response in breast and colorectal cancer. It integrates these data from existing repositories, and new data extracted and curated from the literature (referred as ResCur). It provides a user-friendly web interface (http://www.resmarkerdb.org) to facilitate the exploration of current knowledge of biomarkers of response in breast and colorectal cancer. The database contains more than 500 biomarker-drug-tumour associations. ResMarkerDB aims to enhance translational research efforts in identifying actionable biomarkers of drug response in cancer.

Speaker: Judith Pérez, Integrative Biomedical Informatics - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Aula 473.10 (PRBB, 4th floor)

Tuesday, 7th May, 2019, 12:00

Presentation of the Human Computational Biology Group

Speaker: ​Lara Nonell, PhD BiCoH (Human Computational Biology), MARGenomics, IMIM Scientific and Technical Services

Room Charles Darwin, PRBB Innner square

Thursday, 2nd May, 2019, 12:00

Uncovering de novo gene birth in baker's yeast with RNA-seq and ribosome profiling

De novo gene birth is a unique mechanism of new gene formation- unlike genes originating from duplication or fusion, de novo genes come from previously non-genic sequences-this potentially exposes completely novel peptides to selection. Several groups have previously investigated de novo gene birth in baker's yeast (Saccharomyces cerevisiae). Interestingly, many of these analyses have produced contrasting observations. To better understand the true origins of these de novo genes, we performed the first analysis of de novo gene birth in Saccharomycotina using transcriptomics data for eleven different species of yeast as well as ribosome profiling for S. cerevisiae (doi.org/10.1101/575837). We identified more than 200 putative de novo transcripts which often appear in regions overlapping older genes on the opposite strand.

Speaker: Will Blevins, Evolutionary Genomics - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Aula 473.10 (PRBB, 4th floor)

Friday, 29th March, 2019, 10.00 - 11.00

Continual Reinforcement Learning in 3D Non-stationary Environments

Dynamic and always-changing environments constitute an hard challenge for current reinforcement learning techniques. Artificial agents, nowadays, are often trained in very static and reproducible conditions in simulation, where the common assumption is that observations can be sampled i.i.d from the environment. However, tackling more complex problems and real-world settings this can be rarely considered the case, with environments often non-stationary and subject to unpredictable, frequent changes. In this talk we discuss about a new open benchmark for learning continually through reinforce in a complex 3D non-stationary object picking task based on VizDoom and subject to several environmental changes. We further propose a number of end-to-end, model-free continual reinforcement learning strategies showing competitive results even without any access to previously encountered environmental conditions or observations.

Speaker: Vincenzo Lomonaco, DISI Department, University of Bologna, Italy

Room Ramón y Cajal, PRBB Innner square

Wednesday, 27th March, 2019, 12:00

Enabling comorbidity analyses from real world clinical data

Speaker: Laura Furlong, Miquel Servet Researcher at the IMIM, UPF Associate Lecturer, Head of the Integrative Biomedical Informatics Group - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Xipre 173.06 (PRBB, 1st floor)

Thursday, 14th March, 2019, 12:00

The DisGeNET knowledge management platform for disease genomics

The rapid advances in disease genomics and genetics of the last two decades have made it possible to catalog a large volume of genetic alterations found in patients for a broad spectrum of diseases: cancer, Mendelian, rare, and complex diseases. These data are freely available, but scattered across different repositories and catalogs. Furthermore, accessing, navigating and analyzing this information is a challenge due to its heterogeneity, and lack of standardization. To overcome these challenges, we have developed DisGeNET (http://www.disgenet.org), one of the largest available repositories of genes and variants involved in human diseases. In the seminar, we will present the release 6.0 of DisGeNET, and discuss several case studies, in the areas of drug discovery and disease genomics.

Speaker: Janet Piñero, Integrative Biomedical Informatics - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Aula 473.10 (PRBB, 4th floor)

Friday, 23th November, 2018, 10.00

Deep Reinforcement Learning for Partially Observable Environments

Many real-world sequential decision-making problems are partially observable by nature and the environmental model is often unknown. Examples include visual occlusions, unobserved latent causes like in healthcare or when we rely on noisy sensors. Consequently, there is a great need for reinforcement learning methods that can tackle such problems given only a stream of observations.  In this talk, I will briefly present the two fundamental approaches how partial observability can be tackled when we want to learn a policy, namely memory or inference. Subsequently, I will present our recently proposed algorithm "Deep Variational Reinforcement  Learning" (DVRL) which combines learning a model with particle filtering to allow the agent to reason more effectively about the unobserved state of the environment.

Speaker: Maximilian Igl, Department of Computer Science, University of Oxford, UK

Room Marie Curie, PRBB Innner square

Thursday, 4th October, 2018, 12:00

Is ribosome profiling better than RNA-seq for estimating protein abundances? A case study in Saccharomyces cerevisiae in normal and oxidative stress conditions

Yeast cells respond dynamically to different environments; often this response involves adjusting the abundance of different proteins. In many published experiments, this cellular response is studied by proxy-measuring variations in transcript abundance across different conditions using high throughput RNA sequencing. However, variations in transcript abundance do not always reflect changes in protein abundance. Ribosome profiling, or Ribo-seq, specifically targets only the ribosome-protected fragments of RNA; as there is pervasive translation of ribosome-assocaiated RNAs, this would be expected to provide a more accurate view of changes at the protein level than RNA-seq. We performed a differential gene expression analysis of oxidative stress in baker's yeast using RNA-seq, Ribo-seq, and liquid chromatography mass spectrometry. A subset of genes involved in oxidation-reduction processes is detected by RNA-seq and Ribo-seq, but RNA-seq also identifies many genes which are not significant in the Ribo-seq analysis which suggests that significant changes in mRNA abundance do not always result in different protein abundance. Furthermore, the proteomics data more closely resemble the Ribo-seq results than RNA-seq. Our findings demonstrate that there could be limitations to using RNA-seq when making inferences about changes in protein abundance and the potential of Ribo-seq to fill this gap.

Speaker: Will Blevins, Evolutionary Genomics Group - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Aula 473.10 (PRBB, 4th floor)



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