Tools




Seminars, events & talks

Thursday, 25th March, 2021, 12:00

New gene explosion in three different organisms regardless of the mechanism of origin

PRBB Computational Genomics Seminar. Chair: Mar Albà (Head of Evolutionary Genomics Group). New genes are constantly created in all organisms by two different mechanisms: gene duplication and de novo gene birth. The first mechanism generates an exact copy of a gene that will diverge from the original. On the other hand, de novo genes are originated from previously non-coding regions producing a completely original gene. Both mechanisms contribute to the generation of new genes, however, their relative contribution to short-time adaptation and long-term evolution is not well understood. In our group, we used a standard methodology to measure the rate of formation and persistence of both, de novo and duplicated genes in three different groups formed by yeasts, insects and vertebrates. We observed that independently of how new genes are formed the number of genes is higher at the species' level and then rapidly declines until a steady-state level. We also studied the purifying selection of groups of genes with polymorphism data and we observed weak purifying selection, that increases over time. Zoom webinar: https://us02web.zoom.us/j/81073249721 / Password: 788137

Speaker: Jose Carlos Montañés, Evolutionary Genomics Group - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Online

Thursday, 18th February, 2021, 12:00

Multivariate analysis of single-cell and spatial transcriptomic data

PRBB Computational Genomics Seminar. Chair: Robert Castelo (Head of Functional Genomics Group). Recent technological advances in molecular biology allow the sequencing of RNA from individual cells (single-cell RNA-seq) and the joint analysis of gene expression and spatial cellular organization (spatial transcriptomics). Typically, the genes whose expressions are differential between cell states or across the different areas of a tissue slice are identified with univariate (gene-wise) models. However, it may be beneficial to explicitly account for gene dependencies in multivariate statistical models. In this talk, I will show two examples of such models: (i) a graphical model for single-cell RNA-seq and (ii) a co-clustering model for spatial data. I will show how to use the first model to explore the dynamics of transcription factors in development and the second model to jointly identify spatially dependent genes and cell states/types. Finally, I will discuss the advantages of community-based open software development in Bioconductor. Zoom webinar: https://us02web.zoom.us/j/81073249721 / Password: 788137

Speaker: Davide Risso, Dept. of Statistical Sciences, Università di Padova, Italy

Room Online

Thursday, 14th January, 2021, 11:00

Neural network potentials for protein folding

Zoom webinar: https://zoom.us/j/93117636692?pwd=WGdBTktTeVRtL216bjBGK09vZ2RpZz09

Meeting ID: 931 1763 6692 / Password: 160118

Speaker: Maciej Majewski, Computational Science Group - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Online

Thursday, 5th November, 2020, 12:00

Systems medicine temporal analysis of patient disease trajectories

Incorporating the temporal dimension into disease comorbidity studies has shown to be crucial for achieving a better understanding of the disease progression. Furthermore, due to the multifactorial nature of human disease, exploring disease associations from different perspectives can provide a global view of the underlying mechanisms and thus, shed more light on their aetiology. In this work, a temporal systems-medicine approach is proposed for identifying time-dependent multimorbidity patterns from patient disease trajectories, by integrating data from electronic health records with genetic and phenotypic information. Specifically, the disease trajectories are clustered using an unsupervised algorithm based on dynamic time warping and three disease similarity metrics: clinical, genetic and phenotypic. The proposed integrative methodology can be applied to any longitudinal cohort and disease of interest. Prostate cancer is, herein, selected as a use case of medical interest to demonstrate, for the first time, the identification of temporal disease associations in different disease spaces. Zoom webinar: https://us02web.zoom.us/j/81073249721

Speaker: Alexia Giannoula, Integrative Biomedical Informatics Group - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)

Room Online

Friday, 24th April, 2020, 10.30

Soft-matter materials modeling in the data-driven era

Advanced statistical methods are rapidly impregnating many scientific fields, offering new perspectives on long-standing problems. In materials science, data-driven methods are already bearing fruit in various disciplines, such as hard condensed matter or inorganic chemistry, while comparatively little has happened in soft matter. I will describe how we use data-driven methods to leverage molecular simulations in soft matter. We aim at establishing structure-property relationships for complex thermodynamic processes across the chemical space of small molecules. Akin to screening experiments, we devise a high-throughput coarse-grained simulation framework. Coarse-graining is an appealing screening strategy for two main reasons: it significantly reduces the size of chemical space and it can suggest a low-dimensional representation of the structure-property relationship.

I will illustrate these aspects through the passive translocation of small molecules across a phospholipid bilayer, identifying interpretable structure-property relations, as well as recent results on the screening of small molecules to drive phase transitions in lipid mixtures. Further applications of recent machine learning architectures to molecular simulations will be described: representation learning of a free-energy landscape using Gaussian-mixture variational autoencoders, and the systematic backmapping of coarse-grained configurations to an atomistic level using conditional generative adversarial networks.

Speaker: Tristan Bereau, Van't Hoff Institute for Molecular Sciences and Informatics Institute, University of Amsterdam, Netherlands

Room Charles Darwin, PRBB Innner square

Thursday, 16th January, 2020, 12:00

Unravelling the mystery of orphan genes to understand the origins of genetic novelty

What explains the presence of a gene only in the genome of one species and not in any other? Species-specific protein-coding genes, also known as orphans, can arise "from scratch" from previously non-genic loci, through a process known as de novo gene emergence. How exactly the evolutionary transition from non-gene to functional gene unfolds is unclear. Can such de novo emerging genes increase an organism's fitness, and if so how? Orphan genes can also result from extensive sequence divergence of ancestral genes, which can eventually erase all similarity of a gene to its homologues in other species, a process even less well understood than de novo emergence.  I will present novel findings which advance our understanding of both these evolutionary mechanisms and bring us a small step closer to a complete picture of the origins of genetic novelty.

Speaker: Nikos Vakirlis, Benaki Phytopathological Institute, Athens, Greece

Room Aula room 473.10 (4th floor)

Thursday, 9th January, 2020, 12:00

Multi-Omics Factor Analysis: a principled framework for the integration of large-scale multi-omics data

Methods for analysing large-scale multi-omics studies are statistically challenging and currently lacking. I will present MOFA, a statistical framework for the comprehensive and scalable integration of multi-omics data. MOFA builds upon a Bayesian Factor Analysis framework combined with fast GPU-accelerated stochastic variational inference. The model allows for interpreting variation in both bulk and single-cell datasets by pooling information across cells and features to reconstruct a low-dimensional representation of the data. Uniquely, the model supports flexible sparsity constraints that allow joint modelling across multiple groups (conditions or experiments) and views (modalities or assays). To demonstrate the use of MOFA, I will present analysis from data sets of different scales and designs, including personalised medicine applications from patient cohorts and signal extraction from complex single-cell data.

Speaker: Ricard Argelaguet, European Bioinformatics Institute (EBI), Stegle/Marioni Group

Room Aula room 473.10 (4th floor)

Thursday, 28th November, 2019

Advances in Computational Biology Conference 2019

The first Advances in Computational Biology conference will bring together researchers working on systems biology, omics technologies, artificial intelligence and high-performance computing with applications to biology from both the public and private sectors. One of the main purposes of the conference is to visualize and promote the research done by women scientists and for this reason, all presenters will be women, although the conference is open to everyone. We want to create a space to foster collaborations between scientists, providing an excellent opportunity to share ideas and build research networks.  Mar Albà, head of the Evolutionary genomics group is member of the organizing committee and Laura I. Furlong, head of the Integrative Bioinformatics group is member of the scientific committee of the event.

Room La Pedrera Building, Barcelona, Spain

Thursday, 24th October, 2019, 12.00

Detecting Signs of Depression in Tweets in Spanish: Behavioral and Linguistic Analysis

Abstract: Mental disorders have become a major concern in public health, and they are one of the main causes of the overall disease burden worldwide. On the other hand, Social Media platforms allow us to observe thoughts and feelings of people's daily lives, including those of patients suffering from mental disorders. In this presentation we will discuss the usefulness of identifying the linguistic features of tweets in Spanish and the behavioral patterns of Twitter users who generate them, which could suggest signs of depression. Twitter users who are potentially suffering from depression modify the general characteristics of their language and the way they interact on social media. On the basis of these changes, these users can be monitored and supported, thus introducing new opportunities for studying depression and providing additional health care services to people with this disorder.

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

Room Aula room 473.10 (4th floor)

Monday, 14th October, 2019, 10:00

Interaction of Membrane Cholesterol with G Protein-Coupled Receptors: Novel Insights in Health and Disease

 G protein-coupled receptors (GPCRs) are the largest class of molecules involved in signal transduction across membranes, and represent major drug targets in all clinical areas.  The overall focus of our work is on the role of membrane cholesterol in GPCR organization (oligomerization), dynamics and function with implications in health and disease.  The GPCR of choice is the serotonin1A receptor, an important neurotransmitter receptor implicated in the generation and modulation of cognitive, behavioral and developmental functions, and an important drug target.  We demonstrated that membrane cholesterol is necessary for ligand binding, and G-protein coupling and signaling of serotonin1A receptors.   Interestingly, high-resolution crystal structures of GPCRs exhibit bound cholesterol.  In this context, we reported the presence of cholesterol recognition/interaction amino acid consensus (CRAC) motifs in the serotonin1A receptor.  Recent results employing mutations in the CRAC motifs show the importance of Lys101 in transmembrane helix II in conferring cholesterol-sensitivity to signaling by the receptor.  In addition, using a combination of experimental and MD simulation approaches, we demonstrated that the receptor is more stable and compact in the presence of membrane cholesterol.  Further, our results provide important insights in cholesterol-dependent oligomerization of the receptor using a variety of approaches such as photobleaching homo-FRET, photobleaching image correlation spectroscopy, and coarse grain MD simulations.  We ension that progress in deciphering molecular details of the nature of GPCR-cholesterol interaction in the membrane would lead to better insight into our overall understanding of GPCR function in health and disease.

Speaker: Prof. Amitabha Chattopadhyay, Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, India

Room Marie Curie, PRBB Inner square



Site Information