Guillem Hernández Gu ...
Bachelors degree in bioinformatics
The Bachelor’s Degree in Bioinformatics includes a mandatory Bachelor's Degree Final Project of a scientific-professional nature to be carried out during the last two terms of students’ final year.
The Bachelor's Degree Final Project can either be a comprehensive project in the field of technologies specific to bioinformatics that brings together the competences acquired over the course of the degree or a project that explores an innovative idea (e.g. a computer program, scientific model for a biomedical question or a biological phenomenon).
Students will be overseen by a supervisor throughout the process of preparing their final project, which they will present to a board of examiners made up of lecturers on the degree course at the end of the final academic year.
Guillem Hernández Gu ...
Author: Guillem Hernández Guillamet
Project supervisor: Mireia Olivella i Beatriz Lòpez
Emotion prediction using physiological signals. Method pipeline that transform time-series to qualitative representations, reducing the complexity, to mine from a structural and feature-driven point of view using adopted techniques from bioinformatics and text mining tools. Method gathers diverse signals to perform multiple classification procedure simultaneously for a posterior consensus analysis, aiming the best prediction.
Institution: Control Engineering and Intelligent Systems (eXit) - Universitat de Girona (udG)
Ignasi Andreu Godall
Author: Ignasi Andreu Godall
Project supervisor: Gabriel Valiente
Finding an optimal solution to a multiple sequence alignment problem instance for more than two sequences is a hard optimization problem that is prohibitively computationally expensive, even for a few sequences of moderate length. Consequently, research on multiple sequence alignment has mainly focused on heuristic methods. However, recent advances in solvers for integer linear programming have made it possible to find exact, optimal solutions to multiple sequence alignment problem instances for several sequences of moderate length.
Institution: Universitat Politècnica de Catalunya (UPC)
Laura Aviñó Esteban
Author: Laura Aviñó Esteban
Project supervisor: Daniel Zerbino
Despite knowing where genes and the genomic regions regulate them, called enhancers; we still do not know which one interacts with which gene. In this work, I have generated models based on machine learning techniques using different subsets data, including Hi-C, epigenomics and eQTLs, to predict such conections. I have also created a method to impute interactions using dimensionality reduction techniques in the expression of RNA. All in all, I have shown that integrating different data sources in the same method increases its performance.
Institution: European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI)
Rubén Molina Fernand ...
Author: Rubén Molina Fernandez
Project supervisor: Baldomero Oliva
We modelled the potential interaction between AB-Amyloid and the Insulin Receptor, under the hypothesis that a feedback loop could be in the system, generating Alzheimer when the Insulin Receptor dimerization does not take place, like in Diabetes disease.
Institution: Unitat de Recerca en Informàtica Biomèdica (GRIB) Universitat Pompeu Fabra (UPF)
Author: Jordi Busoms
Project supervisor: Xavier Jalencas i Jordi Mestres
Unexpected binding of drugs to proteins beyond the intended protein target is one of the main causes of adverse drug reactions. Computational approaches to profiling compounds over thousands of proteins rely mostly on fast ligand-based methodologies. Structure-based methods are still computationally demanding. The main objective of this project is to investigate more efficient structure-based approaches to anticipating the likely binding of small molecules to thousand of proteins without the need to process them all individually. We have obtained a fully working algorithm that is able to get groups of similar binding sites from three-dimensional protein structures and generate representative signatures of the entire group of proteins.
Institution: Institut Hospital del Mar d'Investigacions Mèdiques (IMIM)
José Miguel Ramírez ...
Author: José Miguel Ramírez Cardeñosa
Project supervisor: Eva Novoa
RNA modifications have recently emerged as key regulators in many biological processes. However, current methods to genome-wide map RNA modifications using next-generation sequencing (NGS) are only available for 5 % of the known modifications, among other drawbacks. A new method is the direct RNA sequencing platform developed by Oxford Nanopore Technologies, which is able to sequence native RNA molecules. Here, we systematically compare state-of-the-art base-calling and mapping algorithms, as well as their ability to detect and distinguish RNA modifications using systematic base-calling ‘errors’. We find that Guppy 3.0.3 produces the highest accuracy and qualities, being also able to detect RNA modifications with the highest accuracy, and that GraphMap performs better than minimap2. However, distinguishing between different types of RNA modifications that modify the same ribonucleotide, such as 5-methylcytosine and 5-hydroxymethylcytosine, still remains a challenge.
Institution: Centre de Regulació Genòmica (CRG)
Ferriol Calvet Riera
Author: Ferriol Calvet Riera
Project supervisor: Dr. Jonathan M. Mudge, Dr. Adam Frankish
Upstream open reading frames are genomic features present in the 5’ UTRs of protein-coding transcripts that are known to be important for translation regulation. We have provided a dataset with 104497 unique possible uORFs in the GENCODEv34 transcriptome. Each of them has additional features and a score showing how likely it is to be real that was computed based on them. The tools and pipelines we have implemented are easily replicable and can allow fast updates to the current annotation or data version. Apart from all these, we provide a custom track to visualize uORFs in the UCSC genome browser.
Institution: Institución: EMBL-EBI - European Bioinformatics Institute
Paula Balcells Falgu ...
Author: Paula Balcells Falgueras
Project supervisor: Virginie Uhlmann, Dra. Mireia Olivella
Quantitative characterisation of objects in bioimages can provide useful information to help understand biological phenomena. In this project, we have developed a general-purpose Python package to quantify, compare and explore the morphology of 2D objects in bioimages from their contours. Based on parametric spline curve models, quantitative metrics are computed analytically and implemented algorithmically. We have also tested our methods on two microscopy datasets.
Institutions: EMBL-EBI - European Bioinformatics Institute
Marta Ibáñez Lligoña
Author: Marta Ibáñez Lligoña
Project supervisor: Dr. Amanda Sferruzzi-Perri, Dr Xiaohui Zhao, Dr Tina Napso
Placenta manages signals between the mother and the fetus which affects maternal physiology, nutrient exchange, and placental malformations that can lead to complications in pregnancy. To improve the understanding of placental endocrinology in normal and pregnancy complications, we have used mass spectrometry and bioinformatic techniques to study the placental peptidome and secretome. In which we have obtained a 319-protein list of potentially secreted proteins that are expressed in the placenta and function in structural anatomical development and the immune system, among others. 37,3% of these proteins have been reported to be dysregulated at a gene level in pregnancy pathologies.
Institución: University of Cambridge
Andrea Nieto-Aliseda ...
Author: Andrea Nieto-Aliseda Sutton
Project supervisor: Biola M. Javierre, Dra. Mireia Olivella
The objective of this project is to add towards the understanding of B-cell Acute Lymphoblastic Leukemia oncogenesis, identifying deregulated genes by studying epigenetic mutations observed at their regulatory elements, particularly long-range enhancers which can be studied through the 3D analysis of the genome’s architecture.
Institution: IJC - Institut de Recerca contra la Leucèmia Josep Carreras
Alexis Molina Martín ...
Author: Alexis Molina Martínez Delos Reyes
Project supervisor: Victor Guallar
Protein thermostability is an important topic in industrial biotechnology since it plays a key role in the enzymatic process set-up, and thus, on enhanced production. We propose a pipeline, based on state-of-the- art methods, for studying thermostability and identifying mutable regions on enzymes using molecular simulations and residue interaction networks. Taking as a central pillar the hypothesis that flexibility plays a major role in resistance to thermal changes, the pipeline was built upon analyses able to reveal the most relevant regions in terms of stability of two different proteins in different retrospective studies.
Institución: BSC - Barcelona Supercomputing Center
Irene Acero Pousa
Author: Irene Acero Pousa
Project supervisor: Estela Càmara
Huntington’s disease (HD) is a genetic neurodegenerative disease caused by a mutation in the HTT gene which involves a mixture of symptoms, including motor, cognitive and psychiatric deficits. However, there is a high degree of heterogeneity in the prominence and evolution of each type of symptom. The three main cortico-striatal circuits (motor, cognitive control and motivational) result affected by neurodegeneration, which could be one possible source of such interindividual differences among HD patients. The aim of this research is to characterize the structural connectivity of the three main cortico-striatal circuits in order to delineate specific neurodegeneration patterns that might underlay the different symptomatic profiles in HD.
Institution: IDIBELL - Institut d'Investigació Biomèdica de Bellvitge
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