Obiettivo The aim of this project is to develop methods for analysis of time-series based on count data. For example, detecting significant differences between two count data time series would distinguish between two different models: one in which the two time series are interchangeable, and one in which the second sample is a modification of the first, i.e. the two time series are non-interchangeable. This will broaden the target of my project to general analysis of count time-series data such as clustering, classification, perturbations inference and machine learning over sequential count data. The project will focus on count data sets from ribonucleic acid sequencing (RNA-seq) time course experiments. The method I plan to develop potentially has promising applications in a variety of multidisciplinary fields where event-counting is required, such as economics and biology. In economics, examples include the number of applicants for a job, or the number of labour strikes during a year. In biology, recent examples include high-throughput sequencing, such as RNA-seq and chromatin immunoprecipitation sequencing (ChIP-seq) analyses. These examples are especially relevant to this project because the method I will be developing enables various features of organisms to be compared through tag counts.I am enthusiastic about having the opportunity to be instrumental to a field where once developed this project will have areal impact in finding better treatments for patients with neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), Alzheimer’s and Parkinson’s Disease. Professor Neil Lawrence will act as the supervisor of the fellowship and will take over responsibility for my training and development. My fellowship experience will be enriched further through a six month secondment period at University of Manchester with Professor Magnus Rattray and through the opportunity to collaborate with SITraN’s Professor Winston Hide and Biogen Idec Industry. Campo scientifico natural sciencesbiological sciencesneurobiologynatural sciencescomputer and information sciencesdata sciencenatural sciencesbiological sciencesbiochemistrybiomoleculesproteinsnatural sciencesbiological sciencesgeneticsRNAnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programma(i) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Argomento(i) MSCA-IF-2014-EF - Marie Skłodowska-Curie Individual Fellowships (IF-EF) Invito a presentare proposte H2020-MSCA-IF-2014 Vedi altri progetti per questo bando Meccanismo di finanziamento MSCA-IF-EF-ST - Standard EF Coordinatore THE UNIVERSITY OF SHEFFIELD Contribution nette de l'UE € 195 454,80 Indirizzo FIRTH COURT WESTERN BANK S10 2TN Sheffield Regno Unito Mostra sulla mappa Regione Yorkshire and the Humber South Yorkshire Sheffield Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 195 454,80