COuNt data TimE SerieS Analysis: significance tests and sequencing data application

Información del proyecto

CONTESSA

Identificador del acuerdo de subvención: 660388

DOI

10.3030/660388

Proyecto cerrado

Fecha de la firma de la CE 23 Marzo 2015

Fecha de inicio 1 Agosto 2015

Fecha de finalización 31 Julio 2017

Financiado con arreglo a

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coste total

€ 195 454,80

Aportación de la UE

€ 195 454,80

Coordinado por

THE UNIVERSITY OF SHEFFIELD
United Kingdom

Objetivo

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 a
real 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.

Ámbito científico (EuroSciVoc)

• ciencias naturales › ciencias biológicas › neurobiología
• ciencias naturales › informática y ciencias de la información › ciencia de datos
• ciencias naturales › ciencias biológicas › bioquímica › biomoléculas › proteínas
• ciencias naturales › ciencias biológicas › genética › ARN
• ciencias naturales › informática y ciencias de la información › inteligencia artificial › aprendizaje automático

Programa(s)

• H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions PROGRAMA PRINCIPAL
  
• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
  

Tema(s)

• MSCA-IF-2014-EF - Marie Skłodowska-Curie Individual Fellowships (IF-EF)
  

Régimen de financiación

MSCA-IF-EF-ST - Standard EF

Convocatoria de propuestas

H2020-MSCA-IF-2014

Coordinador

THE UNIVERSITY OF SHEFFIELD

• Aportación neta de la UEn: € 195 454,80
• Dirección: FIRTH COURT WESTERN BANK ; S10 2TN Sheffield ; Reino Unido
• Región: Yorkshire and the Humber › South Yorkshire › Sheffield
• Tipo de actividad: Higher or Secondary Education Establishments
• Coste total: € 195 454,80