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

Total Cost €


EC-Contrib. €






Project "CONTESSA" data sheet

The following table provides information about the project.


Organization address
postcode: S10 2TN

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website
 Total cost 195˙454 €
 EC max contribution 195˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2014
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2015
 Duration (year-month-day) from 2015-08-01   to  2017-07-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE UNIVERSITY OF SHEFFIELD UK (SHEFFIELD) coordinator 195˙454.00


 Project objective

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.


year authors and title journal last update
List of publications.
2016 A. Carissimo,L. Cutillo, I. Defeis
Validation of community robustness
published pages: , ISSN: , DOI:
Arrxiv 2019-07-24

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The information about "CONTESSA" are provided by the European Opendata Portal: CORDIS opendata.

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