Project structure

PANGAIA > Project structure

Scientific structure

The PANGAIA project is structured into five work packages.

WP1 and WP5 deal with management, education, and dissemination, while the research objectives are are split between WP2, WP3, and WP4.

WP1: Management and Coordination: building future collaborations to ensure self-sustainability

The goal of this WP is to guarantee that all planned secondments will be executed as expected and that all information will be distributed among all interested parties. This WP is devoted to monitoring the secondments and guaranteeing that all network events are organized following the schedule.

WP2: Representation of Pan-genomes: graph-based algorithms and data structures

The goal of this WP is to to rethink the main essential data structures and algorithms that are components of basic genome analysis pipelines under the paradigm shift from sequences to graphs.

This WP includes four tasks:

Task 2.1: Constructing a pan-genome

The goal of this task is to develop a suitable representations of a pangenome that reflects the genetic variation of a population that will act as a reference system for pangenome based applications.

Task 2.2: Dynamic update of a pan-genome

This task will face the problem of developing efficient dynamic update procedures for the pangenome representations developed in Task 2.1.

Task 2.3: Alignment to graph pan-genomes

The goal of this task is to design algorithms for the aligning sequences to the various pan-genome representations developed in Task 2.1.

Task 2.4: Software development of tools for pan-genome construction and indexing

This task is focused on the implementation and validation of software prototypes related to the functionalities designed in the previous tasks.

WP3: Comparative and Evolutionary Pan-Genomics

The goal of this WP is to developed new algorithmic tools to answer questions related to the comparison of genomes to detect significant genomic variants.

This WP includes three tasks:

Task 3.1: Measures of similarities in pan-genomes

The goal of this task is to develop measures of similarities and dissimilarities between two graph structures that can be used in classical clustering algorithms dealing with data representing graphs.

Task 3.2: Statistical differential analysis in pan-genomes

The goal of this task is to study the differential analysis of pangenome graphs to: (1) discover statistically significant patterns, and (2) perform a comparative analysis in situations of sequencing data with high error rate or low coverage.

Task 3.3: Evolution in pan-genomes

The goal of this task is to develop methods for inferring a
common evolution from the comparative analysis of graph pangenomes.

WP4: Translational pan-genomics data integration and clinical applications

The goal of this WP is to transform the data strctures and algorithmic methods developed in WP2 and WP3 into graph-based pangenomics tools for biomedical and clinical application.

This WP includes two tasks:

Task 4.1: Machine learning approaches to predict disease-related features

The goal of this task is to use machine (deep) learning techniques for predicting disease-related features in individual genomes, exploiting the results developed in WP3.

Task 4.2: Association discover in microbiome pan-genomics

The goal of this task is to develop methods to detect features from bacterial pangenomes that associate with the resistance of antibiotics.

WP5: Communication and Dissemination

The goals of this WP are to disseminate the results obtained by the project to the scientific community and to communicate those results to the general public.

WP6: Ethics requirements

The goal of this WP is to evaluate all ethical aspects of the project, most notably data privacy and informed consent of all individuals involved. Since the project will only use anonymized data, the main task is to guaranteed that data that no personally-identifiable data is used.

Management structure

The coordinator is Paola Bonizzoni (Univ. Milano – Bicocca).

Supervisory Board

The supervisory board monitors the progress of the project and approves the setting-up and execution of network-wide events. Its members are:

  • Paola Bonizzoni (Univ. Milano – Bicocca, chair)
  • Marco Previtali (Univ. Milano – Bicocca, Administrative Manager)
  • Alexander Schönhuth (Univ. Bielefeld)
  • Tomas Szemes (Geneton)
  • Tomas Vinar (Comenius Univ.)
  • Anthony J Cox (Illumina UK)
  • Leen Stougie (Centrum Wiskunde & Informatica)
  • Rayan Chikhi (Institut Pasteur)
  • Iman Hajirasouliha (Weill-Cornell Medical College, non-voting member)
  • Cedric Chauve (Simon Fraser Univ., non-voting member)
  • Paul Medvedev (Penn State Univ., non-voting member)
  • Kunihiko Sadakane (The Univ. of Tokyo, non-voting member)

Executive Committee

The Executive Committee carries out the actions decided by the Supervisory Board and it verifies the quality of deliverables, monitors dissemination activities and exploitation of results. Its members are:

  • Brona Brejova (Comenius Univ., chair, leader of WP3)
  • Paola Bonizzoni (Univ. Milano – Bicocca, leader of WP1)
  • Rayan Chikhi (Institut Pasteur, leader of WP2)
  • Gianluca Della Vedova (Univ. Milano – Bicocca, leader of WP5)
  • Solon P. Pissis (Centrum Wiskunde & Informatica, leader of WP4)
  • Jens Stoye (Univ. Bielefeld, leader of WP6)

Advisory Board

The Advisory Board is an independent body that advises on the project’s strategy, including scientific matters, industrial relevance, gender issues, and career development. Its members are:

  • Daniel Gusfield (UC Davis)
  • Teresa Przytycka (NCBI, NLM, NIH)
  • Gabriel Valiente (Technical University of Catalonia)