AlgoDay 2017


26 July 2017


Sala Seminari, U14, DISCo, Univ. Milano-Bicocca


We are witnessing an explosion in the availability of data, ranging from social media interactions, to biological sequences, to sensor data, which share the huge availability and low cost. Since those data are, by far, impractical or impossible to keep in memory, we need a paradigm shift in algorithm design, towards succinct data structures and parallel and/or external memory algorithms.


We are organizing a 1-day brainstorming event devoted to Algorithms and Data Structures for Massive Data, focused on innovative algorithmic solutions and on discussing open problems. Graph-based formulations will be especially investigated. AlgoDay is open to graduate students and researchers that are interested in this topic and are willing to do research in this field.

The event is open to all researchers that are interested in algorithms for massive datasets and want to investigate research directions that can lead to collaboration.

Some topics of interest are:

  • indexing massive data
  •  representation and queries in massive graphs
Detailed program
  • h. 10.30. Marco Previtali (AlgoLab – DISCo). Bloom filter tree and succinct bidirectional de Brujin graphs: Two tools for indexing massive data and graphs
  • h. 11.00. Simone Ciccolella (AlgoLab – DISCo). Beyond Perfect Phylogeny: Multisample Phylogeny Reconstruction via ILP
  • h. 11.30. Paolo Boldi and Marco Genuzio (Univ. Milano). Graph compression and static functions representation
  • h. 12.30. Andrea Maurino (DISCo) TBA
  • h. 13.00. Mauricio Soto (DISCo) Embeddings of semantic graphs
  • h. 13.30. Lunch and discussion on open problems and research directions

Stefano Beretta – Gianluca Della Vedova – Raffaella Rizzi



Special session on Algorithmics for biology

Special session at Computability in Europe 2017.

Organized by Paola Bonizzoni (Milano, Italy) and Veli Mäkinen (Helsinki, Finland).


  • Tobias Marschall (Max-Planck-Institut für Informatik, Germany)
    A Guided Tour to Computational Haplotyping (slides)
  • Fabio Vandin (University of Padova, Italy)
    Algorithms for Cancer Mutation Networks
  • Gregory Kucherov (University Paris-Est Marne-la-Vallée, France)
    Modern algorithmic techniques for biosequence search
  • Gianluca Della Vedova (University of Milano-Bicocca, Italy)
    Character-based Phylogeny Construction and its Application to Tumor Evolution (slides)

Workshop on Graph Assembly Algorithms for omics data

November 18th, 2016

Univ. Milano-Bicocca. Building U24 – Room C02

Theme and scope

New and different sequencing technologies have appeared in the last few years with the promise of overcoming Illumina as the reference platform: PacBio, 10x Genomics, and MinION being the most relevant today. Those technological improvements have shown the limitations of managing linear strings instead of richer models that are usually graph-based. Transcriptomics was the first field where the need of imposing a structure over strings has become clear, leading to the notion of a splicing graph to represent all possible transcripts of a gene, as well as the exon-intron structure. Genome assemblers are increasingly aware that a diploid organism has two different, but very similar, copies of each genome: hence the correct outcome of an assembly cannot be a single string. Finally, metagenomics studies different species that can share portions of the genome: another example where the correct representation of an assembly cannot be linear. Moreover, the 1000 Genomes project has generated new interest in the analysis of a population genome.

From a bioinformatics point of view, this results in the need for refining the classical approach where a genome is represented as a single string. Instead, some approaches based on graph representations have become more popular. For instance, some recent developments have been obtained on defining a common format (GFA – Graph Fragment Assembly) to represent an assembly graph.

The aim of this informal workshop is to bring together researchers from different, but correlated, areas under the widest possible notion of graph assembly algorithms, such as genome assembly, alternative splicing prediction, metagenomics, graph manipulation and representation, that are involved in the thorough investigation of these problems with both theoretical and experimental approaches. The goal is to brainstorm which challenges are the most important and can drive the research agenda in the next few years, and to jumpstart a proposal for a European Training Network (specific call) under the Horizon 2020 program and/or a COST action (call).

Nonexclusive list of relevant topics

  • graph assembly
  • variation graphs
  • de Bruijn graphs
  • string graphs
  • alternative splicing
  • metagenomics
  • the population genome
  • pan-genome graph
  • graph fragment assembly

Tentative schedule

9-9.30: Welcome and registration

9.30-11.35: Session 1 (5 talks, 25 minutes each)

  1. Alexander Schoenhuth (Centrum Wiskunde & Informatica). De novo assembly of viral quasispecies using overlap graphs (slides)

  2. Leena Salmela (University of Helsinki). Path searching problems in de Bruijn graphs (slides)

  3. Tomas Vinar (Comenius University). Probabilistic Models for Genome Assembly

  4. Jouni Siren (Wellcome Trust Sanger Institute). Indexing Graphs for Path Queries (slides)

  5. Guillaume Holley (Universität Bielefeld). Bloom Filter Trie: an efficient data structure for colored de Bruijn graphs (slides1 slides2)

11.35-12.00: Coffee break

12.00-13.40: Session 2 (4 talks, 25 minutes each)

  1. Pierre Peterlongo (Université de Rennes 1). Graph assembly algorithms at the Genscale team (slides)

  2. Jean-François Flot (Université libre de Bruxelles). Read compaction from a De Bruijn graph: a new paradigm for polymorphic genome assembly

  3. Rayan Chikhi (CNRS). Efficient construction of compacted de Bruijn graphs (slides)

  4. Rumen Andonov (Université de Rennes 1). Global Optimization Methods for Genome Scaffolding and Completing Genome Assemblies (slides)

13.40-14.30: Lunch

14.30-15.45: Session 3 (3 talks, 25 minutes each)

  1. Tobias Marschall (Universität des Saarlandes). Computational pan-genomics: status, promises and challenges (slides)

  2. Eric Rivals (CNRS). Superstring Graph: an alternative to assembly with multiple de Bruijn graphs

  3. Gianluca Della Vedova (Università di Milano-Bicocca). BWT and Graph Algorithms

15.45-17.30: Discussion

Venue and accommodation

The workshop will take place in Milano, at the Department of Computer Science (DISco), at the U24 building (Edificio U24).

Milan is easily reachable by all major European and main international airports. How to reach us

The suggested hotels are Starhotel Tourist and Hotel Arcimboldi that are both within a 5-minute walk from the workshop site.

List of speakers

Scientific Committee:

Paola Bonizzoni
Gianluca Della Vedova
Raffaella Rizzi

List of partecipants

  • Rumen Andonov
  • Stefano Beretta
  • Paola Bonizzoni
  • Broňa Brejová
  • Rayan Chikhi
  • Gianluca Della Vedova
  • Guillaume Holley
  • Jean-François Flot
  • Murray Patterson
  • Pierre Peterlongo
  • Nadia Pisanti
  • Alberto Policriti
  • Marco Previtali
  • Eric Rivals
  • Raffaella Rizzi
  • Romeo Rizzi
  • Giovanna Rosone
  • Leena Salmela
  • Alexander Schönhuth
  • Marinella Sciortino
  • Jouni Sirén
  • Jens Stoye
  • Tomáš Vinař

Tesi: Algoritmi di indicizzazione del grafo del pangenoma


La tesi si occupa di modellare, disegnare e implementare nuovi metodi di pattern matching dove il testo non è più una struttura lineare, ma è rappresentabile da un grafo orientato aciclico dove i vertici corrispondono a porzioni di genoma condivisi da uno o più individui e gli archi identificano le varianti genomiche presenti in ogni persone.

L’ambito fornisce la possibilità di avere più tesi di laurea magistrale, anche coordinate fra loro. Ad esempio:

  1. definire e studiare il problema computazionale quando il pattern a sua volta è un grafo.
  2. implementare un algoritmo di pattern matching con testo che è un grafo
  3. disegnare e implementare un algoritmo di allineamento di un read con un grafo
  4. modellare e disegnare un algoritmo per il caso di genomi con variazioni strutturali


Laboratorio di Algoritmica Sperimentale — Algolab —


Interesse ed entusiasmo per inventare nuovi algoritmi per indicizzare grafi basati su BWT (Burrows-Wheeler transform)

Risultati attesi

Nuovi modelli o algoritmi per l’indicizzazione e interrogazione di dati modellabili come grafi.

Per informazioni contattare

Paola Bonizzoni <> oppure Gianluca Della Vedova <>

Tempo di realizzazione

6 mesi