Advances in High-Performance Bioinformatics

and Biomedicine

The computational approach to biology and biomedicine is dealing with an enormous availability of high throughput data and an extreme complexity in the analysis of life systems. Both these issues make the scaling-up promise of High Performance Computing (HPC) extremely appealing. Currently, the possibility of parallelising algorithms and analysis techniques exploiting the various HPC emerging frameworks is receiving a lot of interest. Examples include the porting of legacy applications to clusters, e.g. those for genome analysis and assembly, and the use of distributed technologies, cloud computing, on-chip supercomputing, GPGPUs, and massively parallel architectures for the treatment of high-throughput data-sets. HPC frameworks is becoming particular relevant in biomedicine to speed-up the analysis of tumor molecular profiling data allowing researchers to better characterize the principles of tumor evolution across cancer types.
The aim of this special session is to present the latest efforts in HP Computational Biology and to foster the integration of researchers interested in HPC and Computational Biology.

Important Dates:

Paper submission:   10th Sep 2018 5th Oct 2018 15th Oct 2018 30th Oct 2018
Acceptance notification:   17th Oct 2018 15th Nov 2018 23rd Nov 2018 27th Nov 201830th Nov 2018
Camera ready due:   12th Nov 2018 15th Dec 2018 19th Dec 2018
Conference: 13th - 15th Feb 2019


    Notification extended
    November 27, 2018
    November 30, 2018

    July 21, 2018:
    List of accepted special sessions

    July 21, 2018:
    Call for paper available


  • Algorithms for genomics and proteomics
  • DNA assembly and mapping
  • Sequence analysis
  • SNP analysis and classification
  • Expression analysis and clustering techniques
  • Phylogeny reconstruction algorithms
  • Biological databases for big data management
  • Virtual labs and experiments
  • Parallel architectures for Computational Biology
  • System infrastructure for high throughput analysis
  • Algorithms and models for cancer evolution
  • Approaches to cancer clones identification

Programme Co-chairs:

Marco Beccuti, University of Turin, Italy

Francesca Cordero, University of Turin, Italy

Ivan Merelli, Istituto di Tecnologie Biomediche, Consiglio Nazionale delle Ricerche, Italy

Daniele D'Agostino, CNR-IMATI, Italy

Programme Committee:

Marzio Pennisi, University of Catania

Ernesto Picardi, University of Bari

Paolo Ballarini, Ecole Centrale de Paris

Claudia Misale, IBM New York

Fabio Vandin, Univeirsity of Padua

Giuse' Lo Bosco, University of Palermo

Mitra Purandare, IBM Zurich

Sandra Gesing, University of Notre Dame

Alberto Policriti, University of Udine

Luciano Milanesi, CNR Milan

Horacio Pérez-Sánchez, Universidad Católica de Murcia

Maurizio Drocco, University of Turin

Fabio Tordini, University of Turin

Giulio Ferrero, University of Turin


Dr. Marco Beccuti
Dept. of Computer Science
Università degli Studi di Torino
E-mail: beccuti@di.unito.it

Dr. Francesca Cordero
Dept. of Computer Science
Università degli Studi di Torino
E-mail: fcordero@di.unito.it