BITS2019-Analysis of Big Omics Data
Algorithms and Tools for the Analysis of Big Omics Data


With the rapid explosion of biological and medical data, resulting from the always more advanced sequencing technologies, high-throughput techniques, clinical and imaging data, electronic health records, etc., important challenges arise for the extraction of useful knowledge and the production of novel insights in Biology and Medicine. Large-scale and high-resolution omics data such as genomics, transcriptomics, proteomics and even metagenomics data are nowadays available. We are actually able to collect data at the resolution of individual cells by using optimized next generation sequencing (NGS) technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment. Indeed, these special types of “big data” are complex in contents, heterogeneous in formats and order of Terabytes in amount.

The ultimate goal of this workshop is to provide to participants the opportunity of introducing and discussing new methods, theoretical approaches, algorithms, tools, and platforms that are relevant to the bioinformatics community for the extraction, integration and analysis of big omics data.

This will hopefully imply also the definition of new problems raised in managing complex data, and the dissemination of novel ideas on the application of “big data” methodologies in the biological and medical domain.

The list of topics for the workshop, that has not to be intended as exhaustive, is reported below.



  • Integration of biomedical databases and sources
  • Algorithms and tools for Next-Generation Sequencing data analysis andinterpretation
  • Big data analytics for omics data
  • Models for complex clinic and genetic data
  • Algorithms and tools for the analysis of Metagenomes
  • Epigenomics
  • Deep learning approaches for the omics data
  • Single cell data analysis
  • Omics data functional prediction
  • Computational Cancer Genomics



  • Fabio Fassetti, DIMES – Università della Calabria
  • Giosué Lo Bosco, DMI – Università degli Studi di Palermo
  • Cinzia Pizzi, DEI – Università degli Studi di Padova
  • Simona E. Rombo, DMI – Università degli Studi di Palermo


The workshop is free for BITS participants, and it will include both Invited Talks and Oral Presentations. For the attendees who want to participate by an Oral Presentation, it is necessary to submit an abstract (see details below).




Fabio Vandin, Associate Professor, University of Padua


Sequencing technologies now allow measuring different features of a cancer genome at an outstanding level of detail for an unprecedented number of tumors. The resulting datasets provide an exceptional opportunity to gain insight into cancer development and progression by identifying patterns of mutations across different tumors. However, the identification of reliable patterns poses severe computational and statistical challenges, due to the high dimensionality of the problem. In this talk I will discuss some recent work on the development of algorithms to identify reliable and significant patterns from measurements of a large collection of tumors, including patterns associated with clinical or functional measures, and highlight some of the current and future challenges.


Luca Pinello, Assistant Professor, Massachusetts General Hospital Research Institute and Harvard Medical School, USA


Recent technological advances are accelerating our understanding of complex biological systems. In particular, single cell technologies allow profiling transcriptomic or epigenomic states of thousands of cells, while clustered regularly interspaced short palindromic repeats (CRISPR) genome editing has revolutionized the ability to modify a genome of interest in a targeted and programmable way. However, the processing, integration, and interpretation of sequencing data coming from these technologies is challenging.

In this talk, I will first present STREAM, a computational method for single-cell analysis of transcriptomic and epigenomic data. This method starting from sequencing data can be used to disentangle complex cellular types and states in development, differentiation or in perturbation studies. It can accurately detect cellular hierarchies and recover complex developmental trajectories. In addition, it provides informative and intuitive visualization techniques to highlight important genes that can be used as markers to define sub-populations and rare cell types.

Then, I will present how to design and analyze recent CRISPR tiling screens using two methods we have recently developed called CRISPR-SURF and CRISPResso. Tiling perturbations allow a powerful and high-throughput functional interrogation of non-coding elements throughout the genome. Functional mapping can be achieved by densely tiling single guide RNAs (sgRNAs) across a non-coding region of interest, where each sgRNA enables linking a unique, genomic location to an observable phenotype. CRISPR-SURF and CRISPResso can be used to analyze tiling screens and provide the capability to discover functional non-coding regions and to dissect their critical elements thereby enabling a powerful characterization of genetic variants involved in traits or diseases.





9:30 - Welcome

Session I

9:35 - Invited Talk: Luca Pinello, Massachusetts General Hospital Research Institute and Harvard

Medical School, USA


10:20 – Amato D, Di Benedetto E

A web application for comparative analysis of nucleosome positioning

10:35 – Flati T, Gioiosa S, Chillemi G, Castrignanò T.

BPA: a high-scalable Bioinformatics Pipeline Assistant for seamless bioinformatics pipeline automation

10:50 – Cattaneo G, Ferraro Petrillo U, Giancarlo R, Palini F.

A Spark Algorithmic Paradigm For Spaced Words Alignment-Free Classification, with Focus on


11:05 – Garofalo F, Greco D, Rosone G, Sciortino M

Parallel Computation of Matching Statistics and Average Common Substring


11:20 - Coffee Break


Session II

11:45 - Invited Talk: Fabio Vandin, University of Padua, Italy


12:30 – Masseroli M, Pinoli P, Canakoglu A, Bernasconi A, Gulino A, Nanni L, Orlova O,

Pallotta S, Ceri S.

Genomic big data management, modeling and computing

12:45 – Rossi N, Piazza C, Gigante N, Vitacolonna N

CIMICE - Markov Chain Inference Method to Identify Cancer Evolution

13:00 - Andreani T, Carancini G, Carletti M

Stochastic modelling of PTEN gene expression dynamics with delay in Glioma cells

13:15 - Parasiliti Palumbo GA, Biondi P, Russo G, Sgroi G, Pennisi M, Pappalardo F

A Mapreduce based algorithm for the analysis and discovery of novel therapeutic targets


Full articles presented as Oral Presentations to the workshop will be selected for the pubblication in BMC Bioinformatics journal. Full articles have been through the journal's standard peer review process for supplements.



Important Dates

Abstract Submission Deadline: 26 May 2019

Notification of Acceptance: 02 Jun 2019

Workshop: 26 June 2019


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