SWIM (SWitchMiner)

Over the last two decades, biological sciences have undergone radical transformation through the development of new research technologies that have produced a real explosion in the amount of data available. Just think of the modern genomic sequencing techniques that have made the sequencing of the human genome, different animal and plant organisms, and many microorganisms simpler, less expensive and more reliable with enormous benefits for diagnosis and treatment of diseases. In the wake of the genome, many other objects that represent various biological entities analyzed in their entirety are defined and studied: from transcriptome (the complete set of RNA expressed by the cell) to the proteome (the complete set of proteins) to more exotic objects such as interactome and metabolome. This huge amount of data available is an immense resource for research, but only the amount is not enough. If in the past there was a difficulty in collecting genetic data, today the challenge is to give them meaning and it is therefore essential to use effective informatics solutions capable of managing, analyzing and integrating these biological "Big Data".
An excellent solution for integrating data to support research was designed by Dr. Paci, who developed SWIM (SWitchMiner), a freely downloadable open-source software with GNU GPL license available at The software comes with a wizard-like GUI that greatly simplifies the execution of the otherwise complicated procedure and allows the user to interact with the software by executing certain operations through a series of subsequent steps. The software, capable of detecting genes responsible for major changes in the phenotype of a cell, has so far been successfully applied in two very different fields: the vine-wine and the oncology.
On the one hand, viticulture is undoubtedly a field of great economic and strategic importance and of great cultural value for Italy. Speaking of numbers, grapevine moves a turnover of over 100 billion euros a year. The potential impacts justify the choice of applying SWIM to the genome of grapevine, a project that has led to the identification of key genes in the ripening process of grapes. Thanks to SWIM it is now possible to decipher plant responses to particular conditions or stages of development and to control the quality of wine in response to climate change. The results of this study were published in the prestigious scientific journal The Plant Cell (The Plant Cell 2014, 26, pp. 4617-4635) and by many national newspapers (La Stampa, Il Gazzettino, Gambero Rosso, Corriere del Veneto, Vinoso, Bere il Vino, Agrinews, VQ-Vite, Vino&Qualità, Trebicchieri). For this publication, Dr. Paci received the SysBio 2014 Award as the best publication of the year by the SYSBIO Center for Systems Biology (
On the other hand, oncology is undoubtedly a field of high healthcare, social and economic impact. Cancer is still the second cause of death in Italy (30% of all deaths) after cardiovascular disease, with a growing number of tumor sufferers. It is estimated that in Italy there are 365,000 new cancer diagnosis per year (excluding carcinomas), over 189,000 (52%) among men and over 176,000 (48%) among women. To these few reassuring numbers, the ever-increasing costs that the National Health Service must support for anti-cancer therapies must be added. In Italy, the costs are between 50 and 150 thousand euros per year of care, with an increase estimated at + 17% in 2018. The main goal of research in this area is certainly the innovation of therapy through discovery and the development of new drugs that can provide incremental benefit both to the patient and National Health Service in terms of health and costs. The potential impacts justify the choice of applying SWIM to about twenty different types of tumor, a project that has led to the identification of genes with a key role in neoplastic transformation. Thanks to SWIM it is now possible to identify new potential therapeutic targets for the treatment of different types of cancer. The findings of this study were published in the prestigious Scientific Reports of Nature (Scientific Reports 2017, 7, Article number: 44797). For this work, Dr. Paci also received the Best Poster Award 2016 from the IEEE Technical Committee on Computational Life Science Society (TCCLS) at the Lipari Computational Microbiology and Microbiome-Based Medicine School.