ABOUT US

ABOUT US

Software services for Precision Medicine

Kazaam Lab provides useful software services to extract hidden information within heterogeneous biomedical big data.

The ultimate goal is to guide healthcare decisions towards the most effective treatment for a particular patient, thereby improving the quality of care. We contribute to make precision medicine a reality thanks to the effective use of Big Data and Artificial Intelligence technologies.

MISSION

Contribute to allow that Precision Medicine may be applied regularly and effectively in the globe

VISION

Become a recognized brand for decision support services in Precision Medicine

STRATEGY

Enable holistic views of cells and individuals by combining powerful models, efficient algorithms and innovative technologies

VIDEO

Phoenix eHealth Platform

PRODUCTS

Phoenix eHealth Platform

Data integration, modelling and analysis

PHOENIX eHealth Platform is a SaaS platform for Big Data Analytics that provides decision support services in the context of Precision Medicine.

PHOENIX aims to fill the current gap between the amount of biomedical data currently available and the value that can be extracted from them. Data span from molecular interactions, to genotype-phenotype, clinical and behavioral data.

PHOENIX users are: physicians, who gather information and make decisions about best treatment and preventive measures for the patient. Clinical laboratories, providing medical laboratory tests that enable physicians to successfully practice Precision Medicine. Pharmaceutical companies, providing insights into patient-specific mechanisms that cause or contribute to disease, which enables the “precise” targeting of these mechanisms.

Phoenix
Phoenix

RoadMap

RoadMap

April 2020

EIT Health RIS Innostars Awards (75K)

February 2020

Selected for BIOUPPER (17 out of 117)

November 2019

Finalists (ICT) at the National Prize for Innovation (12 out of 67)

October 2019

Selected at STARTCUP Sicilia

October 2019

Winners of STARTCUP Palermo (II Prize)

Pubblications

Our Pubblications

S.Morfea, F.Pace, S. E. Rombo. A Big-Data Framework for Genotype-Phenotype Data Integration, Modelling and Analysis. 16th Annual Meeting of the Bioinformatics Italian Society, June 26-28, 2019, Palermo, Italy

DOI.

C. Giallombardo, S. Morfea, S. E. Rombo. An Integrative Framework for the Construction of Big Functional Networks. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018): 2088-2093, Madrid, Spain, December 3-6, 2018.

DOI

S. Panni, R. C. Lovering, P. Porras, S. Orchard. Non-coding RNA regulatory networks, Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, 2019, 194417, ISSN 1874-9399

DOI

R. Giancarlo, S. E. Rombo, F. Utro. In vitro versus in vivo compositional landscapes of histone sequence preferences in eukaryotic genomes. Bioinformatics 34(20): 454-3460, 2018.

DOI

F. Fassetti, S. E. Rombo, C. Serrao. Discriminative Pattern Discovery on Biological Networks. Springer Briefs in Computer Science, Springer 2017, ISBN 978-3-319-63476-0, pp. 3-45.

DOI

Sacco, F., Mattioni, A., Boldt, K.. Panni, S. et al. A subset of RAB proteins modulates PP2A phosphatase activity. Sci Rep 6, 32857 (2016).

DOI