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Article ; Online: A novel algorithm for finding top-k weighted overlapping densest connected subgraphs in dual networks.

Dondi, Riccardo / Hosseinzadeh, Mohammad Mehdi / Guzzi, Pietro H

Applied network science

2021 Volume 6, Issue 1, Page(s) 40

Abstract: The use of networks for modelling and analysing relations among data is currently growing. Recently, the use of a single networks for capturing all the aspects of some complex scenarios has shown some limitations. Consequently, it has been proposed to ... ...

Abstract	The use of networks for modelling and analysing relations among data is currently growing. Recently, the use of a single networks for capturing all the aspects of some complex scenarios has shown some limitations. Consequently, it has been proposed to use Dual Networks (DN), a pair of related networks, to analyse complex systems. The two graphs in a DN have the same set of vertices and different edge sets. Common subgraphs among these networks may convey some insights about the modelled scenarios. For instance, the detection of the Top-k Densest Connected subgraphs, i.e. a set k subgraphs having the largest density in the conceptual network which are also connected in the physical network, may reveal set of highly related nodes. After proposing a formalisation of the approach, we propose a heuristic to find a solution, since the problem is computationally hard. A set of experiments on synthetic and real networks is also presented to support our approach.
Language	English
Publishing date	2021-06-05
Publishing country	Switzerland
Document type	Journal Article
ISSN	2364-8228
ISSN (online)	2364-8228
DOI	10.1007/s41109-021-00381-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Regional Resource Assessment During the COVID-19 Pandemic in Italy: Modeling Study.

Guzzi, Pietro H / Tradigo, Giuseppe / Veltri, Pierangelo

JMIR medical informatics

2021 Volume 9, Issue 3, Page(s) e18933

Abstract: Background: COVID-19 has been declared a worldwide emergency and a pandemic by the World Health Organization. It started in China in December 2019, and it rapidly spread throughout Italy, which was the most affected country after China. The pandemic ... ...

Abstract	Background: COVID-19 has been declared a worldwide emergency and a pandemic by the World Health Organization. It started in China in December 2019, and it rapidly spread throughout Italy, which was the most affected country after China. The pandemic affected all countries with similarly negative effects on the population and health care structures. Objective: The evolution of the COVID-19 infections and the way such a phenomenon can be characterized in terms of resources and planning has to be considered. One of the most critical resources has been intensive care units (ICUs) with respect to the infection trend and critical hospitalization. Methods: We propose a model to estimate the needed number of places in ICUs during the most acute phase of the infection. We also define a scalable geographic model to plan emergency and future management of patients with COVID-19 by planning their reallocation in health structures of other regions. Results: We applied and assessed the prediction method both at the national and regional levels. ICU bed prediction was tested with respect to real data provided by the Italian government. We showed that our model is able to predict, with a reliable error in terms of resource complexity, estimation parameters used in health care structures. In addition, the proposed method is scalable at different geographic levels. This is relevant for pandemics such as COVID-19, which has shown different case incidences even among northern and southern Italian regions. Conclusions: Our contribution can be useful for decision makers to plan resources to guarantee patient management, but it can also be considered as a reference model for potential upcoming waves of COVID-19 and similar emergency situations.
Language	English
Publishing date	2021-03-09
Publishing country	Canada
Document type	Journal Article
ZDB-ID	2798261-0
ISSN	2291-9694
ISSN	2291-9694
DOI	10.2196/18933
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Article ; Online: Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data.

Mercatelli, Daniele / Cabrelle, Chiara / Veltri, Pierangelo / Giorgi, Federico M / Guzzi, Pietro H

Briefings in bioinformatics

2022 Volume 23, Issue 5

Abstract: Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene ... ...

Abstract	Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as 'signaling hubs'. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called 'SURFACER'. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.
MeSH term(s)	Antineoplastic Agents/therapeutic use ; Biomarkers, Tumor/genetics ; Biomarkers, Tumor/metabolism ; Breast Neoplasms/metabolism ; Female ; Humans ; Membrane Proteins/genetics ; Transcriptome
Chemical Substances	Antineoplastic Agents ; Biomarkers, Tumor ; Membrane Proteins
Language	English
Publishing date	2022-09-08
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbac400
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Article ; Online: Regional Resource Assessment During the COVID-19 Pandemic in Italy

Guzzi, Pietro H / Tradigo, Giuseppe / Veltri, Pierangelo

JMIR Medical Informatics, Vol 9, Iss 3, p e

Modeling Study

2021 Volume 18933

Abstract: BackgroundCOVID-19 has been declared a worldwide emergency and a pandemic by the World Health Organization. It started in China in December 2019, and it rapidly spread throughout Italy, which was the most affected country after China. The pandemic ... ...

Abstract	BackgroundCOVID-19 has been declared a worldwide emergency and a pandemic by the World Health Organization. It started in China in December 2019, and it rapidly spread throughout Italy, which was the most affected country after China. The pandemic affected all countries with similarly negative effects on the population and health care structures. ObjectiveThe evolution of the COVID-19 infections and the way such a phenomenon can be characterized in terms of resources and planning has to be considered. One of the most critical resources has been intensive care units (ICUs) with respect to the infection trend and critical hospitalization. MethodsWe propose a model to estimate the needed number of places in ICUs during the most acute phase of the infection. We also define a scalable geographic model to plan emergency and future management of patients with COVID-19 by planning their reallocation in health structures of other regions. ResultsWe applied and assessed the prediction method both at the national and regional levels. ICU bed prediction was tested with respect to real data provided by the Italian government. We showed that our model is able to predict, with a reliable error in terms of resource complexity, estimation parameters used in health care structures. In addition, the proposed method is scalable at different geographic levels. This is relevant for pandemics such as COVID-19, which has shown different case incidences even among northern and southern Italian regions. ConclusionsOur contribution can be useful for decision makers to plan resources to guarantee patient management, but it can also be considered as a reference model for potential upcoming waves of COVID-19 and similar emergency situations.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	027
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	JMIR Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Predicting the response of the dental pulp to SARS-CoV2 infection: a transcriptome-wide effect cross-analysis.

Galicia, Johnah C / Guzzi, Pietro H / Giorgi, Federico M / Khan, Asma A

Genes and immunity

2020 Volume 21, Issue 5, Page(s) 360–363

Abstract: Pulpitis, inflammation of the dental pulp, is a disease that often necessitates emergency dental care. While pulpitis is considered to be a microbial disease primarily caused by bacteria, viruses have also been implicated in its pathogenesis. Here, we ... ...

Abstract	Pulpitis, inflammation of the dental pulp, is a disease that often necessitates emergency dental care. While pulpitis is considered to be a microbial disease primarily caused by bacteria, viruses have also been implicated in its pathogenesis. Here, we determined the expression of the SARS-CoV2 receptor, angiotensin converting enzyme 2 (ACE2) and its associated cellular serine protease TPMRSS2 in the dental pulp under normal and inflamed conditions. Next, we explored the relationship between the SARS-CoV-2/human interactome and genes expressed in pulpitis. Using existing datasets we show that both ACE2 and TPMRSS2 are expressed in the dental pulp and, that their expression does not change under conditions of inflammation. Furthermore, Master Regulator Analysis of the SARS-CoV2/human interactome identified 75 relevant genes whose expression values are either up-regulated or down-regulated in both the human interactome and pulpitis. Our results suggest that the dental pulp is vulnerable to SARS-CoV2 infection and that SARS-CoV-2 infection of the dental pulp may contribute to worse outcomes of pulpitis.
MeSH term(s)	Angiotensin-Converting Enzyme 2 ; Betacoronavirus/metabolism ; COVID-19 ; Coronavirus Infections/complications ; Coronavirus Infections/metabolism ; Coronavirus Infections/virology ; Datasets as Topic ; Dental Pulp/metabolism ; Dental Pulp/virology ; Gene Expression Profiling ; Gene Expression Regulation ; Humans ; Pandemics ; Peptidyl-Dipeptidase A/metabolism ; Pneumonia, Viral/complications ; Pneumonia, Viral/metabolism ; Pneumonia, Viral/virology ; Pulpitis/metabolism ; Pulpitis/virology ; Receptors, Coronavirus ; Receptors, Virus/metabolism ; SARS-CoV-2 ; Serine Endopeptidases/metabolism
Chemical Substances	Receptors, Coronavirus ; Receptors, Virus ; Peptidyl-Dipeptidase A (EC 3.4.15.1) ; ACE2 protein, human (EC 3.4.17.23) ; Angiotensin-Converting Enzyme 2 (EC 3.4.17.23) ; Serine Endopeptidases (EC 3.4.21.-) ; TMPRSS2 protein, human (EC 3.4.21.-)
Keywords	covid19
Language	English
Publishing date	2020-10-03
Publishing country	England
Document type	Journal Article
ZDB-ID	2060566-3
ISSN	1476-5470 ; 1466-4879
ISSN (online)	1476-5470
ISSN	1466-4879
DOI	10.1038/s41435-020-00112-6
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Article: Master Regulator Analysis of the SARS-CoV-2/Human Interactome.

Guzzi, Pietro H / Mercatelli, Daniele / Ceraolo, Carmine / Giorgi, Federico M

Journal of clinical medicine

2020 Volume 9, Issue 4

Abstract: The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary ... ...

Abstract	The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus.
Keywords	covid19
Language	English
Publishing date	2020-04-01
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662592-1
ISSN	2077-0383
ISSN	2077-0383
DOI	10.3390/jcm9040982
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Article ; Online: Network for network concept offers new insights into host- SARS-CoV-2 protein interactions and potential novel targets for developing antiviral drugs.

Eskandarzade, Neda / Ghorbani, Abozar / Samarfard, Samira / Diaz, Jose / Guzzi, Pietro H / Fariborzi, Niloofar / Tahmasebi, Ahmad / Izadpanah, Keramatollah

Computers in biology and medicine

2022 Volume 146, Page(s) 105575

Abstract: SARS-CoV-2, the causal agent of COVID-19, is primarily a pulmonary virus that can directly or indirectly infect several organs. Despite many studies carried out during the current COVID-19 pandemic, some pathological features of SARS-CoV-2 have remained ... ...

Abstract	SARS-CoV-2, the causal agent of COVID-19, is primarily a pulmonary virus that can directly or indirectly infect several organs. Despite many studies carried out during the current COVID-19 pandemic, some pathological features of SARS-CoV-2 have remained unclear. It has been recently attempted to address the current knowledge gaps on the viral pathogenicity and pathological mechanisms via cellular-level tropism of SARS-CoV-2 using human proteomics, visualization of virus-host protein-protein interactions (PPIs), and enrichment analysis of experimental results. The synergistic use of models and methods that rely on graph theory has enabled the visualization and analysis of the molecular context of virus/host PPIs. We review current knowledge on the SARS-COV-2/host interactome cascade involved in the viral pathogenicity through the graph theory concept and highlight the hub proteins in the intra-viral network that create a subnet with a small number of host central proteins, leading to cell disintegration and infectivity. Then we discuss the putative principle of the "gene-for-gene and "network for network" concepts as platforms for future directions toward designing efficient anti-viral therapies.
MeSH term(s)	Antiviral Agents/pharmacology ; Antiviral Agents/therapeutic use ; Humans ; Pandemics ; Proteins/metabolism ; SARS-CoV-2 ; COVID-19 Drug Treatment
Chemical Substances	Antiviral Agents ; Proteins
Language	English
Publishing date	2022-04-30
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	127557-4
ISSN	1879-0534 ; 0010-4825
ISSN (online)	1879-0534
ISSN	0010-4825
DOI	10.1016/j.compbiomed.2022.105575
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Article: Predicting the response of the dental pulp to SARS-CoV2 infection: a transcriptome-wide effect cross-analysis

Galicia, Johnah C / Guzzi, Pietro H / Giorgi, Federico M / Khan, Asma A

Genes Immun

Abstract	Pulpitis, inflammation of the dental pulp, is a disease that often necessitates emergency dental care. While pulpitis is considered to be a microbial disease primarily caused by bacteria, viruses have also been implicated in its pathogenesis. Here, we determined the expression of the SARS-CoV2 receptor, angiotensin converting enzyme 2 (ACE2) and its associated cellular serine protease TPMRSS2 in the dental pulp under normal and inflamed conditions. Next, we explored the relationship between the SARS-CoV-2/human interactome and genes expressed in pulpitis. Using existing datasets we show that both ACE2 and TPMRSS2 are expressed in the dental pulp and, that their expression does not change under conditions of inflammation. Furthermore, Master Regulator Analysis of the SARS-CoV2/human interactome identified 75 relevant genes whose expression values are either up-regulated or down-regulated in both the human interactome and pulpitis. Our results suggest that the dental pulp is vulnerable to SARS-CoV2 infection and that SARS-CoV-2 infection of the dental pulp may contribute to worse outcomes of pulpitis.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #813984
Database	COVID19

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Article ; Online: Master Regulator Analysis of the SARS-CoV-2/Human Interactome

Guzzi, Pietro H / Mercatelli, Daniele / Ceraolo, Carmine / Giorgi, Federico M

2020

Abstract	The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus.
Keywords	COVID-19 ; SARS-CoV-2 ; bioinformatics ; coronavirus ; gene network analysis ; covid19
Language	English
Publishing country	it
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Master Regulator Analysis of the SARS-CoV-2/Human Interactome

Guzzi, Pietro H. / Mercatelli, Daniele / Ceraolo, Carmine / Giorgi, Federico

Journal of Clinical Medicine, 9(4):982

2020

Abstract	The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus.
Keywords	COVID-19 ; gene network analysis ; bioinformatics ; SARS-CoV-2 ; Coronavirus ; covid19
Language	English
Publishing country	de
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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