International Journal of Molecular Sciences
Alessandri, Luca; Ratto, Maria Luisa; Contaldo, Sandro Gepiro; Beccuti, Marco; Cordero, Francesca; Arigoni, Maddalena; Calogero, Raffaele A.
Background: Biological processes are based on complex networks of cells and molecules. Single cell multi‐omics is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell. Methods: Since single cell technologies provide many sample measurements, they are the ideal environment for the application of Deep Learning and Machine Learning approaches. An autoencoder is composed of an encoder and a decoder sub-model. An autoencoder is a very powerful […]
Licheri, Nicola; Bonnici, Vincenzo; Beccuti, Marco; Giugno, Rosalba
Background: Graphs are mathematical structures widely used for expressing relationships among elements when representing biomedical and biological information. On top of these representations, several analyses are performed. A common task is the search of one substructure within one graph, called target. The problem is referred to as one-to-one subgraph search, and it is known to be NP-complete. Heuristics and indexing techniques can be applied to facilitate the search. Indexing techniques are also […]
npj Systems Biology and Applications
Alessandri, Luca; Cordero, Francesca; Beccuti, Marco; Licheri, Nicola; Arigoni, Maddalena; Olivero, Martina; Di Renzo, Maria Flavia; Sapino, Anna; Calogero, Raffaele
Single-cell RNA sequencing (scRNAseq) is an essential tool to investigate cellular heterogeneity. Thus, it would be of great interest being able to disclose biological information belonging to cell subpopulations, which can be defined by clustering analysis of scRNAseq data. In this manuscript, we report a tool that we developed for the functional mining of single cell clusters based on Sparsely-Connected Autoencoder (SCA). This tool allows uncovering hidden features associated with scRNAseq data. […]
International Conference on Information and Knowledge Management, Proceedings
Beccuti, Marco; Bonnici, Vincenzo; Giugno, Rosalba
Multi-omics analysis aims at extracting previously uncovered biological knowledge by integrating information across multiple single-omic sources. Past approaches have focused on the simultaneous analysis of a small number of omic data sets. Current challenges face the problem of integrating multiple omic sources into a unified complex model, or of combining already available tools for two-by-two omics analyses and merging their outcomes. By doing so and leveraging integrated system-level knowledge, […]
Genuardi, Elisa; Romano, Greta; Beccuti, Marco; Alessandria, Beatrice; Mannina, Donato; Califano, Catello; Rota Scalabrini, Delia; Cortelazzo, Sergio; Ladetto, Marco; Ferrero, Simone; Calogero, Raffaele A.; Cordero, Francesca
Minimal residual disease (MRD) determined by classic polymerase chain reaction (PCR) methods is a powerful outcome predictor in mantle cell lymphoma (MCL). Nevertheless, some technical pitfalls can reduce the rate of of molecular markers. Therefore, we applied the EuroClonality-NGS IGH (next-generation sequencing immunoglobulin heavy chain) method (previously published in acute lymphoblastic leukaemia) to 20 MCL patients enrolled in an Italian phase III trial sponsored by Fondazione Italiana Linfomi. […]
International Journal of Molecular Sciences
Nosi, Vladimir; Luca, Alessandrì; Milan, Melissa; Arigoni, Maddalena; Benvenuti, Silvia; Cacchiarelli, Davide; Cesana, Marcella; Riccardo, Sara; Filippo, Lucio Di; Cordero, Francesca; Beccuti, Marco; Comoglio, Paolo M.; Calogero, Raffaele A.
Background: Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell lung cancer (NSCLC) MET exon 14 skipping was shown to be targetable. Methods: We constructed neural networks (NN/CNN) specifically designed to detect MET exon 14 skipping events using RNAseq data. Furthermore, for discovery purposes we also developed […]
Proceedings – 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Amparore, Elvio Gilberto; Beccuti, Marco; Castagno, Paolo; Franceschinis, Giuliana; Pennisi, Marzio; Pernice, Simone
The immune system (IS) represents a complex network of cells and molecules devoted to the protection of individuals from external pathogens, and in terms of complexity, it is only second to the central nervous system. As our knowledge of the IS mechanisms has become more exhaustive, interest has grown in applying modeling and simulation techniques in this context. In particular, among these techniques, the Agent Based Models (ABMs) have been increasingly applied for the IS simulation. One of the […]
CEUR Workshop Proceedings
Licheri, Nicola; Amparore, Elvio; Bonnici, Vincenzo; Giugno, Rosalba; Beccuti, Marco
Graphs are a widely used structure for knowledge representation. Their uses range from biochemical to biomedical applications and are recently involved in multi-omics analyses. A key computational task regarding graphs is the search of specific topologies contained in them. The task is known to be NP-complete, thus indexing techniques are applied for dealing with its complexity. In particular, techniques exploiting paths extracted from graphs have shown good performances in terms of time requirements, […]
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Beccuti, M.; Castagno, P.; Franceschinis, G.; Pennisi, M.; Pernice, S.
The recent technological advances in computer science have enabled the definition of new modeling paradigms that differ from the classical ones in describing the system in terms of its components or entities. Among them, Agent-Based Models (ABMs) are gaining more and more popularity thanks to their ability to capture emergent phenomena resulting from the interactions of individual entities. However, ABMs lack a formal definition and precisely defined semantics. To overcome this issue we propose a […]
Methods in Molecular Biology
Alessandrì, Luca; Cordero, Francesca; Beccuti, Marco; Arigoni, Maddalena; Calogero, Raffaele A.
Single-cell RNAseq data can be generated using various technologies, spanning from isolation of cells by FACS sorting or droplet sequencing, to the use of frozen tissue sections retaining spatial information of cells in their morphological context. The analysis of single cell RNAseq data is mainly focused on the identification of cell subpopulations characterized by specific gene markers that can be used to purify the population of interest for further biological studies. This chapter describes the […]
Methods in Molecular Biology
Ferrero, Giulio; Licheri, Nicola; De Bortoli, Michele; Calogero, Raffaele A.; Beccuti, Marco; Cordero, Francesca
Analysis of circular RNA (circRNA) expression from RNA-Seq data can be performed with different algorithms and analysis pipelines, tools allowing the extraction of heterogeneous information on the expression of this novel class of RNAs. Computational pipelines were developed to facilitate the analysis of circRNA expression by leveraging different public tools in easy-to-use pipelines. This chapter describes the complete workflow for a computationally reproducible analysis of circRNA expression starting […]
Francavilla, Antonio; Gagliardi, Amedeo; Piaggeschi, Giulia; Tarallo, Sonia; Cordero, Francesca; Pensa, Ruggero G.; Impeduglia, Alessia; Caviglia, Gian Paolo; Ribaldone, Davide Giuseppe; Gallo, Gaetano; Grioni, Sara; Ferrero, Giulio; Pardini, Barbara; Naccarati, Alessio
For their stability and detectability faecal microRNAs represent promising molecules with potential clinical interest as non-invasive diagnostic and prognostic biomarkers. However, there is no evidence on how stool miRNA profiles change according to an individual’s age, sex, and body mass index (BMI) or how lifestyle habits influence the expression levels of these molecules. We explored the relationship between the stool miRNA levels and common traits (sex, age, BMI, and menopausal status) or lifestyle […]
Frontiers in Immunology
Piaggeschi, Giulia; Rolla, Simona; Rossi, Niccolò; Brusa, Davide; Naccarati, Alessio; Couvreur, Simon; Spector, Tim D.; Roederer, Mario; Mangino, Massimo; Cordero, Francesca; Falchi, Mario; Visconti, Alessia
Tobacco smoking is known to impact circulating levels of major immune cells populations, but its effect on specific immune cell subsets remains poorly understood. Here, using high-resolution data from 223 healthy women (25 current and 198 never smokers), we investigated the association between smoking status and 35,651 immune traits capturing immune cell subset frequencies. Our results confirmed that active tobacco smoking is associated with increased frequencies of circulating CD8+ T cells expressing […]
International Journal of Molecular Sciences
Alessandri, Luca; Ratto, Maria Luisa; Contaldo, Sandro Gepiro; Beccuti, Marco; Cordero, Francesca; Arigoni, Maddalena; Calogero, Raffaele A.
Background: Biological processes are based on complex networks of cells and molecules. Single cell multi‐omics is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell. Methods: Since single cell technologies provide many sample measurements, they are the ideal environment for the application of Deep Learning and Machine Learning approaches. An autoencoder is composed of an encoder and a decoder sub-model. An autoencoder is a very powerful […]
BMC Bioinformatics
Licheri, Nicola; Bonnici, Vincenzo; Beccuti, Marco; Giugno, Rosalba
Background: Graphs are mathematical structures widely used for expressing relationships among elements when representing biomedical and biological information. On top of these representations, several analyses are performed. A common task is the search of one substructure within one graph, called target. The problem is referred to as one-to-one subgraph search, and it is known to be NP-complete. Heuristics and indexing techniques can be applied to facilitate the search. Indexing techniques are also […]
npj Systems Biology and Applications
Alessandri, Luca; Cordero, Francesca; Beccuti, Marco; Licheri, Nicola; Arigoni, Maddalena; Olivero, Martina; Di Renzo, Maria Flavia; Sapino, Anna; Calogero, Raffaele
Single-cell RNA sequencing (scRNAseq) is an essential tool to investigate cellular heterogeneity. Thus, it would be of great interest being able to disclose biological information belonging to cell subpopulations, which can be defined by clustering analysis of scRNAseq data. In this manuscript, we report a tool that we developed for the functional mining of single cell clusters based on Sparsely-Connected Autoencoder (SCA). This tool allows uncovering hidden features associated with scRNAseq data. […]
International Conference on Information and Knowledge Management, Proceedings
Beccuti, Marco; Bonnici, Vincenzo; Giugno, Rosalba
Multi-omics analysis aims at extracting previously uncovered biological knowledge by integrating information across multiple single-omic sources. Past approaches have focused on the simultaneous analysis of a small number of omic data sets. Current challenges face the problem of integrating multiple omic sources into a unified complex model, or of combining already available tools for two-by-two omics analyses and merging their outcomes. By doing so and leveraging integrated system-level knowledge, […]
British Journal of Haematology
Genuardi, Elisa; Romano, Greta; Beccuti, Marco; Alessandria, Beatrice; Mannina, Donato; Califano, Catello; Rota Scalabrini, Delia; Cortelazzo, Sergio; Ladetto, Marco; Ferrero, Simone; Calogero, Raffaele A.; Cordero, Francesca
Minimal residual disease (MRD) determined by classic polymerase chain reaction (PCR) methods is a powerful outcome predictor in mantle cell lymphoma (MCL). Nevertheless, some technical pitfalls can reduce the rate of of molecular markers. Therefore, we applied the EuroClonality-NGS IGH (next-generation sequencing immunoglobulin heavy chain) method (previously published in acute lymphoblastic leukaemia) to 20 MCL patients enrolled in an Italian phase III trial sponsored by Fondazione Italiana Linfomi. […]
International Journal of Molecular Sciences
Nosi, Vladimir; Luca, Alessandrì; Milan, Melissa; Arigoni, Maddalena; Benvenuti, Silvia; Cacchiarelli, Davide; Cesana, Marcella; Riccardo, Sara; Filippo, Lucio Di; Cordero, Francesca; Beccuti, Marco; Comoglio, Paolo M.; Calogero, Raffaele A.
Background: Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell lung cancer (NSCLC) MET exon 14 skipping was shown to be targetable. Methods: We constructed neural networks (NN/CNN) specifically designed to detect MET exon 14 skipping events using RNAseq data. Furthermore, for discovery purposes we also developed […]
Proceedings – 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Amparore, Elvio Gilberto; Beccuti, Marco; Castagno, Paolo; Franceschinis, Giuliana; Pennisi, Marzio; Pernice, Simone
The immune system (IS) represents a complex network of cells and molecules devoted to the protection of individuals from external pathogens, and in terms of complexity, it is only second to the central nervous system. As our knowledge of the IS mechanisms has become more exhaustive, interest has grown in applying modeling and simulation techniques in this context. In particular, among these techniques, the Agent Based Models (ABMs) have been increasingly applied for the IS simulation. One of the […]
CEUR Workshop Proceedings
Licheri, Nicola; Amparore, Elvio; Bonnici, Vincenzo; Giugno, Rosalba; Beccuti, Marco
Graphs are a widely used structure for knowledge representation. Their uses range from biochemical to biomedical applications and are recently involved in multi-omics analyses. A key computational task regarding graphs is the search of specific topologies contained in them. The task is known to be NP-complete, thus indexing techniques are applied for dealing with its complexity. In particular, techniques exploiting paths extracted from graphs have shown good performances in terms of time requirements, […]
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Beccuti, M.; Castagno, P.; Franceschinis, G.; Pennisi, M.; Pernice, S.
The recent technological advances in computer science have enabled the definition of new modeling paradigms that differ from the classical ones in describing the system in terms of its components or entities. Among them, Agent-Based Models (ABMs) are gaining more and more popularity thanks to their ability to capture emergent phenomena resulting from the interactions of individual entities. However, ABMs lack a formal definition and precisely defined semantics. To overcome this issue we propose a […]
Methods in Molecular Biology
Alessandrì, Luca; Cordero, Francesca; Beccuti, Marco; Arigoni, Maddalena; Calogero, Raffaele A.
Single-cell RNAseq data can be generated using various technologies, spanning from isolation of cells by FACS sorting or droplet sequencing, to the use of frozen tissue sections retaining spatial information of cells in their morphological context. The analysis of single cell RNAseq data is mainly focused on the identification of cell subpopulations characterized by specific gene markers that can be used to purify the population of interest for further biological studies. This chapter describes the […]
Methods in Molecular Biology
Ferrero, Giulio; Licheri, Nicola; De Bortoli, Michele; Calogero, Raffaele A.; Beccuti, Marco; Cordero, Francesca
Analysis of circular RNA (circRNA) expression from RNA-Seq data can be performed with different algorithms and analysis pipelines, tools allowing the extraction of heterogeneous information on the expression of this novel class of RNAs. Computational pipelines were developed to facilitate the analysis of circRNA expression by leveraging different public tools in easy-to-use pipelines. This chapter describes the complete workflow for a computationally reproducible analysis of circRNA expression starting […]
Scientific Reports
Francavilla, Antonio; Gagliardi, Amedeo; Piaggeschi, Giulia; Tarallo, Sonia; Cordero, Francesca; Pensa, Ruggero G.; Impeduglia, Alessia; Caviglia, Gian Paolo; Ribaldone, Davide Giuseppe; Gallo, Gaetano; Grioni, Sara; Ferrero, Giulio; Pardini, Barbara; Naccarati, Alessio
For their stability and detectability faecal microRNAs represent promising molecules with potential clinical interest as non-invasive diagnostic and prognostic biomarkers. However, there is no evidence on how stool miRNA profiles change according to an individual’s age, sex, and body mass index (BMI) or how lifestyle habits influence the expression levels of these molecules. We explored the relationship between the stool miRNA levels and common traits (sex, age, BMI, and menopausal status) or lifestyle […]
Frontiers in Immunology
Piaggeschi, Giulia; Rolla, Simona; Rossi, Niccolò; Brusa, Davide; Naccarati, Alessio; Couvreur, Simon; Spector, Tim D.; Roederer, Mario; Mangino, Massimo; Cordero, Francesca; Falchi, Mario; Visconti, Alessia
Tobacco smoking is known to impact circulating levels of major immune cells populations, but its effect on specific immune cell subsets remains poorly understood. Here, using high-resolution data from 223 healthy women (25 current and 198 never smokers), we investigated the association between smoking status and 35,651 immune traits capturing immune cell subset frequencies. Our results confirmed that active tobacco smoking is associated with increased frequencies of circulating CD8+ T cells expressing […]