Article
Computer Science, Artificial Intelligence
Ramakrishnan Raman, Amit Barve, R. Meenakshi, G. M. Jayaseelan, P. Ganeshan, Syed Noeman Taqui, Hesham S. Almoallim, Sulaiman Ali Alharbi, S. S. Raghavan
Summary: This paper presents a deep learning methodology for taxonomic categorization of metagenomic information, using DBNs and CNNs for feature extraction and processing. The proposed methodology outperforms traditional classifiers and can be used for bacterial sample classification.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Biochemical Research Methods
Hongxuan Zhai, Julia Fukuyama
Summary: K-mer-based distances are often used to describe differences between communities in metagenome sequencing studies. In this paper, we show a strong relationship between k-mer-based distances and phylogenetically-informed beta-diversity measures. Our results allow for phylogenetically-informed analyses using only k-mer data and provide insight into one class of phylogenetically-informed beta-diversity measures.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Genetics & Heredity
Timothy Chappell, Shlomo Geva, James M. Hogan, David Lovell, Andrew Trotman, Dimitri Perrin
Summary: We propose a novel approach for the Metagenomic Geolocation Challenge that utilizes random projection of sample reads. This approach directly uses k-mer composition to characterize samples, eliminating the computationally demanding step of aligning reads to microbial reference sequences. Our findings demonstrate that k-mer representations carry sufficient information to determine the origin of metagenomic samples and that this reference-free approach requires less computation compared to previous methods.
FRONTIERS IN GENETICS
(2022)
Article
Ecology
Po-Yu Liu, Shan-Hua Yang, Sung-Yin Yang
Summary: The new algorithm KTU (K-mer Taxonomic Unit) re-clusters ASVs into optimal biological taxonomic units, improving biological explanations for correlations and significances of clinical and environmental factors.
METHODS IN ECOLOGY AND EVOLUTION
(2022)
Article
Genetics & Heredity
Diego A. A. Morais, Joao V. F. Cavalcante, Shenia S. Monteiro, Matheus A. B. Pasquali, Rodrigo J. S. Dalmolin
Summary: Metagenomic studies provide valuable insights into the taxonomic composition and functional characteristics of microbial communities. However, selecting and setting up the appropriate tools for comprehensive metagenomic analysis poses challenges. In this study, the researchers surveyed state-of-the-art tools, created simulated datasets, and performed benchmarks to develop an efficient and flexible metagenomic analysis pipeline called MEDUSA. Compared to existing tools, MEDUSA accurately identifies a greater number of species and is well-suited for functional analysis.
FRONTIERS IN GENETICS
(2022)
Article
Biochemical Research Methods
Yoann Dufresne, Teo Lemane, Pierre Marijon, Pierre Peterlongo, Amatur Rahman, Marek Kokot, Paul Medvedev, Sebastian Deorowicz, Rayan Chikhi
Summary: The research introduces the K-mer File Format as a general framework for storing and manipulating k-mer sets, achieving significant space savings compared to other formats and enabling interoperability across different tools.
Article
Biotechnology & Applied Microbiology
Rajan Saha Raju, Abdullah Al Nahid, Preonath Chondrow Dev, Rashedul Islam
Summary: The classification of viruses is essential for organizing the abundant virus population. However, assigning taxonomy to virus sequences is challenging. In this study, a method called VirusTaxo was developed using diverse virus genera to classify viruses from metagenomic sequences.
Review
Microbiology
Alban Mathieu, Mickael Leclercq, Melissa Sanabria, Olivier Perin, Arnaud Droit
Summary: Shotgun sequencing of environmental DNA has greatly advanced the field of environmental microbiology, but current alignment methods have limitations. Deep learning models show promise in improving annotation efficiency, but their robustness needs further validation in different environmental samples and genome databases.
FRONTIERS IN MICROBIOLOGY
(2022)
Article
Biochemical Research Methods
Davide Storato, Matteo Comin
Summary: The paper focuses on improving metagenomic reads classification by enhancing the reference k-mer library with novel discriminative k-mers from the input sequencing reads. The results demonstrate an improved F-measure, particularly in the absence of close reference genomes.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Carlo Ferravante, Domenico Memoli, Domenico Palumbo, Paolo Ciaramella, Antonio Di Loria, Ylenia D'Agostino, Giovanni Nassa, Francesca Rizzo, Roberta Tarallo, Alessandro Weisz, Giorgio Giurato
Summary: HOME-BIO is a comprehensive pipeline for metagenomics data analysis, comprising three independent analytical modules designed for an inclusive analysis of large NGS datasets. It is a powerful and easy-to-use tool that can be run by users with limited computational expertise, allowing in-depth analyses and customization according to specific user needs.
BMC BIOINFORMATICS
(2021)
Article
Biotechnology & Applied Microbiology
Alon Kafri, Benny Chor, David Horn
Summary: Background Inversion Symmetry is a generalization of the second Chargaff rule, stating that the count of a string of k nucleotides on a single chromosomal strand equals the count of its inverse (reverse-complement) k-mer. It holds for many species, both eukaryotes and prokaryotes, for ranges of k which may vary from 7 to 10 as chromosomal lengths vary from 2Mbp to 200 Mbp. Building on this formalism, the concept of k-mer distances between chromosomes is introduced, with two distance measures, D-1 and D-2, formulated. Exploration of k-mer distances has led to the discovery of measures of evolutionary distances among bacterial strains based on synteny blocks between chromosomes.
Article
Gastroenterology & Hepatology
Naoyoshi Nagata, Suguru Nishijima, Yasushi Kojima, Yuya Hisada, Koh Imbe, Tohru Miyoshi-Akiyama, Wataru Suda, Moto Kimura, Ryo Aoki, Katsunori Sekine, Mitsuru Ohsugi, Kuniko Miki, Tsuyoshi Osawa, Kohjiro Ueki, Shinichi Oka, Masashi Mizokami, Ece Kartal, Thomas S. B. Schmidt, Esther Molina-Montes, Lidia Estudillo, Nuria Malats, Jonel Trebicka, Stephan Kersting, Melanie Langheinrich, Peer Bork, Naomi Uemura, Takao Itoi, Takashi Kawai
Summary: This study identified gut and oral metagenomic signatures that accurately predict pancreatic ductal carcinoma (PDAC) and validated their effectiveness in independent cohorts. Patients with certain microbial species in the gut and oral microbiomes were found to have higher risk of PDAC-related mortality. These findings provide valuable information for the diagnosis and prognosis of PDAC.
Article
Microbiology
Jiayin Zhou, Xiaoli Yu, Jihua Liu, Wei Qin, Zhili He, David Stahl, Nianzhi Jiao, Jizhong Zhou, Qichao Tu
Summary: In this study, a curated functional gene database called VB(12)Path was developed for accurate metagenomic profiling of VB12 synthesis gene families in complex environments. The results revealed significant differences in VB12 synthesis processes between the ocean and the human intestine. This database is expected to be a valuable tool for studying cobalamin biosynthesis processes in both environmental and human microbiome research.
Article
Biochemistry & Molecular Biology
Silvio Weging, Andreas Gogol-Doring, Ivo Grosse
Summary: kASA is a tool based on k-mer, capable of efficiently identifying and profiling metagenomic DNA or protein sequences with high sensitivity and precision. Custom algorithms and data structures optimized for external memory storage enable a full-scale taxonomic analysis on various devices.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Food Science & Technology
Irene Franciosa, Ilario Ferrocino, Manuela Giordano, Jerome Mounier, Kalliopi Rantsiou, Luca Cocolin
Summary: Using Metagenomics, this study investigated the microbial dynamics in the fermentation process of Salame Piemonte sausage, identifying how different strains of L. sakei can significantly influence the quality characteristics of the final product.
FOOD RESEARCH INTERNATIONAL
(2021)
Article
Computer Science, Interdisciplinary Applications
Giovanni Giacalone, Marco Barra, Angelo Bonanno, Gualtiero Basilone, Ignazio Fontana, Monica Calabro, Simona Genovese, Rosalia Ferreri, Giuseppa Buscaino, Salvatore Mazzola, Riko Noormets, Christopher Nuth, Giosue Lo Bosco, Riccardo Rizzo, Salvatore Aronica
Summary: In this study, acoustic data collected in Kongsfjorden, Svalbard, was analyzed to develop a method for identifying and classifying fish aggregations using 3D acoustic patterns. The results suggest that three distinct groups can be identified mathematically. This approach shows promise for improving monitoring programs for marine resources and can be applied to climate change research.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Computer Science, Interdisciplinary Applications
Ignazio Fontana, Marco Barra, Angelo Bonanno, Giovanni Giacalone, Riccardo Rizzo, Olga Mangoni, Simona Genovese, Gualtiero Basilone, Rosalia Ferreri, Salvatore Mazzola, Giosue Lo Bosco, Salvatore Aronica
Summary: Acoustic surveys play a significant role in assessing the distribution and abundance of pelagic organisms. The identification of species in acoustic observations is usually based on biological sampling and expert knowledge. This study examines the use of unsupervised clustering methods for identifying krill species and finds that k-means performs better than hierarchical methods. The findings highlight the importance of selecting specific variables for clustering analysis to improve accuracy.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Biochemistry & Molecular Biology
Federica Scalia, Rosario Barone, Francesca Rappa, Antonella Marino Gammazza, Fabrizio Lo Celso, Giosue Lo Bosco, Giampaolo Barone, Vincenzo Antona, Maria Vadala, Alessandra Maria Vitale, Giuseppe Donato Mangano, Domenico Amato, Giusy Sentiero, Filippo Macaluso, Kathryn H. Myburgh, Everly Conway de Macario, Alberto J. L. Macario, Mario Giuffre, Francesco Cappello
Summary: Recognition of diseases associated with mutations of the chaperone system genes (chaperonopathies) is increasing, but the impact of the mutation on the chaperone molecule and the mechanisms underlying tissue abnormalities are not well understood. This study examined the histological features of skeletal muscle from a patient with a severe, early onset, distal motor neuropathy carrying a mutation on the CCT5 subunit (MUT). The mutated muscle showed significant modifications including fiber atrophy, disruption of tissue architecture, and apoptosis. The study also found abnormal localization and precipitation of various proteins in the mutated muscle. In silico analyses of the mutant CCT5 molecule revealed abnormalities that could impair chaperoning functions. Further in vitro and in vivo analysis of the mutated CCT5 is anticipated to provide additional insights on subunit involvement in neuromuscular disorders.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Computer Science, Software Engineering
Domenico Amato, Giosue Lo Bosco, Raffaele Giancarlo
Summary: Learned Indexes use a model to restrict the search range of a sorted table, and using the SOSD benchmarking software, this study demonstrates that k-ary search is more efficient in certain computer architectures. This research provides guidelines for selecting the search routine within the learned indexing framework.
SOFTWARE-PRACTICE & EXPERIENCE
(2023)
Article
Biochemistry & Molecular Biology
Laura La Paglia, Mirella Vazzana, Manuela Mauro, Francesca Dumas, Antonino Fiannaca, Alfonso Urso, Vincenzo Arizza, Aiti Vizzini
Summary: Through bioinformatics and in vivo experiments, it was found that LPS induction activates the expression of multiple immune genes in granulocyte hemocytes, leading to the activation of the Nf-kB signaling pathway and downstream pro-inflammatory gene expression. The study reveals the evolutionarily conserved functional link between the Mif-Csn-Nf-kB axis in the ascidian C. robusta during LPS-mediated inflammation response, which is finely regulated by non-coding molecules such as microRNAs.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemical Research Methods
Antonino Fiannaca, Massimo La Rosa, Laura La Paglia, Salvatore Gaglio, Alfonso Urso
Summary: Single-cell RNA-sequencing enables the characterization of cell types and estimation of cell population composition. This study presents a GOWDL model, which combines gene ontology and marker genes, for cell type classification and demonstrates its effectiveness in multiple tissues.
BRIEFINGS IN BIOINFORMATICS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Gianmarco Coppola, Antonino Fiannaca, Massimo La Rosa, Laura La Paglia, Alfonso Urso, Salvatore Gaglio
Summary: Recent advances in single-cell RNA-sequencing and the availability of more data have led to the development of algorithms for analyzing single cells in gene expression data. This study proposes an artificial intelligence architecture that classifies cell types in human tissue. Combining a deep learning model based on convolutional neural network (CNN) with a wide model, the architecture integrates the concept of functional genes neighborhood from Gene Ontology into the CNN model and incorporates information on biologically relevant marker genes for each cell type in the underlying human tissue. The proposed architecture was tested on seven human tissue datasets and compared with three reference literature algorithms, showing equal or better performance than the other models within each tissue.
ENGINEERING APPLICATIONS OF NEURAL NETWORKS, EAAAI/EANN 2022
(2022)
Proceedings Paper
Computer Science, Information Systems
Salvatore Calderaro, Giosue Lo Bosco, Riccardo Rizzo, Filippo Vella
Summary: This study proposes a histopathological image classification method based on convolutional neural networks. By utilizing metric learning, the network learns a representation that clusters labeled samples based on their characteristics, improving classification performance and supporting labeling decisions.
2022 IEEE EIGHTH INTERNATIONAL CONFERENCE ON MULTIMEDIA BIG DATA (BIGMM 2022)
(2022)
Article
Biochemistry & Molecular Biology
Massimo La Rosa, Antonino Fiannaca, Laura La Paglia, Alfonso Urso
Summary: This study presents a graph neural network (GNN) approach for analyzing RNA interference-messenger RNA interaction networks. The GNN method has the ability to predict the efficacy of siRNA and achieves high accuracy on benchmark datasets.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Antonino D'Alessandro, Andrea Di Benedetto, Giosue Lo Bosco, Anna Figlioli
Summary: This work introduces an active learning approach to improve the classification of seismo-volcanic events, particularly explosion quakes, using a random forest classifier. Human intervention is involved to annotate uncertain data, resulting in improved probability distribution of events after intervention.
2022 IEEE CONFERENCE ON EVOLVING AND ADAPTIVE INTELLIGENT SYSTEMS (IEEE EAIS 2022)
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Mariella Farella, Giuseppe Chiazzese, Giosue Lo Bosco
Summary: This paper proposes the design of an avatar system with question-answering capabilities for immersive navigation of cultural heritage sites. The system utilizes technologies like Virtual Reality, Augmented Reality, and Artificial Intelligence to enhance user experience.
2022 IEEE 21ST MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (IEEE MELECON 2022)
(2022)
Article
Biochemistry & Molecular Biology
Claudia Musial, Narcyz Knap, Renata Zaucha, Paulina Bastian, Giampaolo Barone, Giosue Lo Bosco, Fabrizio Lo-Celso, Lucyna Konieczna, Mariusz Belka, Tomasz Baczek, Antonella Marino Gammazza, Alicja Kuban-Jankowska, Francesco Cappello, Stephan Nussberger, Magdalena Gorska-Ponikowska
Summary: 2-Methoxyestradiol (2-ME) as an inhibitor for non-small cell lung cancer cells may serve as a potential therapeutic approach, reducing cell viability, promoting protein palmitoylation and oxidative stress, and showing relative safety in healthy human cells compared to other estrogen metabolism intermediates.