CorrelaGenes: a new tool for the interpretation of the human transcriptome

Cremaschi, Paolo; Rovida, Sergio; Sacchi, Lucia; Lisa, Antonella; Calvi, Francesca; Montecucco, Alessandra; Biamonti, Giuseppe; Bione, Silvia; Sacchi, Gianni

doi:10.1186/1471-2105-15-s1-s6

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…The test for statistical independence of specific ARGs and specific transposons was performed using the chi-square test, and the P -value of the chi-square test was used to assess the independence of the two genes ( 48 ) at a significance test level of α = 0.05.…”

Section: Methodsmentioning

confidence: 99%

Synergistic horizontal transfer of antibiotic resistance genes and transposons in the infant gut microbial genome

Ding,

Jiang,

et al. 2024

mSphere

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Transposons, plasmids, bacteriophages, and other mobile genetic elements facilitate horizontal gene transfer in the gut microbiota, allowing some pathogenic bacteria to acquire antibiotic resistance genes (ARGs). Currently, the relationship between specific ARGs and specific transposons in the comprehensive infant gut microbiome has not been elucidated. In this study, ARGs and transposons were annotated from the Unified Human Gastrointestinal Genome (UHGG) and the Early-Life Gut Genomes (ELGG). Association rules mining was used to explore the association between specific ARGs and specific transposons in UHGG, and the robustness of the association rules was validated using the external database in ELGG. Our results suggested that ARGs and transposons were more likely to be relevant in infant gut microbiota compared to adult gut microbiota, and nine robust association rules were identified, among which Klebsiella pneumoniae , Enterobacter hormaechei_A , and Escherichia coli_D played important roles in this association phenomenon. The emphasis of this study is to investigate the synergistic transfer of specific ARGs and specific transposons in the infant gut microbiota, which can contribute to the study of microbial pathogenesis and the ARG dissemination dynamics. IMPORTANCE The transfer of transposons carrying antibiotic resistance genes (ARGs) among microorganisms accelerates antibiotic resistance dissemination among infant gut microbiota. Nonetheless, it is unclear what the relationship between specific ARGs and specific transposons within the infant gut microbiota. K. pneumoniae , E. hormaechei_A , and E. coli_D were identified as key players in the nine robust association rules we discovered. Meanwhile, we found that infant gut microorganisms were more susceptible to horizontal gene transfer events about specific ARGs and specific transposons than adult gut microorganisms. These discoveries could enhance the understanding of microbial pathogenesis and the ARG dissemination dynamics within the infant gut microbiota.

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Section: Methodsmentioning

confidence: 99%

Synergistic horizontal transfer of antibiotic resistance genes and transposons in the infant gut microbial genome

Ding,

Jiang,

et al. 2024

mSphere

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“…Cremaschi, Rovida et al are the authors of "CorrelaGenes: A new tool for the interpretation of the human transcriptomes" [ 9 ]. This paper presents a new approach and tool for mining public gene expression profiles from the Gene Expression Omnibus (GEO) system that couples association rules and χ 2 test.…”

Section: A Short Presentation Of Selected Papersmentioning

confidence: 99%

NETTAB 2012 on "Integrated Bio-Search"

2014

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The NETTAB 2012 workshop, held in Como on November 14-16, 2012, was devoted to "Integrated Bio-Search", that is to technologies, methods, architectures, systems and applications for searching, retrieving, integrating and analyzing data, information, and knowledge with the aim of answering complex bio-medical-molecular questions, i.e. some of the most challenging issues in bioinformatics today. It brought together about 80 researchers working in the field of Bioinformatics, Computational Biology, Biology, Computer Science and Engineering. More than 50 scientific contributions, including keynote and tutorial talks, oral communications, posters and software demonstrations, were presented at the workshop. This preface provides a brief overview of the workshop and shortly introduces the peer-reviewed manuscripts that were accepted for publication in this Supplement.

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An Association Rule Mining Approach to Discover lncRNAs Expression Patterns in Cancer Datasets

Cremaschi

Carriero

Astrologo

et al. 2015

BioMed Research International

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In the past few years, the role of long noncoding RNAs (lncRNAs) in tumor development and progression has been disclosed although their mechanisms of action remain to be elucidated. An important contribution to the comprehension of lncRNAs biology in cancer could be obtained through the integrated analysis of multiple expression datasets. However, the growing availability of public datasets requires new data mining techniques to integrate and describe relationship among data. In this perspective, we explored the powerness of the Association Rule Mining (ARM) approach in gene expression data analysis. By the ARM method, we performed a meta-analysis of cancer-related microarray data which allowed us to identify and characterize a set of ten lncRNAs simultaneously altered in different brain tumor datasets. The expression profiles of the ten lncRNAs appeared to be sufficient to distinguish between cancer and normal tissues. A further characterization of this lncRNAs signature through a comodulation expression analysis suggested that biological processes specific of the nervous system could be compromised.

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CorrelaGenes: a new tool for the interpretation of the human transcriptome

Cited by 3 publications

References 21 publications

Synergistic horizontal transfer of antibiotic resistance genes and transposons in the infant gut microbial genome

Synergistic horizontal transfer of antibiotic resistance genes and transposons in the infant gut microbial genome

NETTAB 2012 on "Integrated Bio-Search"

An Association Rule Mining Approach to Discover lncRNAs Expression Patterns in Cancer Datasets

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