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Daniel Thomas S, Vijayakumar K, John L, Krishnan D, Rehman N, Revikumar A, Kandel Codi JA, Prasad TSK, S S V, Raju R. Machine Learning Strategies in MicroRNA Research: Bridging Genome to Phenome. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2024; 28:213-233. [PMID: 38752932 DOI: 10.1089/omi.2024.0047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2024]
Abstract
MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression. This article offers the salient and current aspects of machine learning (ML) tools and approaches from genome to phenome in miRNA research. First, we underline that the complexity in the analysis of miRNA function ranges from their modes of biogenesis to the target diversity in diverse biological conditions. Therefore, it is imperative to first ascertain the miRNA coding potential of genomes and understand the regulatory mechanisms of their expression. This knowledge enables the efficient classification of miRNA precursors and the identification of their mature forms and respective target genes. Second, and because one miRNA can target multiple mRNAs and vice versa, another challenge is the assessment of the miRNA-mRNA target interaction network. Furthermore, long-noncoding RNA (lncRNA)and circular RNAs (circRNAs) also contribute to this complexity. ML has been used to tackle these challenges at the high-dimensional data level. The present expert review covers more than 100 tools adopting various ML approaches pertaining to, for example, (1) miRNA promoter prediction, (2) precursor classification, (3) mature miRNA prediction, (4) miRNA target prediction, (5) miRNA- lncRNA and miRNA-circRNA interactions, (6) miRNA-mRNA expression profiling, (7) miRNA regulatory module detection, (8) miRNA-disease association, and (9) miRNA essentiality prediction. Taken together, we unpack, critically examine, and highlight the cutting-edge synergy of ML approaches and miRNA research so as to develop a dynamic and microlevel understanding of human health and diseases.
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Affiliation(s)
- Sonet Daniel Thomas
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
| | - Krithika Vijayakumar
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
| | - Levin John
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
| | - Deepak Krishnan
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
| | - Niyas Rehman
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
| | - Amjesh Revikumar
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
- Kerala Genome Data Centre, Kerala Development and Innovation Strategic Council, Thiruvananthapuram, Kerala, India
| | - Jalaluddin Akbar Kandel Codi
- Department of Surgical Oncology, Yenepoya Medical College, Yenepoya (Deemed to Be University), Manglore, Karnataka, India
| | | | - Vinodchandra S S
- Department of Computer Science, University of Kerala, Thiruvananthapuram, Kerala, India
| | - Rajesh Raju
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya (Deemed to Be University), Manglore, Karnataka, India
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La Paglia L, Vazzana M, Mauro M, Dumas F, Fiannaca A, Urso A, Arizza V, Vizzini A. Transcriptomic and Bioinformatic Analyses Identifying a Central Mif-Cop9-Nf-kB Signaling Network in Innate Immunity Response of Ciona robusta. Int J Mol Sci 2023; 24:ijms24044112. [PMID: 36835523 PMCID: PMC9960688 DOI: 10.3390/ijms24044112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/13/2023] [Accepted: 02/16/2023] [Indexed: 02/22/2023] Open
Abstract
The Ascidian C. robusta is a powerful model for studying innate immunity. LPS induction activates inflammatory-like reactions in the pharynx and the expression of several innate immune genes in granulocyte hemocytes such as cytokines, for instance, macrophage migration inhibitory factors (CrMifs). This leads to intracellular signaling involving the Nf-kB signaling cascade that triggers downstream pro-inflammatory gene expression. In mammals, the COP9 (Constitutive photomorphogenesis 9) signalosome (CSN) complex also results in the activation of the NF-kB pathway. It is a highly conserved complex in vertebrates, mainly engaged in proteasome degradation which is essential for maintaining processes such as cell cycle, DNA repair, and differentiation. In the present study, we used bioinformatics and in-silico analyses combined with an in-vivo LPS exposure strategy, next-generation sequencing (NGS), and qRT-PCR to elucidate molecules and the temporal dynamics of Mif cytokines, Csn signaling components, and the Nf-κB signaling pathway in C. robusta. A qRT-PCR analysis of immune genes selected from transcriptome data revealed a biphasic activation of the inflammatory response. A phylogenetic and STRING analysis indicated an evolutionarily conserved functional link between the Mif-Csn-Nf-kB axis in ascidian C. robusta during LPS-mediated inflammation response, finely regulated by non-coding molecules such as microRNAs (miRNAs).
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Affiliation(s)
- Laura La Paglia
- Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy
| | - Mirella Vazzana
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy
| | - Manuela Mauro
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy
| | - Francesca Dumas
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy
| | - Antonino Fiannaca
- Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy
| | - Alfonso Urso
- Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy
| | - Vincenzo Arizza
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy
| | - Aiti Vizzini
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy
- Correspondence:
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Hauschild AC, Pastrello C, Ekaputeri G, Bethune-Waddell D, Abovsky M, Ahmed Z, Kotlyar M, Lu R, Jurisica I. MirDIP 5.2: tissue context annotation and novel microRNA curation. Nucleic Acids Res 2022; 51:D217-D225. [PMID: 36453996 PMCID: PMC9825511 DOI: 10.1093/nar/gkac1070] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/16/2022] [Accepted: 11/28/2022] [Indexed: 12/05/2022] Open
Abstract
MirDIP is a well-established database that aggregates microRNA-gene human interactions from multiple databases to increase coverage, reduce bias, and improve usability by providing an integrated score proportional to the probability of the interaction occurring. In version 5.2, we removed eight outdated resources, added a new resource (miRNATIP), and ran five prediction algorithms for miRBase and mirGeneDB. In total, mirDIP 5.2 includes 46 364 047 predictions for 27 936 genes and 2734 microRNAs, making it the first database to provide interactions using data from mirGeneDB. Moreover, we curated and integrated 32 497 novel microRNAs from 14 publications to accelerate the use of these novel data. In this release, we also extend the content and functionality of mirDIP by associating contexts with microRNAs, genes, and microRNA-gene interactions. We collected and processed microRNA and gene expression data from 20 resources and acquired information on 330 tissue and disease contexts for 2657 microRNAs, 27 576 genes and 123 651 910 gene-microRNA-tissue interactions. Finally, we improved the usability of mirDIP by enabling the user to search the database using precursor IDs, and we integrated miRAnno, a network-based tool for identifying pathways linked to specific microRNAs. We also provide a mirDIP API to facilitate access to its integrated predictions. Updated mirDIP is available at https://ophid.utoronto.ca/mirDIP.
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Affiliation(s)
| | | | - Gitta Kirana Anindya Ekaputeri
- Department of Medical Informatics, University Medical Center Göttingen, Georg-August University, Göttingen, Lower Saxony 37075, Germany
| | - Dylan Bethune-Waddell
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto M5T 0S8, Canada
| | - Mark Abovsky
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto M5T 0S8, Canada
| | - Zuhaib Ahmed
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto M5T 0S8, Canada
| | - Max Kotlyar
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto M5T 0S8, Canada
| | - Richard Lu
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto M5T 0S8, Canada
| | - Igor Jurisica
- To whom correspondence should be addressed. Tel: +1 416 581 7437;
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Shakyawar S, Southekal S, Guda C. mintRULS: Prediction of miRNA–mRNA Target Site Interactions Using Regularized Least Square Method. Genes (Basel) 2022; 13:genes13091528. [PMID: 36140696 PMCID: PMC9498445 DOI: 10.3390/genes13091528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 08/19/2022] [Accepted: 08/22/2022] [Indexed: 11/16/2022] Open
Abstract
Identification of miRNA–mRNA interactions is critical to understand the new paradigms in gene regulation. Existing methods show suboptimal performance owing to inappropriate feature selection and limited integration of intuitive biological features of both miRNAs and mRNAs. The present regularized least square-based method, mintRULS, employs features of miRNAs and their target sites using pairwise similarity metrics based on free energy, sequence and repeat identities, and target site accessibility to predict miRNA-target site interactions. We hypothesized that miRNAs sharing similar structural and functional features are more likely to target the same mRNA, and conversely, mRNAs with similar features can be targeted by the same miRNA. Our prediction model achieved an impressive AUC of 0.93 and 0.92 in LOOCV and LmiTOCV settings, respectively. In comparison, other popular tools such as miRDB, TargetScan, MBSTAR, RPmirDIP, and STarMir scored AUCs at 0.73, 0.77, 0.55, 0.84, and 0.67, respectively, in LOOCV setting. Similarly, mintRULS outperformed other methods using metrics such as accuracy, sensitivity, specificity, and MCC. Our method also demonstrated high accuracy when validated against experimentally derived data from condition- and cell-specific studies and expression studies of miRNAs and target genes, both in human and mouse.
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Affiliation(s)
- Sushil Shakyawar
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Siddesh Southekal
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Chittibabu Guda
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA
- Center for Biomedical Informatics Research and Innovation (CBIRI), University of Nebraska Medical Center, Omaha, NE 68198, USA
- Correspondence:
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Vizzini A, Bonura A, La Paglia L, Fiannaca A, La Rosa M, Urso A, Mauro M, Vazzana M, Arizza V. Transcriptomic Analyses Reveal 2 and 4 Family Members of Cytochromes P450 (CYP) Involved in LPS Inflammatory Response in Pharynx of Ciona robusta. Int J Mol Sci 2021; 22:ijms222011141. [PMID: 34681801 PMCID: PMC8537429 DOI: 10.3390/ijms222011141] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 10/01/2021] [Accepted: 10/12/2021] [Indexed: 11/25/2022] Open
Abstract
Cytochromes P450 (CYP) are enzymes responsible for the biotransformation of most endogenous and exogenous agents. The expression of each CYP is influenced by a unique combination of mechanisms and factors including genetic polymorphisms, induction by xenobiotics, and regulation by cytokines and hormones. In recent years, Ciona robusta, one of the closest living relatives of vertebrates, has become a model in various fields of biology, in particular for studying inflammatory response. Using an in vivo LPS exposure strategy, next-generation sequencing (NGS) and qRT-PCR combined with bioinformatics and in silico analyses, compared whole pharynx transcripts from naïve and LPS-exposed C. robusta, and we provide the first view of cytochrome genes expression and miRNA regulation in the inflammatory response induced by LPS in a hematopoietic organ. In C. robusta, cytochromes belonging to 2B,2C, 2J, 2U, 4B and 4F subfamilies were deregulated and miRNA network interactions suggest that different conserved and species-specific miRNAs are involved in post-transcriptional regulation of cytochrome genes and that there could be an interplay between specific miRNAs regulating both inflammation and cytochrome molecules in the inflammatory response in C. robusta.
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Affiliation(s)
- Aiti Vizzini
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy; (M.M.); (M.V.); (V.A.)
- Correspondence:
| | - Angela Bonura
- Istituto per la Ricerca e l’Innovazione Biomedica-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy;
| | - Laura La Paglia
- Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Antonino Fiannaca
- Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Massimo La Rosa
- Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Alfonso Urso
- Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Manuela Mauro
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy; (M.M.); (M.V.); (V.A.)
| | - Mirella Vazzana
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy; (M.M.); (M.V.); (V.A.)
| | - Vincenzo Arizza
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche-Università di Palermo, Via Archirafi 18, 90128 Palermo, Italy; (M.M.); (M.V.); (V.A.)
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Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer. BMC Cancer 2021; 21:452. [PMID: 33892654 PMCID: PMC8063430 DOI: 10.1186/s12885-021-08166-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Accepted: 04/08/2021] [Indexed: 12/11/2022] Open
Abstract
Background Ovarian cancer (OC) is a gynecological malignancy with the highest mortality rate. Cisplatin (DDP) based chemotherapy is a standard strategy for ovarian cancer. Despite good response rates for initial chemotherapy, almost 80% of the patients treated with DDP based chemotherapy will experience recurrence due to drug-resistant, which will ultimately result in fatality. The aim of the present study was to examine the pathogenesis and potential molecular markers of cisplatin-resistant OC by studying the differential expression of mRNAs and miRNAs between cisplatin resistant OC cell lines and normal cell lines. Methods Two mRNA datasets (GSE58470 and GSE45553) and two miRNA sequence datasets (GSE58469 and GSE148251) were downloaded from the Gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were screened by the NetworkAnalyst. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. The protein-protein interaction network was constructed using STRING and Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities. FunRich and MiRNATip databases were used to identify the target genes of the DEMs. Results A total of 380 DEGs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs containing 379 nodes and 1049 edges was constructed, and 4 key modules and 24 hub genes related to cisplatin-resistant OC were screened. Two hundred ninety-nine target genes of the 5 DEMs were found out. Subsequently, one of these 299 target genes (UBB) belonging to the hub genes of GSE58470 and GSE45553 was identified by MCODE and CytoHubba,which was regulated by one miRNA (mir-454). Conclusions One miRNA–mRNA regulatory pairs (mir-454-UBB) was established. Taken together, our study provided evidence concerning the alteration genes involved in cisplatin-resistant OC, which will help to unravel the mechanisms underlying drug resistant.
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Vizzini A, Bonura A, La Paglia L, Fiannaca A, La Rosa M, Urso A, Arizza V. ceRNA Network Regulation of TGF-β, WNT, FOXO, Hedgehog Pathways in the Pharynx of Ciona robusta. Int J Mol Sci 2021; 22:ijms22073497. [PMID: 33800649 PMCID: PMC8037537 DOI: 10.3390/ijms22073497] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 03/22/2021] [Accepted: 03/25/2021] [Indexed: 12/19/2022] Open
Abstract
The transforming growth factor-β (TGF-β) family of cytokines performs a multifunctional signaling, which is integrated and coordinated in a signaling network that involves other pathways, such as Wintless, Forkhead box-O (FOXO) and Hedgehog and regulates pivotal functions related to cell fate in all tissues. In the hematopoietic system, TGF-β signaling controls a wide spectrum of biological processes, from immune system homeostasis to the quiescence and self-renewal of hematopoietic stem cells (HSCs). Recently an important role in post-transcription regulation has been attributed to two type of ncRNAs: microRNAs and pseudogenes. Ciona robusta, due to its philogenetic position close to vertebrates, is an excellent model to investigate mechanisms of post-transcriptional regulation evolutionarily highly conserved in immune homeostasis. The combined use of NGS and bioinformatic analyses suggests that in the pharynx, the hematopoietic organ of Ciona robusta, the Tgf-β, Wnt, Hedgehog and FoxO pathways are involved in tissue homeostasis, as they are in human. Furthermore, ceRNA network interactions and 3'UTR elements analyses of Tgf-β, Wnt, Hedgehog and FoxO pathways genes suggest that different miRNAs conserved (cin-let-7d, cin-mir-92c, cin-mir-153), species-specific (cin-mir-4187, cin-mir-4011a, cin-mir-4056, cin-mir-4150, cin-mir-4189, cin-mir-4053, cin-mir-4016, cin-mir-4075), pseudogenes (ENSCING00000011392, ENSCING00000018651, ENSCING00000007698) and mRNA 3'UTR elements are involved in post-transcriptional regulation in an integrated way in C. robusta.
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Affiliation(s)
- Aiti Vizzini
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche–Università di Palermo, via Archirafi 18, 90100 Palermo, Italy;
- Correspondence:
| | - Angela Bonura
- Istituto per La Ricerca e l’Innovazione Biomedica–Consiglio Nazionale Delle Ricerche, via Ugo La Malfa 153, 90100 Palermo, Italy;
| | - Laura La Paglia
- Istituto di Calcolo e Reti ad Alte Prestazioni–Consiglio Nazionale Delle Ricerche, via Ugo La Malfa 153, 90100 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Antonino Fiannaca
- Istituto di Calcolo e Reti ad Alte Prestazioni–Consiglio Nazionale Delle Ricerche, via Ugo La Malfa 153, 90100 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Massimo La Rosa
- Istituto di Calcolo e Reti ad Alte Prestazioni–Consiglio Nazionale Delle Ricerche, via Ugo La Malfa 153, 90100 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Alfonso Urso
- Istituto di Calcolo e Reti ad Alte Prestazioni–Consiglio Nazionale Delle Ricerche, via Ugo La Malfa 153, 90100 Palermo, Italy; (L.L.P.); (A.F.); (M.L.R.); (A.U.)
| | - Vincenzo Arizza
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche–Università di Palermo, via Archirafi 18, 90100 Palermo, Italy;
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Urso A, Fiannaca A, La Rosa M, La Paglia L, Lo Bosco G, Rizzo R. BITS2019: the sixteenth annual meeting of the Italian society of bioinformatics. BMC Bioinformatics 2020; 21:363. [PMID: 32938383 PMCID: PMC7493178 DOI: 10.1186/s12859-020-03708-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The 16th Annual Meeting of the Bioinformatics Italian Society was held in Palermo, Italy, on June 26-28, 2019. More than 80 scientific contributions were presented, including 4 keynote lectures, 31 oral communications and 49 posters. Also, three workshops were organised before and during the meeting. Full papers from some of the works presented in Palermo were submitted for this Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been accepted for publication in this Supplement, for a complete presentation of the outcomes of the meeting.
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Affiliation(s)
- Alfonso Urso
- ICAR-CNR, Institute for high performance computing and networking, National Research Council of Italy, Palermo, 90146, Italy.
| | - Antonino Fiannaca
- ICAR-CNR, Institute for high performance computing and networking, National Research Council of Italy, Palermo, 90146, Italy
| | - Massimo La Rosa
- ICAR-CNR, Institute for high performance computing and networking, National Research Council of Italy, Palermo, 90146, Italy
| | - Laura La Paglia
- ICAR-CNR, Institute for high performance computing and networking, National Research Council of Italy, Palermo, 90146, Italy
| | - Giosue' Lo Bosco
- Department of Mathematics and Computer Science, University of Palermo, Palermo, 90128, Italy
| | - Riccardo Rizzo
- ICAR-CNR, Institute for high performance computing and networking, National Research Council of Italy, Palermo, 90146, Italy
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Grigaitis P, Starkuviene V, Rost U, Serva A, Pucholt P, Kummer U. miRNA target identification and prediction as a function of time in gene expression data. RNA Biol 2020; 17:990-1000. [PMID: 32249661 PMCID: PMC7549638 DOI: 10.1080/15476286.2020.1748921] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 04/01/2020] [Accepted: 03/23/2020] [Indexed: 02/07/2023] Open
Abstract
The understanding of miRNA target interactions is still limited due to conflicting data and the fact that high-quality validation of targets is a time-consuming process. Faster methods like high-throughput screens and bioinformatics predictions are employed but suffer from several problems. One of these, namely the potential occurrence of downstream (i.e. secondary) effects in high-throughput screens has been only little discussed so far. However, such effects limit usage for both the identification of interactions and for the training of bioinformatics tools. In order to analyse this problem more closely, we performed time-dependent microarray screening experiments overexpressing human miR-517a-3p, and, together with published time-dependent datasets of human miR-17-5p, miR-135b and miR-124 overexpression, we analysed the dynamics of deregulated genes. We show that the number of deregulated targets increases over time, whereas seed sequence content and performance of several miRNA target prediction algorithms actually decrease over time. Bioinformatics recognition success of validated miR-17 targets was comparable to that of data gained only 12 h post-transfection. We therefore argue that the timing of microarray experiments is of critical importance for detecting direct targets with high confidence and for the usability of these data for the training of bioinformatics prediction tools.
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Affiliation(s)
- Pranas Grigaitis
- Centre for Quantitative Analysis of Molecular and Cellular Biosystems (Bioquant), Heidelberg University, Heidelberg, Germany
| | - Vytaute Starkuviene
- Centre for Quantitative Analysis of Molecular and Cellular Biosystems (Bioquant), Heidelberg University, Heidelberg, Germany
- Institute of Biosciences, Vilnius University Life Sciences Centre, Vilnius, Lithuania
| | - Ursula Rost
- Centre for Quantitative Analysis of Molecular and Cellular Biosystems (Bioquant), Heidelberg University, Heidelberg, Germany
| | - Andrius Serva
- Centre for Quantitative Analysis of Molecular and Cellular Biosystems (Bioquant), Heidelberg University, Heidelberg, Germany
| | - Pascal Pucholt
- Centre for Quantitative Analysis of Molecular and Cellular Biosystems (Bioquant), Heidelberg University, Heidelberg, Germany
| | - Ursula Kummer
- Centre for Quantitative Analysis of Molecular and Cellular Biosystems (Bioquant), Heidelberg University, Heidelberg, Germany
- Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
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Cui S, Tang J, Wang S, Li L. Kaempferol protects lipopolysaccharide-induced inflammatory injury in human aortic endothelial cells (HAECs) by regulation of miR-203. Biomed Pharmacother 2019; 115:108888. [DOI: 10.1016/j.biopha.2019.108888] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Revised: 04/16/2019] [Accepted: 04/17/2019] [Indexed: 12/12/2022] Open
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