A review of Cloud computing technologies for comprehensive microRNA analyses

Computational Biology and Chemistry - Tập 88 - Trang 107365 - 2020
Dariusz Mrozek1
1Department of Applied Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland

Tài liệu tham khảo

Abuín, 2015, BigBWA: approaching the Burrows-Wheeler aligner to Big Data technologies, Bioinformatics, 31, 4003, 10.1093/bioinformatics/btv506 Alessandrini, 2018, Proposed molecular and mirna classification of gastric cancer, Int. J. Mol. Sci., 19, 10.3390/ijms19061683 Backes, 2017, miRCarta: a central repository for collecting miRNA candidates, Nucleic Acids Res., 46, D160, 10.1093/nar/gkx851 Beuzelin, 2018, Exosomes and miRNA-loaded biomimetic nanovehicles, a focus on their potentials preventing type-2 diabetes linked to metabolic syndrome, Front. Immunol., 9, 2711, 10.3389/fimmu.2018.02711 Bhattacharya, 2015, SomamiR 2.0: a database of cancer somatic mutations altering microRNA-ceRNA interactions, Nucleic Acids Res., 44, D1005, 10.1093/nar/gkv1220 Bonnici, 2018, Arena-Idb: a platform to build human non-coding RNA interaction networks, BMC Bioinformatics, 19, 25, 10.1186/s12859-018-2298-8 Carlsbecker, 2010, Cell signalling by microRNA165/6 directs gene dose-dependent root cell fate, Nature, 465, 316, 10.1038/nature08977 Cheng, 2009, MicroRNA-21 protects against the H2O2-induced injury on cardiac myocytes via its target gene PDCD4, J. Mol. Cell. Cardiol., 47, 5, 10.1016/j.yjmcc.2009.01.008 Chistiakov, 2016, Cardiac-specific miRNA in cardiogenesis, heart function, and cardiac pathology (with focus on myocardial infarction), J. Mol. Cell. Cardiol., 94, 107, 10.1016/j.yjmcc.2016.03.015 Chiu, 2015, Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks, Genome Res., 25, 257, 10.1101/gr.178194.114 Chou, 2017, miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions, Nucleic Acids Res., 46, D296, 10.1093/nar/gkx1067 Dweep, 2011, miRWalk – database: prediction of possible miRNA binding sites by “walking” the genes of three genomes, J. Biomed. Informatics, 44, 839, 10.1016/j.jbi.2011.05.002 El Ouaamari, 2008, miR-375 targets 3’-phosphoinositide-dependent protein kinase-1 and regulates glucose-induced biological responses in pancreatic β-cells, Diabetes, 57, 2708, 10.2337/db07-1614 Garcia, 2011, Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs, Nat. Struct. Mol. Biol., 18, 1139, 10.1038/nsmb.2115 Ghoshal, 2018, A distributed classifier for MicroRNA target prediction with validation through TCGA expression data, IEEE/ACM Trans. Comput. Biol. Bioinformatics, 15, 1037, 10.1109/TCBB.2018.2828305 Hu, 2018, HLPI-Ensemble: prediction of human lncRNA-protein interactions based on ensemble strategy, RNA Biol., 15, 797 Iwasaki, 2013, Global microRNA elevation by inducible Exportin 5 regulates cell cycle entry, RNA, 19, 490, 10.1261/rna.036608.112 Joglekar, 2009, Expression of islet-specific microRNAs during human pancreatic development, Gene Express. Patterns, 9, 109, 10.1016/j.gep.2008.10.001 Kanellos, 2014, MR-MicroT: a MapReduce-based MicroRNA target prediction method Körner, 2013, MicroRNA-31 sensitizes human breast cells to apoptosis by direct targeting of protein kinase C epsilon (PKCepsilon), J. Biol. Chem., 288, 8750, 10.1074/jbc.M112.414128 La Torre, 2013, Conserved microRNA pathway regulates developmental timing of retinal neurogenesis, Proc. Natl. Acad. Sci. U.S.A., 110, E2362, 10.1073/pnas.1301837110 Le, 2009, Microrna-125b promotes neuronal differentiation in human cells by repressing multiple targets, Mol. Cell. Biol., 29, 5290, 10.1128/MCB.01694-08 Lee, 2012, BioVLAB-MMIA: a cloud environment for microRNA and mRNA integrated analysis (MMIA) on Amazon EC2, IEEE Trans. NanoBiosci., 11, 266, 10.1109/TNB.2012.2212030 Li, 2013, starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data, Nucleic Acids Res., 42, D92, 10.1093/nar/gkt1248 Lodygin, 2008, Inactivation of miR-34a by aberrant CpG methylation in multiple types of cancer, Cell Cycle, 7, 2591, 10.4161/cc.7.16.6533 Maragkakis, 2009, Accurate microRNA target prediction correlates with protein repression levels, BMC Bioinformatics, 10, 10.1186/1471-2105-10-295 Masseroli, 2018, Processing of big heterogeneous genomic datasets for tertiary analysis of Next Generation Sequencing data, Bioinformatics, 35, 729, 10.1093/bioinformatics/bty688 Masseroli, 2016, Modeling and interoperability of heterogeneous genomic big data for integrative processing and querying, Methods, 111, 3, 10.1016/j.ymeth.2016.09.002 Masseroli, 2015, GenoMetric Query Language: a novel approach to large-scale genomic data management, Bioinformatics, 31, 1881, 10.1093/bioinformatics/btv048 Mell, 2011 Messina, 2018, BioGraph: a web application and a graph database for querying and analyzing bioinformatics resources, BMC Syst. Biol., 12, 75, 10.1186/s12918-018-0616-4 Mrozek, 2014 Mrozek, 2018 O’Connell, 2007, MicroRNA-155 is induced during the macrophage inflammatory response, Proc. Natl. Acad. Sci. U.S.A., 104, 1604, 10.1073/pnas.0610731104 Sassen, 2008, MicroRNA-implications for cancer, Virchows Arch., 452, 10.1007/s00428-007-0532-2 Schumacher, 2013, SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop, Bioinformatics, 30, 119, 10.1093/bioinformatics/btt601 Sheikh Hassani, 2019, A semi-supervised machine learning framework for microRNA classification, Hum. Genomics, 13, 1, 10.1186/s40246-019-0221-7 Shenouda, 2009, MicroRNA function in cancer: oncogene or a tumor suppressor?, Cancer Metastasis Rev., 28, 10.1007/s10555-009-9188-5 Suksangrat, 2019, 129 Tang, 2017, Tumor origin detection with tissue-specific miRNA and DNA methylation markers, Bioinformatics, 34, 398, 10.1093/bioinformatics/btx622 Tang, 2020, LncRNA MORT inhibits cancer cell proliferation and promotes apoptosis in mantle cell lymphoma by upregulating miRNA-16, Cancer Manag. Res., 12, 2119, 10.2147/CMAR.S233859 Trobaugh, 2017, MicroRNA regulation of RNA virus replication and pathogenesis, Trends Mol. Med., 23, 80, 10.1016/j.molmed.2016.11.003 Ueda, 2010, Relation between microRNA expression and progression and prognosis of gastric cancer: a microRNA expression analysis, Lancet Oncol., 11, 136, 10.1016/S1470-2045(09)70343-2 Verjans, 2017, MiRNA deregulation in cardiac aging and associated disorders, 207, 10.1016/bs.ircmb.2017.03.004 Vienberg, 2017, MicroRNAs in metabolism, Acta Physiol., 219, 346, 10.1111/apha.12681 Wang, 2020, MiR-23b functions as an oncogenic miRNA by downregulating Mcl-1S in lung cancer cell line A549, J. Biochem. Mol. Toxicol., e22494, 10.1002/jbt.22494 Wu, 2019, MirLibSpark: a scalable NGS plant MicroRNA prediction pipeline for multi-library functional annotation, 669 Wu, 2020, Non-coding RNAs and their role in respiratory syncytial virus (RSV) and human metapneumovirus (hMPV) infections, Viruses, 12, 10.3390/v12030345 Yang, 2010, starBase: a database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data, Nucleic Acids Res., 39, D202, 10.1093/nar/gkq1056 Zeng, 2015, Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks, Brief. Bioinformatics, 17, 193, 10.1093/bib/bbv033 Zheng, 2019, MLMDA: a machine learning approach to predict and validate MicroRNA-disease associations by integrating of heterogenous information sources, J. Transl. Med., 17, 1, 10.1186/s12967-019-2009-x Zou, 2016, Multiple sequence alignment and reconstructing phylogenetic trees with Hadoop, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 10.1109/BIBM.2016.7822492 Zou, 2013, Survey of MapReduce frame operation in bioinformatics, Brief. Bioinformatics, 15, 637, 10.1093/bib/bbs088 Zou, 2016, HPTree: reconstructing phylogenetic trees for ultra-large unaligned DNA sequences via NJ model and Hadoop, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 53, 10.1109/BIBM.2016.7822492