A prognosis-related based method for miRNA selection on liver hepatocellular carcinoma prediction

Bao, 2019, Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer, Brief Bioinform Bortolomeazzi, 2017, A survey of software tools for microRNA discovery and characterization using RNA-seq, Brief. Bioinformatics, 20 Cheng, 2020, Omics Data and Artificial Intelligence: New Challenges for Gene Therapy, Curr. Gene Ther., 20, 1 Cheng, 2019, Computational and Biological Methods for Gene Therapy, Curr. Gene Ther., 19, 10.2174/156652321904191022113307 Cheng, 2018, Human Disease System Biology, Curr. Gene Ther., 18, 255, 10.2174/1566523218666181010101114 Cheng, 2020, gutMDisorder: a comprehensive database for dysbiosis of the gut microbiota in disorders and interventions, Nucleic Acids Res., 48, D554, 10.1093/nar/gkz843 Cheng, 2019, Computational methods for identifying similar diseases, Mol. Ther. Nucleic Acids, 18, 590, 10.1016/j.omtn.2019.09.019 Cheng, 2019, LncRNA2Target v2.0: a comprehensive database for target genes of lncRNAs in human and mouse, Nucleic Acids Res., 47, D140, 10.1093/nar/gky1051 Fu, 2020, StackCPPred: a stacking and pairwise energy content-based prediction of cell-penetrating peptides and their uptake efficiency, Bioinformatics, 36, 3028, 10.1093/bioinformatics/btaa131 Gong, 2019, A network embedding-based multiple information integration method for the MiRNA-disease association prediction, BMC Bioinformatics, 20, 468, 10.1186/s12859-019-3063-3 Han, 2019, LncFinder: an integrated platform for long non-coding RNA identification utilizing sequence intrinsic composition, structural information and physicochemical property, Brief. Bioinformatics, 20, 2009, 10.1093/bib/bby065 Hong, 2020, Memristive circuit implementation of biological nonassociative learning mechanism and its applications, IEEE Trans. Biomed. Circuits Syst., 10.1109/TBCAS.2020.3018777 Huang, 2020, Tensor decomposition with relational constraints for predicting multiple types of microRNA-disease associations, Brief. Bioinformatics Huo, 2020, SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso, J. Theor. Biol., 486, 10.1016/j.jtbi.2019.110098 Jeyaram, 2019, A Computational Approach to Identify Novel Potential Precursor miRNAs and their Targets from Hepatocellular Carcinoma Cells, Curr. Bioinform., 14, 24, 10.2174/1574893613666180413150351 Jiang, 2019, FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease association, BMC Genomics, 19, 11 Jiang, 2018, MDA-SKF: Similarity Kernel Fusion for Accurately Discovering miRNA-Disease Association, Front. Genet., 9 Jiang, 2013, Predicting human microRNA-disease associations based on support vector machine, Int J Data Min Bioin, 8, 282, 10.1504/IJDMB.2013.056078 Junwei, 2019, psSubpathway: a software package for flexible identification of phenotype-specific subpathways in cancer progression, Bioinformatics Li, 2020, Clinical trials, progression-speed differentiating features and swiftness rule of the innovative targets of first-in-class drugs, Brief Bioinform, 21, 649, 10.1093/bib/bby130 Li, 2017, NOREVA: normalization and evaluation of MS-based metabolomics data, Nucleic Acids Res., 45, W162, 10.1093/nar/gkx449 Liao, 2018, Cancer diagnosis through IsomiR expression with machine learning method, Curr. Bioinform., 13, 57, 10.2174/1574893611666160609081155 Liu, 2019, iPromoter-2L2.0: identifying promoters and their types by combining Smoothing cutting Window algorithm and sequence-based features, Molecular Therapy-Nucleic Acids, 18, 80, 10.1016/j.omtn.2019.08.008 Liu, 2020, sgRNA-PSM: predict sgRNAs on-target activity based on Position Specific Mismatch, Mol. Ther. €” Nucleic Acids, 20, 323, 10.1016/j.omtn.2020.01.029 Liu, 2019, BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA, and protein sequences at sequence level and residue level based on machine learning approaches, Nucleic Acids Res., 47, e127, 10.1093/nar/gkz740 Liu, 2018, An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics, Cell, 173, 10.1016/j.cell.2018.02.052 Lu, 2019, Identification of lncRNAs-gene interactions in transcription regulation based on co-expression analysis of RNA-seq data, Math. Biosci. Eng., 16, 7112, 10.3934/mbe.2019357 Marceca, 2020, MiREDiBase: a manually curated database of editing events in microRNAs, bioRxiv Müşerref, 2017, On the performance of pre-microRNA detection algorithms, Nat. Commun. Shen, 2019, Critical evaluation of web-based prediction tools for human protein subcellular localization, Brief. Bioinformatics Shen, 2019, LPI-KTASLP: Prediction of lncRNA-Protein Interaction by Semi-Supervised Link Learning with Multivariate Information, IEEE Access, 7, 13486, 10.1109/ACCESS.2019.2894225 Song, 2020, Monodirectional tissue P systems with promoters, IEEE Trans. Cybern. Sun, 2020, Identification of tumor immune infiltration-associated lncRNAs for improving prognosis and immunotherapy response of patients with non-small cell lung cancer, J. Immunother. Cancer, 8, 10.1136/jitc-2019-000110 Tang, 2018, Tumor origin detection with tissue-specific miRNA and DNA methylation markers, Bioinformatics, 34, 398, 10.1093/bioinformatics/btx622 Tang, 2020, ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies, Brief Bioinform, 21, 621, 10.1093/bib/bby127 Tomczak, 2015, The Cancer genome atlas (TCGA): an immeasurable source of knowledge, Contemp. Oncol. Pozn. (Pozn), 19, A68 Wang, 2008, Transcription factor and microRNA regulation in androgen-dependent and -independent prostate cancer cells, BMC Genomics, 9, S22, 10.1186/1471-2164-9-S2-S22 Wang, 2020, Identification of highest-affinity binding sites of yeast transcription factor families, J. Chem. Inf. Model., 60, 1876, 10.1021/acs.jcim.9b01012 Wang, 2010, Signal transducers and activators of transcription-1 (STAT1) regulates microRNA transcription in interferon gamma-stimulated HeLa cells, PLoS One, 5, 10.1371/journal.pone.0011794 Wei, 2014, Improved and promising identification of human MicroRNAs by incorporating a high-quality negative set, IEEEACM Trans. Comput. Biol. Bioinform., 11, 192, 10.1109/TCBB.2013.146 Wei, 2018, ACPred-FL: a sequence-based predictor based on effective feature representation to improve the prediction of anti-cancer peptides, Bioinformatics, 10.1093/bioinformatics/bty451 Wei, 2017, A novel hierarchical selective ensemble classifier with bioinformatics application, Artif. Intell. Med., 83, 82, 10.1016/j.artmed.2017.02.005 Wei, 2017, Improved prediction of protein–protein interactions using novel negative samples, features, and an ensemble classifier, Artif. Intell. Med., 83, 67, 10.1016/j.artmed.2017.03.001 Xu, 2019, Bioinformatics study of RNA interference on the effect of HIF-1 alpha on apelin expression in nasopharyngeal carcinoma cells, Curr. Bioinform., 14, 386, 10.2174/1574893614666190109155825 Xu, 2014, Inferring the soybean (Glycine max) microRNA functional network based on target gene network, Bioinformatics, 30, 94, 10.1093/bioinformatics/btt605 Xue, 2018, What contributes to serotonin-norepinephrine reuptake inhibitors’ dual-targeting mechanism? The key role of transmembrane domain 6 in human serotonin and norepinephrine transporters revealed by molecular dynamics simulation, ACS Chem. Neurosci., 9, 1128, 10.1021/acschemneuro.7b00490 Yan, 2020, Computational methods and applications for identifying disease-associated lncRNAs as potential biomarkers and therapeutic targets, Mol. Ther. Nucleic Acids, 21, 156, 10.1016/j.omtn.2020.05.018 Yang, 2020, Consistent gene signature of schizophrenia identified by a novel feature selection strategy from comprehensive sets of transcriptomic data, Brief Bioinform, 21, 1058, 10.1093/bib/bbz049 Yang, 2020, NOREVA: enhanced normalization and evaluation of time-course and multi-class metabolomic data, Nucleic Acids Res., 48, W436, 10.1093/nar/gkaa258 Yu, 2019, Human Pathway-Based Disease Network, IEEEACM Trans. Comput. Biol. Bioinform., 16, 1240, 10.1109/TCBB.2017.2774802 Yu, 2020, Predict new therapeutic drugs for hepatocellular carcinoma based on gene mutation and expression, Front. Bioeng. Biotechnol., 8, 8, 10.3389/fbioe.2020.00008 Yu, 2018, Predicting potential drugs for breast Cancer based on miRNA and tissue specificity, Int. J. Biol. Sci., 14, 971, 10.7150/ijbs.23350 Zeng, 2020, Target identification among known drugs by deep learning from heterogeneous networks, Chem. Sci., 11, 1775, 10.1039/C9SC04336E Zeng, 2019, Predicting disease-associated circular RNAs using deep forests combined with positive-unlabeled learning methods, Brief. Bioinformatics Zhang, 2020, Early diagnosis of hepatocellular carcinoma using machine learning method, Front. Bioeng. Biotechnol., 8, 254, 10.3389/fbioe.2020.00254 Zhang, 2019, A fast linear neighborhood similarity-based network link inference method to predict microRNA-disease associations Zhang, 2018, SFPEL-LPI: sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions, PLoS Comput. Biol., 14, 10.1371/journal.pcbi.1006616 Zhao, 2015, MicroRNA promoter identification in Arabidopsis Using multiple histone markers, Biomed Res. Int., 2015, 10.1155/2015/861402 Zhao, 2017, Methods of MicroRNA promoter prediction and transcription factor mediated regulatory network, Biomed Res. Int., 2017, 10.1155/2017/7049406 Zhao, 2020, DeepLGP: a novel deep learning method for prioritizing lncRNA target genes, Bioinformatics, 10.1093/bioinformatics/btaa428 Zhao, 2020, Wang G: ECFS-DEA: an ensemble classifier-based feature selection for differential expression analysis on expression profiles, BMC Bioinformatics, 21, 43, 10.1186/s12859-020-3388-y Zhijin Li, 2019, Integrative analysis of DNA methylation and gene expression profiles identifies MIR4435-2HG as an oncogenic lncRNA for glioma progression, Gene, 715 Zhou, 2020, Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer, Brief Bioinform Zhou, 2018, Recurrence-associated long non-coding RNA signature for determining the risk of recurrence in patients with Colon Cancer, Mol. Ther. Nucleic Acids, 12, 518, 10.1016/j.omtn.2018.06.007