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Journal Abstract Search

304 related items for PubMed ID: 31757198

  • 1. MetaCon: unsupervised clustering of metagenomic contigs with probabilistic k-mers statistics and coverage.
    Qian J, Comin M.
    BMC Bioinformatics; 2019 Nov 22; 20(Suppl 9):367. PubMed ID: 31757198
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  • 3. MetaProb 2: Metagenomic Reads Binning Based on Assembly Using Minimizers and K-Mers Statistics.
    Andreace F, Pizzi C, Comin M.
    J Comput Biol; 2021 Nov 22; 28(11):1052-1062. PubMed ID: 34448593
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  • 5. COCACOLA: binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment and paired-end read LinkAge.
    Lu YY, Chen T, Fuhrman JA, Sun F.
    Bioinformatics; 2017 Mar 15; 33(6):791-798. PubMed ID: 27256312
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  • 7. Binning Metagenomic Contigs Using Unsupervised Clustering and Reference Databases.
    Jiang Z, Li X, Guo L.
    Interdiscip Sci; 2022 Dec 15; 14(4):795-803. PubMed ID: 35639335
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  • 8. SolidBin: improving metagenome binning with semi-supervised normalized cut.
    Wang Z, Wang Z, Lu YY, Sun F, Zhu S.
    Bioinformatics; 2019 Nov 01; 35(21):4229-4238. PubMed ID: 30977806
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  • 9. Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes.
    Lin HH, Liao YC.
    Sci Rep; 2016 Apr 12; 6():24175. PubMed ID: 27067514
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  • 10. METAMVGL: a multi-view graph-based metagenomic contig binning algorithm by integrating assembly and paired-end graphs.
    Zhang Z, Zhang L.
    BMC Bioinformatics; 2021 Jul 22; 22(Suppl 10):378. PubMed ID: 34294039
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  • 11. Accurate Binning of Metagenomic Contigs Using Composition, Coverage, and Assembly Graphs.
    Mallawaarachchi V, Lin Y.
    J Comput Biol; 2022 Dec 22; 29(12):1357-1376. PubMed ID: 36367700
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  • 12. GraphBin: refined binning of metagenomic contigs using assembly graphs.
    Mallawaarachchi V, Wickramarachchi A, Lin Y.
    Bioinformatics; 2020 Jun 01; 36(11):3307-3313. PubMed ID: 32167528
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  • 14. BMC3C: binning metagenomic contigs using codon usage, sequence composition and read coverage.
    Yu G, Jiang Y, Wang J, Zhang H, Luo H.
    Bioinformatics; 2018 Dec 15; 34(24):4172-4179. PubMed ID: 29947757
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  • 15. Evaluating metagenomics tools for genome binning with real metagenomic datasets and CAMI datasets.
    Yue Y, Huang H, Qi Z, Dou HM, Liu XY, Han TF, Chen Y, Song XJ, Zhang YH, Tu J.
    BMC Bioinformatics; 2020 Jul 28; 21(1):334. PubMed ID: 32723290
    [Abstract] [Full Text] [Related]

  • 16. Binning metagenomic contigs by coverage and composition.
    Alneberg J, Bjarnason BS, de Bruijn I, Schirmer M, Quick J, Ijaz UZ, Lahti L, Loman NJ, Andersson AF, Quince C.
    Nat Methods; 2014 Nov 28; 11(11):1144-6. PubMed ID: 25218180
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  • 17. Unsupervised Binning of Metagenomic Assembled Contigs Using Improved Fuzzy C-Means Method.
    Liu Y, Hou T, Kang B, Liu F.
    IEEE/ACM Trans Comput Biol Bioinform; 2017 Nov 28; 14(6):1459-1467. PubMed ID: 27295684
    [Abstract] [Full Text] [Related]

  • 18. Estimating the total genome length of a metagenomic sample using k-mers.
    Hua K, Zhang X.
    BMC Genomics; 2019 Apr 04; 20(Suppl 2):183. PubMed ID: 30967110
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  • 19. MetaCRS: unsupervised clustering of contigs with the recursive strategy of reducing metagenomic dataset's complexity.
    Jiang Z, Li X, Guo L.
    BMC Bioinformatics; 2022 Jan 20; 22(Suppl 12):315. PubMed ID: 35045830
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  • 20. Classification of metagenomic sequences: methods and challenges.
    Mande SS, Mohammed MH, Ghosh TS.
    Brief Bioinform; 2012 Nov 20; 13(6):669-81. PubMed ID: 22962338
    [Abstract] [Full Text] [Related]

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