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Improving contig binning of metagenomic data using \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {d}_2^S $$\end{document}d2S oligonucleotide frequency dissimilarity
Improving contig binning of metagenomic data using \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {d}_2^S $$\end{document}d2S oligonucleotide frequency dissimilarity
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Improving contig binning of metagenomic data using \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {d}_2^S $$\end{document}d2S oligonucleotide frequency dissimilarity

Wang, Ying ; Wang, Kun ; Lu, Yang Young ; Sun, Fengzhu

BMC bioinformatics, 2017-09, Vol.18 [Periódico revisado por pares]

London: BioMed Central

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2
Minimum redundancy maximum relevance feature selection approach for temporal gene expression data
Minimum redundancy maximum relevance feature selection approach for temporal gene expression data
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Minimum redundancy maximum relevance feature selection approach for temporal gene expression data

Radovic, Milos ; Ghalwash, Mohamed ; Filipovic, Nenad ; Obradovic, Zoran

BMC bioinformatics, 2017-01, Vol.18 (1), p.9-9, Article 9 [Periódico revisado por pares]

England: BioMed Central Ltd

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3
The effects of multiple features of alternatively spliced exons on the KA/KS ratio test
The effects of multiple features of alternatively spliced exons on the KA/KS ratio test
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The effects of multiple features of alternatively spliced exons on the KA/KS ratio test

Chen, Feng-Chi ; Chuang, Trees-Juen

BMC bioinformatics, 2006-05, Vol.7 (1), p.259-259 [Periódico revisado por pares]

London: BioMed Central Ltd

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4
Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-κB signaling-induced gene expression responses in inflammation
Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-κB signaling-induced gene expression responses in inflammation
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Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-κB signaling-induced gene expression responses in inflammation

Peng, Shih Chi ; Wong, David Shan Hill ; Tung, Kai Che ; Chen, Yan Yu ; Chao, Chun Cheih ; Peng, Chien Hua ; Chuang, Yung Jen ; Tang, Chuan Yi

BMC bioinformatics, 2010-06, Vol.11 (1), p.308-308, Article 308 [Periódico revisado por pares]

BioMed Central Ltd

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5
Reference-guided de novo assembly approach improves genome reconstruction for related species
Reference-guided de novo assembly approach improves genome reconstruction for related species
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Reference-guided de novo assembly approach improves genome reconstruction for related species

Lischer, Heidi E L ; Shimizu, Kentaro K

BMC bioinformatics, 2017-11, Vol.18 (1), p.474-474, Article 474 [Periódico revisado por pares]

England: BioMed Central Ltd

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6
TelomereHunter - in silico estimation of telomere content and composition from cancer genomes
TelomereHunter - in silico estimation of telomere content and composition from cancer genomes
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TelomereHunter - in silico estimation of telomere content and composition from cancer genomes

Feuerbach, Lars ; Sieverling, Lina ; Deeg, Katharina I ; Ginsbach, Philip ; Hutter, Barbara ; Buchhalter, Ivo ; Northcott, Paul A ; Mughal, Sadaf S ; Chudasama, Priya ; Glimm, Hanno ; Scholl, Claudia ; Lichter, Peter ; Fröhling, Stefan ; Pfister, Stefan M ; Jones, David T W ; Rippe, Karsten ; Brors, Benedikt

BMC bioinformatics, 2019-05, Vol.20 (1), p.272-272, Article 272 [Periódico revisado por pares]

England: BioMed Central Ltd

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7
Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network
Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network
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Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network

Li, Ying ; Sun, Hang ; Feng, Shiyao ; Zhang, Qi ; Han, Siyu ; Du, Wei

BMC bioinformatics, 2021-05, Vol.22 (1), p.246-246, Article 246 [Periódico revisado por pares]

England: BioMed Central Ltd

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8
Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison
Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison
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Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison

Vicar, Tomas ; Balvan, Jan ; Jaros, Josef ; Jug, Florian ; Kolar, Radim ; Masarik, Michal ; Gumulec, Jaromir

BMC bioinformatics, 2019-06, Vol.20 (1), p.360-25, Article 360 [Periódico revisado por pares]

England: BioMed Central

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9
iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data
iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data
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iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data

Ge, Steven Xijin ; Son, Eun Wo ; Yao, Runan

BMC bioinformatics, 2018-12, Vol.19 (1), p.534-24, Article 534 [Periódico revisado por pares]

England: BioMed Central Ltd

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10
DrImpute: imputing dropout events in single cell RNA sequencing data
DrImpute: imputing dropout events in single cell RNA sequencing data
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DrImpute: imputing dropout events in single cell RNA sequencing data

Gong, Wuming ; Kwak, Il-Youp ; Pota, Pruthvi ; Koyano-Nakagawa, Naoko ; Garry, Daniel J

BMC bioinformatics, 2018-06, Vol.19 (1), p.220-220, Article 220 [Periódico revisado por pares]

England: BioMed Central Ltd

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