An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

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An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features. is …
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scholarly articleQ13442814

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P356DOI10.1039/C7MB00234C
P698PubMed publication ID28671706

P50authorAbhishek SubramanianQ41581829
Ram Rup SarkarQ57563256
Sutanu NandiQ88437725
P2093author name stringRam Rup Sarkar
Sutanu Nandi
Abhishek Subramanian
P2860cites workGenBankQ21056874
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Uncovering major genomic features of essential genes in Bacteria and a methanogenic ArchaeaQ35666678
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Flux coupling analysis of genome-scale metabolic network reconstructions.Q40497938
A comprehensive genome-scale reconstruction of Escherichia coli metabolism--2011.Q40519259
Experimental and computational assessment of conditionally essential genes in Escherichia coliQ41063583
The organisational structure of protein networks: revisiting the centrality-lethality hypothesisQ41859361
Removal of a ribosome small subunit-dependent GTPase confers salt resistance on Escherichia coli cellsQ41860035
Update on the Keio collection of Escherichia coli single-gene deletion mutantsQ42912234
β-Ketoacyl-Acyl Carrier Protein Synthase III (FabH) Is Essential for Bacterial Fatty Acid SynthesisQ44605232
Gene essentiality prediction based on fractal features and machine learning.Q45948672
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Comparison of codon usage bias across Leishmania and Trypanosomatids to understand mRNA secondary structure, relative protein abundance and pathway functionsQ46719404
Escherichia coli transcriptome dynamics during the transition from anaerobic to aerobic conditionsQ50722060
Comparative analysis of essential genes and nonessential genes in Escherichia coli K12.Q54432611
Escherichia coli di-iron YtfE protein is necessary for the repair of stress-damaged iron-sulfur clusters.Q54447064
Global gene expression in Escherichia coli K-12 during short-term and long-term adaptation to glucose-limited continuous culture conditions.Q54462408
Gene Selection for Cancer Classification using Support Vector MachinesQ56535529
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P433issue8
P921main subjectEscherichia coliQ25419
machine learningQ2539
P304page(s)1584-1596
P577publication date2017-07-01
P1433published inMolecular BioSystemsQ3319467
P1476titleAn integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features
P478volume13

Reverse relations

cites work (P2860)
Q48507473Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling
Q91796642Machine and deep learning meet genome-scale metabolic modeling
Q90044983ePath: an online database towards comprehensive essential gene annotation for prokaryotes

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