E-Flux2 and SPOT: Validated Methods for Inferring Intracellular Metabolic Flux Distributions from Transcriptomic Data

Open Access

Peer-reviewed

Research Article

Min Kyung Kim,

Affiliation Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey, United States of America
⨯
Anatoliy Lane,

Affiliation Department of Computer Science, Rutgers University, Camden, New Jersey, United States of America
⨯
James J. Kelley,

Affiliation Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey, United States of America
⨯
Desmond S. Lun

* E-mail: dslun@rutgers.edu

Affiliations Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey, United States of America, Department of Computer Science, Rutgers University, Camden, New Jersey, United States of America, Department of Plant Biology and Pathology, Rutgers University, New Brunswick, Camden, New Jersey, United States of America, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia, Australia
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Saccharomyces cerevisiae
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Transcriptome analysis
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Gene expression
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Cell metabolism
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Genomics
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Optimization
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Yeast and fungal models
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Microarrays
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