Sriram Chandrasekaran

Molecular Biology · 2010

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Sriram Chandrasekaran trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Scott A. Becker
  2. Bernhard O. Palsson
  3. Radhakrishnan Mahadevan
  4. Adam M. Feist
  5. S. Shen-Orr
  6. Ilya Shmulevich
  7. Mukesh Bansal
  8. C. Schilling
  9. Markus J. Herrgård
  10. Ren Zhang

Who trusts Sriram Chandrasekaran overall

  1. Daniel Machado
  2. Nathan E. Lewis
  3. Aarash Bordbar
  4. Koyel Mitra
  5. Markus J. Herrgård
  6. Bernhard O. Palsson
  7. Jonathan M. Monk
  8. Harish Nagarajan
  9. Anne-Ruxandra Carvunis
  10. Zachary A. King

Papers from Sriram Chandrasekaran's perspective

Ordered by how strongly the researchers Sriram Chandrasekaran trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks (Bioinform.)
  2. Genome-scale models of microbial cells: evaluating the consequences of constraints (Nature Reviews Microbiology)
  3. Regulation of gene expression in flux balance models of metabolism. (Journal of Theoretical Biology)
  4. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox (Nature Protocols)
  5. Reconstruction of Biochemical Networks in Microbial Organisms (Nature Reviews Microbiology)
  6. Network-based prediction of human tissue-specific metabolism (Nature Biotechnology)
  7. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. (Metabolic Engineering)
  8. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository (Nucleic Acids Res.)
  9. How to infer gene networks from expression profiles (Molecular Systems Biology)
  10. Integration of enzyme activities into metabolic flux distributions by elementary mode analysis (BMC Systems Biology)

Their papers