James P. Sethna

Molecular Biology · 2001–2021

A researcher in the Science corpus: 9 papers; trusts 7 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom James P. Sethna trusts overall

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

  1. Mark Newman
  2. Charles H. Bennett
  3. Duncan J. Watts
  4. Philipp Koehn
  5. John C. Hull
  6. Michelle Girvan
  7. Michael B. Elowitz
  8. Steven H. Strogatz

Who trusts James P. Sethna overall

  1. Christopher R. Myers
  2. Luca Cocchi
  3. Miguel Angel Muñoz
  4. Jean-Philippe Bouchaud
  5. Sergey N. Dorogovtsev
  6. Leonardo L. Gollo
  7. Anna Deluca
  8. Ludovic Berthier
  9. Andrew Zalesky
  10. Naoki Masuda

Papers from James P. Sethna's perspective

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

  1. BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems (Nucleic Acids Res.)
  2. Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data
  3. Mechanisms of noise-resistance in genetic oscillators (Proceedings of the National Academy of Sciences of the United States of America)
  4. Prediction and validation of the distinct dynamics of transient and sustained ERK activation (Nature Cell Biology)
  5. Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. (European Journal of Biochemistry)
  6. A Systems Approach to Measuring the Binding Energy Landscapes of Transcription Factors (Science)
  7. A hybrid approach for efficient and robust parameter estimation in biochemical pathways. (Bio Systems)
  8. The Influence of Macromolecular Crowding and Macromolecular Confinement on Biochemical Reactions in Physiological Media* (Journal of Biological Chemistry)
  9. Scale invariance in plastic flow of crystalline solids
  10. Impulses and Physiological States in Theoretical Models of Nerve Membrane.

Their papers