On the limitations of standard statistical modeling in biological systems: A full Bayesian approach for biology

Progress in Biophysics and Molecular Biology

Volumn 113, Issue 1, 2013, Pages 80-91

  Gomez Ramirez, Jaime ^a,b   Sanz, Ricardo ^b  

^a OKAYAMA UNIVERSITY   (Japan)

^b UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Bayesian inference; Cell centric perspective; Full Bayesian approach; Inverse problem; Mathematical biology; Probability distributions conditional on biophysical information

Indexed keywords

ALGORITHM; BAYES THEOREM; BAYESIAN INFERENCE; BIOLOGICAL MODEL; BIOPHYSICS; CELL CENTRIC PERSPECTIVE; COMPUTER SIMULATION; FULL BAYESIAN APPROACH; INVERSE PROBLEM; MATHEMATICAL BIOLOGY; MATHEMATICS; METHODOLOGY; MOLECULAR BIOLOGY; PROBABILITY DISTRIBUTIONS CONDITIONAL ON BIOPHYSICAL INFORMATION; REVIEW; STATISTICAL MODEL; SYSTEM ANALYSIS; SYSTEMS BIOLOGY;

BAYESIAN INFERENCE; CELL CENTRIC PERSPECTIVE; FULL BAYESIAN APPROACH; INVERSE PROBLEM; MATHEMATICAL BIOLOGY; PROBABILITY DISTRIBUTIONS CONDITIONAL ON BIOPHYSICAL INFORMATION;

ALGORITHMS; BAYES THEOREM; BIOPHYSICS; COMPUTER SIMULATION; MATHEMATICS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MOLECULAR BIOLOGY; SYSTEMS BIOLOGY; SYSTEMS INTEGRATION;

EID: 84884984712     PISSN: 00796107     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pbiomolbio.2013.03.008     Document Type: Review

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