His primary areas of investigation include Bioinformatics, Biological system, Physiome, Algorithm and ATP hydrolysis. His Bioinformatics research is multidisciplinary, incorporating elements of CellML, Biophysical Phenomena, Computational biology and Documentation. His biological study spans a wide range of topics, including Conservation law, Prior information and Biochemical Phenomena.
His research in Physiome intersects with topics in Genetic profile, Torso, Breathing, Ion channel and Integrative physiology. As a part of the same scientific study, Edmund J. Crampin usually deals with the Algorithm, concentrating on Turing and frequently concerns with Pattern formation and Domain. His ATP hydrolysis research is multidisciplinary, incorporating perspectives in Active Ion Transport, Ion transporter, Sodium-Potassium-Exchanging ATPase and Membrane potential.
Edmund J. Crampin mainly investigates Biophysics, Biological system, Cell biology, Bond graph and Computational biology. His Biophysics research includes elements of Calcium, Endoplasmic reticulum, Biochemistry, Contraction and Cytosol. His work deals with themes such as Myocyte and Receptor, which intersect with Calcium.
His Biological system research is multidisciplinary, relying on both Energy consumption, Elementary reaction and Bioinformatics. His Cell biology research includes themes of Endocrinology and Keratinocyte. In his work, Inference is strongly intertwined with Gene regulatory network, which is a subfield of Computational biology.
Edmund J. Crampin spends much of his time researching Biophysics, Calcium, Bond graph, Ryanodine receptor and Statistical physics. His studies deal with areas such as ATPase, SERCA, Transporter, Nanoparticle and Membrane as well as Biophysics. Edmund J. Crampin combines subjects such as Nanotechnology, Contraction, Papillary muscle and Isometric exercise with his study of Calcium.
Computation is closely connected to Lattice in his research, which is encompassed under the umbrella topic of Statistical physics. His work in Systems biology addresses issues such as Python, which are connected to fields such as Toolchain and Software engineering. His study brings together the fields of Precision and recall and Biological system.
Biological system, Statistical physics, Lattice, Systems biology and Reaction–diffusion system are his primary areas of study. His Biological system study incorporates themes from Treatment side effects and Cell subpopulations. His Statistical physics research incorporates elements of Spatial ecology, Gating, Markov model and Calcium-induced calcium release.
Edmund J. Crampin integrates many fields, such as Lattice and engineering, in his works. The study incorporates disciplines such as Transporter, ATPase and Software engineering in addition to Systems biology. His research on Reaction–diffusion system often connects related topics like Computation.
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Minimum information requested in the annotation of biochemical models (MIRIAM)
Nicolas Le Novère;Andrew Finney;Michael Hucka;Upinder S. Bhalla.
Nature Biotechnology (2005)
Minimum information reporting in bio-nano experimental literature.
Matthew Faria;Mattias Björnmalm;Kristofer J. Thurecht;Stephen J. Kent.
Nature Nanotechnology (2018)
Reaction and Diffusion on Growing Domains: Scenarios for Robust Pattern Formation
Edmund J. Crampin;Eamonn A. Gaffney;Philip K. Maini.
Bulletin of Mathematical Biology (1999)
Computational physiology and the Physiome Project.
Edmund J. Crampin;Edmund J. Crampin;Matthew Halstead;Peter Hunter;Poul Nielsen.
Experimental Physiology (2004)
Systems Biology: An Approach
P Kohl;E J Crampin;T A Quinn;D Noble.
Clinical Pharmacology & Therapeutics (2010)
Mathematical and computational techniques to deduce complex biochemical reaction mechanisms.
E.J. Crampin;S. Schnell;P.E. McSharry.
Progress in Biophysics & Molecular Biology (2004)
Pattern formation in reaction-diffusion models with nonuniform domain growth.
E. J. Crampin;W. W. Hackborn;P. K. Maini.
Bulletin of Mathematical Biology (2002)
Minimum Information About a Simulation Experiment (MIASE)
Dagmar Waltemath;Richard R. Adams;Daniel A. Beard;Frank T. Bergmann;Frank T. Bergmann.
PLOS Computational Biology (2011)
Multiscale computational modelling of the heart
N. P. Smith;D. P. Nickerson;E. J. Crampin;P. J. Hunter.
Acta Numerica (2004)
Bioinformatics, multiscale modeling and the IUPS Physiome Project
Peter J. Hunter;Edmund J. Crampin;Poul M. F. Nielsen.
Briefings in Bioinformatics (2008)
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