Demo Data from EDBT 2026 / reviewers in the wild / expert
Jan-Hendrik S. Hofmeyr
dblp:20/5942
· DBLP profile ↗
7ranked-venue papers
3as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 7 · 3 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
7 papers |
Bioinformatics and computational biology · 94% Computational science and engineering · 6% Computing education · 0% |
Topics — the 11 heaviest of 14, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology › metabolic network analysis
metabolic control analysis |
0.3 | 4 | 2018 | PySCeSToolbox: a collection of metabolic pathway analysis tools · Bioinform. 2018 MetaModel: a program for modelling and control analysis of metabolic pathways on the IBM PC and compatibles · Comput. Appl. Biosci. 1991 The reversible Hill equation: how to incorporate cooperative enzymes into metabolic models · Comput. Appl. Biosci. 1997 |
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
metabolic pathway analysis |
0.3 | 1 | 2018 | PySCeSToolbox: a collection of metabolic pathway analysis tools · Bioinform. 2018 |
Bioinformatics and computational biology
systems biology |
0.2 | 5 | 2018 | PySCeSToolbox: a collection of metabolic pathway analysis tools · Bioinform. 2018 The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models · Bioinform. 2003 The reversible Hill equation: how to incorporate cooperative enzymes into metabolic models · Comput. Appl. Biosci. 1997 |
Bioinformatics and computational biology › systems biology › computational cell biology
cell simulation |
0.1 | 1 | 2005 | Modelling cellular systems with PySCeS · Bioinform. 2005 |
Bioinformatics and computational biology › systems biology › computational cell biology
cellular modeling |
0.1 | 1 | 2005 | Modelling cellular systems with PySCeS · Bioinform. 2005 |
Bioinformatics and computational biology › systems biology
kinetic modeling |
0.1 | 1 | 2005 | Modelling cellular systems with PySCeS · Bioinform. 2005 |
Computational science and engineering
numerical analysis |
0.1 | 1 | 2005 | Modelling cellular systems with PySCeS · Bioinform. 2005 |
Bioinformatics and computational biology › systems biology
model exchange format |
0.0 | 1 | 2003 | The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models · Bioinform. 2003 |
Bioinformatics and computational biology › systems biology
enzyme kinetics |
0.0 | 1 | 1997 | The reversible Hill equation: how to incorporate cooperative enzymes into metabolic models · Comput. Appl. Biosci. 1997 |
Bioinformatics and computational biology › systems biology
metabolic modeling |
0.0 | 1 | 1997 | The reversible Hill equation: how to incorporate cooperative enzymes into metabolic models · Comput. Appl. Biosci. 1997 |
Bioinformatics and computational biology › systems biology › metabolic modeling
metabolic pathway modeling |
0.0 | 3 | 1991 | MetaModel: a program for modelling and control analysis of metabolic pathways on the IBM PC and compatibles · Comput. Appl. Biosci. 1991 METAMOD: software for steady-state modelling and control analysis of metabolic pathways on the BBC microcomputer · Comput. Appl. Biosci. 1986 Steady-state modelling of metabolic pathways: a guide for the prospective simulator · Comput. Appl. Biosci. 1986 |
Methods — techniques the papers use, named apart from their topics
symbolic control analysis · 0.3supply-demand analysis · 0.3numerical simulation · 0.1XML · 0.0reversible hill equation · 0.0monod-wyman-changeux model · 0.0adair equation · 0.0elasticity coefficients · 0.0control coefficients · 0.0computer simulation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | PySCeSToolbox: a collection of metabolic pathway analysis toolsabstractSummary: PySCeSToolbox is an extension to the Python Simulator for Cellular Systems (PySCeS) that includes tools for performing generalized supply-demand analysis, symbolic metabolic control analysis, and a framework for investigating the kinetic and thermodynamic aspects of enzyme-catalyzed reactions. Each tool addresses a different aspect of metabolic behaviour, control, and regulation; the tools complement each other and can be used in conjunction to better understand higher level system behaviour. Availability and implementation: PySCeSToolbox is available on Linux, Mac OS X and Windows. It is licensed under the BSD 3-clause licence. Code, setup instructions and a link to documentation can be found at https://github.com/PySCeS/PyscesToolbox. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online. Carl D. Christensen, Jan-Hendrik S. Hofmeyr, Johann M. Rohwer |
Bioinform. | 2 |
| 2005 | Modelling cellular systems with PySCeSabstractUNLABELLED: The Python Simulator for Cellular Systems (PySCeS) is an extendable research tool for the numerical analysis and investigation of cellular systems. AVAILABILITY: PySCeS is distributed as Open Source Software under the GNU General Public Licence and is available for download from http://pysces.sourceforge.net CONTACT: [email protected]. Brett G. Olivier, Johann M. Rohwer, Jan-Hendrik S. Hofmeyr |
Bioinform. | 3 |
| 2003 | The systems biology markup language (SBML): a medium for representation and exchange of biochemical network modelsabstractMOTIVATION: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY: The specification of SBML Level 1 is freely available from http://www.sbml.org/ Michael Hucka, Andrew Finney, Herbert M. Sauro, H. Bolouri, John Doyle 0001, Hiroaki Kitano, Adam P. Arkin, Benjamin J. Bornstein, Dennis Bray, Athel Cornish-Bowden, Autumn A. Cuellar, Serge Dronov, Ernst Dieter Gilles, Martin Ginkel, Victoria Gor, Igor Goryanin, W. J. Hedley, Charlie Hodgman, Jan-Hendrik S. Hofmeyr, Peter J. Hunter, Nick S. Juty, J. L. Kasberger, Andreas Kremling, Ursula Kummer, Nicolas Le Novère, Leslie M. Loew, D. Lucio, Pedro Mendes 0001, E. Minch, Eric Mjolsness, Yoichi Nakayama, M. R. Nelson, Poul M. F. Nielsen, T. Sakurada, James C. Schaff, Bruce E. Shapiro, Thomas Simon Shimizu, Hugh D. Spence, Jörg Stelling, Koichi Takahashi, Masaru Tomita |
Bioinform. | 19 |
| 1997 | The reversible Hill equation: how to incorporate cooperative enzymes into metabolic modelsabstractMOTIVATION: Realistic simulation of the kinetic properties of metabolic pathways requires rate equations to be expressed in reversible form, because substrate and product elasticities are drastically different in reversible and irreversible reactions. This presents no special problem for reactions that follow reversible Michaelis-Menten kinetics, but for enzymes showing cooperative kinetics the full reversible rate equations are extremely complicated, and anyway in virtually all cases the full equations are unknown because sufficiently complete kinetic studies have not been carried out. There is a need, therefore, for approximate reversible equations that allow convenient simulation without violating thermodynamic constraints. RESULTS: We show how the irreversible Hill equation can be generalized to a reversible form, including effects of modifiers. The proposed equation leads to behaviour virtually indistinguishable from that predicted by a kinetic form of the Adair equation, despite the fact that the latter is a far more complicated equation. By contrast, a reversible form of the Monod-Wyman-Changeux equation that has sometimes been used leads to predictions for the effects of modifiers at high substrate concentration that differ qualitatively from those given by the Adair equation. Jan-Hendrik S. Hofmeyr, Athel Cornish-Bowden |
Comput. Appl. Biosci. | 1 |
| 1991 | MetaModel: a program for modelling and control analysis of metabolic pathways on the IBM PC and compatiblesabstractMetaModel is a user-friendly program for calculating steady-state fluxes and metabolite concentrations of metabolic systems on the IBM PC and compatible computers. For any steady state that is obtained, one can then calculate a matrix of elasticity coefficients at that steady state, or a matrix of control and response coefficients. It thus offers a simple way to calculate the control structure of a pathway: it provides not only an educational tool that allows the student to verify empirically the classic summation relationships of metabolic control analysis but also a research tool for addressing 'what if?' questions about the behaviour of metabolic systems. Results can not only be printed or stored in a file, but can also be written to a special file that can be read by popular spreadsheet programs, thereby giving access to rapid, flexible and powerful methods for subsequent analysis and plotting of these results. Athel Cornish-Bowden, Jan-Hendrik S. Hofmeyr |
Comput. Appl. Biosci. | 2 |
| 1986 | Steady-state modelling of metabolic pathways: a guide for the prospective simulatorabstractSteady-state modelling and control analysis by means of computer simulation provides valuable insight into the behavior of metabolic pathways. This review, which is aimed at the newcomer to this field, discusses the objectives of steady-state modelling and the steady-state properties of the four basic metabolic structures, namely linear and branched chains, loops and cycles. It is shown how the model definition in terms of stoichiometric reactions and rate equations leads to a set of balance equations from which the conservation constraints and flux relationships can be deduced, either informally or through a rigorous analysis of the stoichiometric matrix. The initial analysis of a steady-state metabolic model is summarized in an algorithm. Key references to the literature on metabolic modelling are given. Jan-Hendrik S. Hofmeyr |
Comput. Appl. Biosci. | 1 |
| 1986 | METAMOD: software for steady-state modelling and control analysis of metabolic pathways on the BBC microcomputerabstractMETAMOD, a BBC microcomputer-based software package for steady-state modelling and control analysis of model metabolic pathways, is described, The package consists of two programs. METADEF allows the user to define the pathway in terms of reactions, rate equations and initial concentrations of metabolites. METACAL uses one of two algorithms to calculate the steady-state concentrations and fluxes. One algorithm uses the current ratio of production and consumption rates of variable metabolites to adjust iteratively their concentrations in such a way that they converge towards the steady state. The other algorithm solves the roots of the system equations by means of a quasi-Newtonian procedure. Control analysis allows the calculation of elasticity, control and response coefficients, by means of finite difference approximation. METAMOD is interactive and easy to use, and suitable for teaching and research purposes. Jan-Hendrik S. Hofmeyr, K. J. van der Merwe |
Comput. Appl. Biosci. | 1 |