| 1. |
- Gennemark, Peter, 1974, et al.
(författare)
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ODEion- a software module for structural identification of ordinary differential equations
- 2014
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Ingår i: Journal of Bioinformatics and Computational Biology. - 0219-7200 .- 1757-6334. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- In the systems biology field, algorithms for structural identification of ordinary differential equations (ODEs) have mainly focused on fixed model spaces like S-systems and/or on methods that require sufficiently good data so that derivatives can be accurately estimated. There is therefore a lack of methods and software that can handle more general models and realistic data. We present ODEion, a software module for structural identification of ODEs. Main characteristic features of the software are: • The model space is defined by arbitrary user-defined functions that can be nonlinear in both variables and parameters, such as for example chemical rate reactions. • ODEion implements computationally efficient algorithms that have been shown to efficiently handle sparse and noisy data. It can run a range of realistic problems that previously required a supercomputer. • ODEion is easy to use and provides SBML output. We describe the mathematical problem, the ODEion system itself, and provide several examples of how the system can be used. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219720013500157
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| 2. |
- Kattas, G.D., et al.
(författare)
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Structural identification of GMA models: Algorithm and model comparison
- 2010
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Ingår i: CMSB 2010 - Proceedings of the 8th International Conference on Computational Methods in Systems Biology. - New York, NY, USA : ACM. - 9781450300681 ; , s. 107-113
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Konferensbidrag (refereegranskat)abstract
- We propose a local search algorithm for structural identification of Generalized Mass Action (GMA) models from time course data. The algorithm has been implemented as part of our existing system for identification of dynamical systems. We compare this approach to existing alternatives in terms of analytical GMA models, analytical GMA models with parameter estimation from time course data, S-systems, and linear models. This is done on three new test problems designed to exhibit different characteristic properties of biochemical pathways, and which are defined with chemical rate reactions. By applying state-of-the-art algorithmic methods we are able to make a full investigation for the test problems also with noisy data. The results show that on the tested problems, our structural identification algorithm is able to find as good or better models than any of the other approaches. It can therefore be expected to be a useful tool for identifying models of unknown systems from time course data. All test problems are available on the web. Copyright 2010 ACM.
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| 3. |
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| 4. |
- Wedelin, Dag, 1964
(författare)
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Revisiting the in-the-middle algorithm and heuristic for integer programming and the max-sum problem
- 2013
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- We consider a very simple algorithm to solve large scale 0-1 integer linear programs - and a simple heuristic to encourage convergence to an integer so- lution - which have been very successful in commercial applications. We find it useful to revisit its main ideas and establish its relation to several known algorithms, including the generalized iterative scaling algorithm. We discuss ways to relate this linear programming based approach to the max-sum prob- lem, and show that the algorithm has a close relation to convergent message passing algorithms for MAP-inference in graphical models such as max-sum diffusion. We further discuss non-conflicting and conflicting max-sum con- straint updates, show that the two algorithms match with these concepts, and that the heuristic has a relation to the max-sum algorithm. We finally give a brief overview of known applications, including a commercial system for airline crew scheduling.
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| 5. |
- Wedelin, Dag, 1964, et al.
(författare)
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Teaching and learning mathematical modelling and problem solving: A case study
- 2013
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Ingår i: 1st International Conference of the Portuguese-Society-for-Engineering-Education (CISPEE), November 2013, Porto, Portugal. - 9781479912193
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Konferensbidrag (refereegranskat)abstract
- Engineering students often fail to connect and apply what they have learnt in introductory mathematics courses to other subjects, sometimes leading to the belief that mathematics is not relevant to them. To bridge this gap between mathematical theory and practice, we have designed a course in mathematical modelling and problem solving at Chalmers University of Technology. The main purpose of the present study is to investigate and better understand what challenges engineering students experience when dealing with mathematical modelling problems and what strategies they use to overcome those challenges. Data was collected through semistructured interviews with six students early in the course and the interviews were based on two problems that the students had solved during the course. The data was analysed using basic strategies for qualitative analysis and led to the identification of two central challenges experienced by the students as well as several strategies for overcoming them. The first challenge is that students are not fully aware of the importance of understanding the problem, and the second is that students get stuck because they do not sufficiently consider alternatives in a non-linear solution process. While these issues have little to do with mathematical modelling as such, the modelling problems given clearly reveal these shortcomings, which we see as lacking problem solving skills. Our findings confirm the importance of teaching mathematical modelling and problem solving, and in a more general setting we see cognitive apprenticeship as a promising framework for teaching and learning in engineering education.
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| 6. |
- Wedelin, Dag, 1964, et al.
(författare)
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Teaching Mathematical Modelling and Problem Solving - A Cognitive Apprenticeship Approach to Mathematics and Engineering Education
- 2014
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Ingår i: International Journal of Engineering Pedagogy. - 2192-4880. ; 4:5, s. 49-55
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Tidskriftsartikel (refereegranskat)abstract
- We describe a course in mathematical modelling and problem solving, intended to provide the students with the appropriate skills to deal with real world problems in science and technology. The course is inquiry-based and centered around approximately 30 reasonably realistic, highly varied and challenging problems, which are solved in pairs. The students are supervised in a cognitive apprentice- ship environment, where the teacher uses a range of tech- niques to align student thinking with expert thinking. After taking the course, most students express and demonstrate a fundamental change in their abilities to think mathematical- ly, in their understanding of the nature of mathematics and its role in their future profession. They also consider it as one of the most important courses in their education. We therefore argue that this kind of course, or similar teaching, should be present in the engineering curriculum.
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