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In theory, the combination of mathematical modeling with experimental studies can be a powerful and compelling approach to understanding cell biology. In practice, choosing appropriate problems, identifying willing and able collaborators, and publishing the resulting research can be remarkably challenging. To provide perspective on the question of whether and when to combine modeling and experiments, a panel of experts at the 2010 ASCB Annual Meeting shared their personal experiences and advice on how to use modeling effectively.
Peer Review, Research, Peer Review, Research, Bioinformatics and Computational Biology, Cell Biology, Biological Sciences, Congresses as Topic, Models, Theoretical, Biological, Medical and Health Sciences, Meeting Review, Models, Biological, Theoretical, Models, Research Design, Biochemistry and cell biology, Developmental Biology
Peer Review, Research, Peer Review, Research, Bioinformatics and Computational Biology, Cell Biology, Biological Sciences, Congresses as Topic, Models, Theoretical, Biological, Medical and Health Sciences, Meeting Review, Models, Biological, Theoretical, Models, Research Design, Biochemistry and cell biology, Developmental Biology
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |