A bunch of tiny individuals—Individual-based modeling for microbes

By F. Hellweger, V. Bucci. 2009

188 citations recorded by the source corpus.

Subfields: Ecology, Information Systems and Management, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e11dcef23b4334cea10b9d2deda7de3c25930e16

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Volker Grimm
2. Uta Berger
3. Steven F. Railsback
4. Allan E. Konopka
5. William R. Cannon
6. Alexander S. Beliaev
7. Hyun‐Seob Song
8. T. Wiegand

In Information Systems and Management

1. Allan E. Konopka
2. William R. Cannon
3. Alexander S. Beliaev
4. Hyun‐Seob Song

In Molecular Biology

1. Allan E. Konopka
2. William R. Cannon
3. Alexander S. Beliaev
4. Hyun‐Seob Song
5. Volker Grimm

Citations in the corpus

• Mathematical Modeling of Microbial Community Dynamics: A Methodological Review (2014, methodology): “Variation in the population can be accounted for by using more rigorous frameworks such as population balance model (PBM) [24] and individual-based model (IbM) [25].”
• The ODD protocol: A review and first update (2010, result): “One important result of this review was that models initially perceived as fundamentally different turned out, when their basic structure design concepts were illuminated by ODD, to be unexpectedly similar (see also Polhill et al., 2008; Hellweger and Bucci, 2009).”
• Modeling Fecal Indicator Bacteria Concentrations in Natural Surface Waters: A Review (2014, unknown): “This approach is novel in the field of FIB modeling but it has been applied in other microbial modeling contexts (Hellweger and Bucci, 2009).”