Predicting microbial growth: graphical methods for comparing models.

N Bratchell; P J McClure; T M Kelly; T A Roberts

doi:10.1016/0168-1605(90)90021-v

Home/Archive/PubMed

PubMed · 2282286

Predicting microbial growth: graphical methods for comparing models.

N Bratchell·P J McClure·T M Kelly·T A Roberts

View original source ↗Export metadata ↓

Abstract

Some simple computer-based graphics were used to compare different models predicting microbial growth responses of salmonellae to three factors (pH, sodium chloride concentration and incubation temperature). Simple linear regression, contour and three-dimensional surface plots all revealed gross differences between the predicted growth parameters from different growth models. Regression and contour plots were found to be more sensitive to small differences in surface topography, but three-dimensional surface plots provided a good overview.

Explore related subjects

Computer Graphics Food Microbiology Hydrogen-Ion Concentration Models, Biological Regression Analysis Salmonella Sodium Chloride Temperature Comparative Study Journal Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

N Bratchell, P J McClure, T M Kelly, T A Roberts. 1990. Predicting microbial growth: graphical methods for comparing models.. https://doi.org/10.1016/0168-1605(90)90021-v

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed1998

EcoCyc: Encyclopedia of Escherichia coli genes and metabolism.

The encyclopedia of Escherichia coli genes and metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of E.coli. The database describes 3030 genes of E.coli , 695 enzymes encoded by a subset of these genes, 595 metabolic reactions that occur in E.coli, and the organization of these reactions into 123 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc can be thought of as an electronic review article because of its copious references to the primary literature, and as a (qualitative) computational model of E.coli metabolism. EcoCyc is available at URL http://ecocyc.PangeaSystems.com/ecocyc/

Computer Graphics↗

PubMed1997

NUCPLOT: a program to generate schematic diagrams of protein-nucleic acid interactions.

Proteins that bind to DNA are found in all areas of genetic activity within the cell. To help understand how these proteins perform their various functions, it is useful to analyse which residues are involved in binding to the DNA and how they interact with the bases and sugar-phosphate backbone of nucleic acids. Here we describe a program called NUCPLOT which can automatically identify these interactions from the 3D atomic coordinates of the complex from a PDB file and generate a plot that shows all the interactions in a schematic manner. The program produces a PostScript output file representing hydrogen, van der Waals and covalent bonds between the protein and the DNA. The resulting diagram is both clear and simple and allows immediate identification of important interactions within the structure. It also facilitates comparison of binding found in different structures. NUCPLOT is a completely automatic program, which can be used for any protein-DNA complex and will also work for certain protein-RNA structures.

Computer Graphics↗

PubMed1997

Identification of synaptic connections in neural ensembles by graphical models.

A method for the identification of direct synaptic connections in a larger neural net is presented. It is based on a conditional correlation graph for multivariate point processes. The connections are identified via the partial spectral coherence of two neurons, given all others. It is shown how these coherences can be calculated by inversion of the spectral density matrix. In simulations with GENESIS, we discuss the relevance of the method for identifying different neural ensembles including an excitatory feedback loop and networks with lateral inhibitions.

Computer Graphics↗