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L Boddy

Publications and source records attributed to L Boddy.

15 recordsLinked to original sources
PubMed2001

Pattern recognition in flow cytometry.

BACKGROUND: Analytical flow cytometry (AFC), by quantifying sometimes more than 10 optical parameters on cells at rates of approximately 10(3) cells/s, rapidly generates vast quantities of multidimensional data, which provides a considerable challenge for data analysis. We review the application of multivariate data analysis and pattern recognition techniques to flow cytometry. METHODS: Approaches were divided into two broad types depending on whether the aim was identification or clustering. Multivariate statistical approaches, supervised artificial neural networks (ANNs), problems of overlapping character distributions, unbounded data sets, missing parameters, scaling up, and estimating proportions of different types of cells comprised the first category. Classic clustering methods, fuzzy clustering, and unsupervised ANNs comprised the second category. We demonstrate the state of the art by using AFC data on marine phytoplankton populations. RESULTS AND CONCLUSIONS: Information held within the large quantities of data generated by AFC was tractable using ANNs, but for field studies the problem of obtaining suitable training data needs to be resolved, and coping with an almost infinite number of cell categories needs further research.

Flow Cytometry↗
PubMed2001

Comparison of five clustering algorithms to classify phytoplankton from flow cytometry data.

BACKGROUND: Artificial neural networks (ANNs) have been shown to be valuable in the analysis of analytical flow cytometric (AFC) data in aquatic ecology. Automated extraction of clusters is an important first stage in deriving ANN training data from field samples, but AFC data pose a number of challenges for many types of clustering algorithm. The fuzzy k-means algorithm recently has been extended to address nonspherical clusters with the use of scatter matrices. Four variants were proposed, each optimizing a different measure of clustering "goodness." METHODS: With AFC data obtained from marine phytoplankton species in culture, the four fuzzy k-means algorithm variants were compared with each other and with another multivariate clustering algorithm based on critical distances currently used in flow cytometry. RESULTS: One of the algorithm variants (adaptive distances, also known as the Gustafson--Kessel algorithm) was found to be robust and reliable, whereas the others showed various problems. CONCLUSIONS: The adaptive distances algorithm was superior in use to the clustering algorithms against which it was tested, but the problem of automatic determination of the number of clusters remains to be addressed.

Algorithms↗
PubMed2001

Rates and quantities of carbon flux to ectomycorrhizal mycelium following 14C pulse labeling of Pinus sylvestris seedlings: effects of litter patches and interaction with a wood-decomposer fungus.

We used a novel digital autoradiographic technique that enabled, for the first time, simultaneous visualization and quantification of spatial and temporal changes in carbon allocation patterns in ectomycorrhizal mycelia. Mycorrhizal plants of Pinus sylvestris L. were grown in microcosms containing non-sterile peat. The time course and spatial distribution of carbon allocation by P. sylvestris to mycelia of its mycorrhizal partners, Paxillus involutus (Batsch) Fr. and Suillus bovinus (L.): Kuntze, were quantified following 14C pulse labeling of the plants. Litter patches were used to investigate the effects of nutrient resource quality on carbon allocation. The wood-decomposer fungus Phanerochaete velutina (D.C.: Pers.) Parmasto was introduced to evaluate competitive and territorial interactions between its mycelial cords and the mycelial system of S. bovinus. Growth of ectomycorrhizal mycelium was stimulated in the litter patches. Nearly 60% of the C transferred from host plant to external mycorrhizal mycelium (> 2 mm from root surfaces) was allocated to mycelium in the patches, which comprised only 12% of the soil area available for mycelial colonization. Mycelia in the litter patch most recently colonized by mycorrhizal mycelium received the largest investment of carbon, amounting to 27 to 50% of the total 14C in external mycorrhizal mycelium. The amount of C transfer to external mycelium of S. bovinus following pulse labeling was reduced from a maximum of 167 nmol in systems with no saprotroph to a maximum of 61 nmol in systems interacting with P. velutina. The 14C content of S. bovinus mycelium reached a maximum 24-36 h after labeling in control microcosms, but allocation did not reach a peak until 56 h after labeling, when S. bovinus interacted with mycelium of P. velutina. The mycelium of S. bovinus contained 9% of the total 14C in the plants (including mycorrhizae) at the end of the experiment, but this was reduced to 4% in the presence of P. velutina. The results demonstrate the dynamic manner in which mycorrhizal mycelia deploy C when foraging for nutrients. The inhibitory effect of the wood-decomposer fungus P. velutina on C allocation to external mycorrhizal mycelium has important implications for nutrient cycling in forest ecosystems.

Autoradiography↗
PubMed2000

Training radial basis function neural networks: effects of training set size and imbalanced training sets.

Obtaining training data for constructing artificial neural networks (ANNs) to identify microbiological taxa is not always easy. Often, only small data sets with different numbers of observations per taxon are available. Here, the effect of both size of the training data set and of an imbalanced number of training patterns for different taxa is investigated using radial basis function ANNs to identify up to 60 species of marine microalgae. The best networks trained to discriminate 20, 40 and 60 species respectively gave overall percentage correct identification of 92, 84 and 77%. From 100 to 200 patterns per species was sufficient in networks trained to discriminate 20, 40 or 60 species. For 40 and 60 species data sets an imbalance in the number of training patterns per species always affected training success, the greater the imbalance the greater the effect. However, this could be largely compensated for by adjusting the networks using a posteriori probabilities, estimated as network output values.

Neural Networks, Computer↗
PubMed2000

Proportion estimation with confidence limits.

A common task in microbiology involves determining the composition of a mixed population of individuals by drawing a sample from the population and using some procedure to identify the individuals in the sample. There may be a significant probability that the identification procedure misidentifies some members of the sample (for example, because the available data are insufficient unambiguously to identify an individual) which makes finding the proportions in the underlying population non-trivial. A further complication arises where individuals are present in the population that do not belong to any of the subpopulations recognised by use of the identification procedure. A simple algorithm is presented to address these problems and construct a maximum likelihood estimate of the proportions, together with confidence limits. The technique is illustrated using an example drawn from flow cytometry in which phytoplankton cells are identified from flow cytometry data by an RBF neural network, and the limitations of the approach are discussed.

Confidence Intervals↗
PubMed2000

Interspecific combative interactions between wood-decaying basidiomycetes.

Competition is the most common type of interaction occurring between wood-decaying higher fungi. Since competition for nutrients in organic resources is effectively brought about by competition for space, the common division into interference and exploitation competition is not very appropriate. Fungal competition can be divided into primary resource capture (obtaining uncolonized resources) and secondary resource capture (combat to obtain resources already colonized by other fungi). Combative mechanisms include antagonism at a distance, hyphal interference, mycoparasitism and gross mycelial contact. Interactions can result in deadlock or replacement, and a hierarchy of combative ability can be discerned amongst fungi that inhabit particular resources, but within this hierarchy there exists intransitivity, modification of outcome by other species and abiotic variables. Interactions can dramatically alter mycelial function, and have potential as biological control agents of fungal pathogens of trees and in service timber.

Journal Article↗
PubMed1999

Identification of phytoplankton from flow cytometry data by using radial basis function neural networks.

We describe here the application of a type of artificial neural network, the Gaussian radial basis function (RBF) network, in the identification of a large number of phytoplankton strains from their 11-dimensional flow cytometric characteristics measured by the European Optical Plankton Analyser instrument. The effect of network parameters on optimization is examined. Optimized RBF networks recognized 34 species of marine and freshwater phytoplankton with 91. 5% success overall. The relative importance of each measured parameter in discriminating these data and the behavior of RBF networks in response to data from "novel" species (species not present in the training data) were analyzed.

Flow Cytometry↗
PubMed1998

Encounter with New Resources Causes Polarized Growth of the Cord-Forming Basidiomycete Phanerochaete velutina on Soil.

Abstract The development and physiology of cord-forming saprotrophic basidiomycetes, which form extensive and persistent mycelial networks in woodland ecosystems, can be conveniently studied on non-sterile soil in laboratory microcosms mimicking field conditions. Morphological responses of Phanerochaete velutina mycelial systems to resource encounters, and decay partitioning following encounters, varied according to whether simulated woody litter was unsterile or autoclaved and on whether encounter took place at the mycelial foraging front or behind the margin (simulating litter fall onto established systems in the field). Results show that encounter of discrete resources by P. velutina is rapidly communicated to the entire mycelial system; that resource capture takes high priority at the expense of continued system extension and decay-derived carbon reallocation; and that polarized growth toward newly encountered resources, previously considered to occur infrequently with this species, may be readily detected using image analysis techniques. Potential advantages of polarized development of P. velutina are discussed.

Journal Article↗
PubMed1996

A comparison of some neural and non-neural methods for identification of phytoplankton from flow cytometry data.

Four artificial neural network paradigms (multilayer perceptron networks, learning vector quantization networks, and radial and asymmetric basis function networks) and two statistical methods (parametric statistical classification by modelling each class with Gaussian distributions, and non-parametric density estimation via the K-nearest neighbour method) were compared for their ability to identify seven freshwater and five marine phytoplankton species from flow cytometric data. Kohonen self-organizing maps were also used to examine similarities between species. Optimized networks and statistical methods performed similarly, correctly identifying between 86.8% and 90.1% of data from freshwater species, and between 81.3% and 84.1% of data from marine species. Choice of identification technique must therefore be made on the basis of other criteria. We highlight the way each method partitions the data space and thereby separates the data clusters, and discuss the relative merits of each with reference to complexity of data boundaries, training time, analysis time and behaviour when presented with 'novel' data.

Biometry↗
PubMed1994

Effects of oxygen, pH and nitrate concentration on denitrification by Pseudomonas species.

The production of nitrogen-containing gases by denitrification in three organisms was examined using membrane inlet mass spectrometry. The effects of O2 (during both growth and maintenance) and of pH, nitrate concentration and carbon source were tested in non-proliferating cell suspensions. Two strains of Pseudomonas aeruginosa were capable of co-respiration of NO3- and O2 and, under controlled O2 supply, gave oscillatory denitrification. Variations in culture and assay conditions affected both the rate of denitrification and the ratio of end products (N2O:N2). Higher rates were seen following anaerobic growth. Optimum values of pH and nitrate concentration for denitrification are given. Generally, the optimum pH was 7.0-7.5, approximately that of the growth medium. Optimum nitrate concentration was generally 20 mM.

Acetates↗
PubMed1994

Neural network analysis of flow cytometric data for 40 marine phytoplankton species.

Flow cytometry data (time of flight, horizontal and vertical forward light scatter, 90 degrees light scatter, and "red" and "orange" integral fluorescence) were collected for laboratory cultures of 40 species of marine phytoplankton, from the following taxonomic classes, the Dinophyceae, Bacillariophyceae, Prymnesiophyceae, Cryptophyceae, and other flagellates. Single-hidden-layer "back-propagation" neural networks were trained to discriminate between species by recognising patterns in their flow cytometric signatures, and network performance was assessed using an independent test data set. Two approaches were adopted employing: (1) a hierarchy of small networks, the first identifying to which major taxonomic group a cell belonged, and then a network for that taxonomic group identified to species, and (2) a single large network. Discriminating some of the major taxonomic groups was successful but others less so. With networks for specific groups, cryptophyte species were all identified reliably (probability of correct classification always being > 0.75); in the other groups half of the species were identified reliably. With the large network, dinoflagellates, cryptomonads, and flagellates were identified almost as well as by networks specific for these groups. The application of neural computing techniques to identification of such a large number of species represents a significant advance from earlier studies, although further development is required.

Flow Cytometry↗
PubMed1994

A comparison of Radial Basis Function and backpropagation neural networks for identification of marine phytoplankton from multivariate flow cytometry data.

Two artificial neural network classifiers, the well-known Multi-layer Perception (MLP) (also known as the 'backpropagation network'), and the more recently developed Radial Basis Function (RBF) network, were evaluated and compared for their ability to identify multivariate flow cytometric data from five North Sea plankton groups (Dinoflagellidae, Bacillariophyceae, Prymnesiomonadida, Cryptomonadida, and other flagellates). RBF networks generally performed similarly to MLPs, and slightly better in cases where the data were markedly multimodal; RBF networks also have much shorter training times. The performance of MLPs was improved greatly by the use of a symmetrical bipolar 'transfer function' as opposed to the commonly-used asymmetric form. The issues of network optimisation and computational efficiency in use are discussed.

Evaluation Studies as Topic↗
PubMed1989

The effect of oxygen on denitrification in Paracoccus denitrificans and Pseudomonas aeruginosa.

Denitrification by Paracoccus denitrificans and Pseudomonas aeruginosa was studied using quadrupole membrane-inlet mass spectrometry to measure simultaneously and continuously dissolved gases. Evidence was provided for aerobic denitrification by both species: in the presence of O2, N2O production increased in Pa. denitrificans, while that of N2 decreased; with Ps. aeruginosa, the concentrations of both N2 and N2O increased on introducing O2 into the gas phase. Disappearance of NO-3 was monitored in anaerobically and aerobically grown cells which were maintained either anaerobically or aerobically: the rate and extent of NO-3 utilization by both species depended on growth and maintenance conditions. The initial rate of disappearance was most rapid under completely anaerobic conditions, and lowest rates occurred when cells were grown anaerobically and maintained aerobically. In nitrogen balance experiments both species converted over 87% of the added NO-3 to N2 and N2O under both anaerobic and aerobic maintenance conditions.

Nitrates↗