CMEIAS JFrad: A Digital Computing Tool to Discriminate the Fractal Geometry of Landscape Architectures and Spatial Patterns of Individual Cells in Microbial Biofilms

Zhou, Ji; Card, Kyle J.; Dazzo, Frank B.

doi:10.1007/s00248-014-0495-1

Cited by 20 publications

(26 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SEM images of 10000× magnification were subjected to 11 different mathematical methods to compute fractal dimension using CMEIAS JFrad version 1.0 software freely available at http://cme.msu.edu/cmeias/ (Ji et al 2015). The output data of melanin fractal dimensions were saved as *csv files and analysed statistically using the SYSTAT 13.…”

Section: Methodsmentioning

confidence: 99%

Purification and characterisation of a sulphur rich melanin from edible mushroom Termitomyces albuminosus Heim

2018

View full text Add to dashboard Cite

Production, purification and characterisation of a black pigment from Termitomyces albuminosus as melanin is reported, for the first time, from shaken submerged culture condition using scanning electron microscopy (SEM), elemental analysis, ultraviolet–visible (UV-VIS), and Fourier transformed infrared spectroscopy (FTIR), electron paramagnetic resonance (EPR) and 13C (CP/MAS) NMR spectra. SEM results on T. albuminosus revealed nanogranular nature of melanin nanoparticles within size range of 400–100 nm with fractal dimension D = 1.195–1.73. Elemental analysis of melanin indicated 54.6% C, 3.5% H, 2.4% N, 26.9% O, and 12% S. UV-VIS and FTIR spectra confirmed to the characteristic of melanin and were identical to the reference commercial sepia melanin. Further validation of the identity of pigment as melanin was achieved by EPR analysis. Termitomyces albuminosus melanin is postulated to be DOPA-type melanin confirmed by 13C (CP/MAS) NMR spectral analysis showing chemical shift at 200–170 ppm carbonyl, 160–110 ppm aromatic region, and with high 40–30 ppm open chain aliphatic region. Chemical modification through oxidation and cysteinylation (Pheomelanin) is implied as indicated by relatively high sulphur content (12%).

show abstract

Section: Methodsmentioning

confidence: 99%

Purification and characterisation of a sulphur rich melanin from edible mushroom Termitomyces albuminosus Heim

2018

View full text Add to dashboard Cite

show abstract

“…A nutrient shift-up perturbation in two continuously fed anaerobic bioreactors with morphologically distinct start communities was presented as an example of CMEIAS application for characterizing microbial population dynamics in ecological systems. To date, three upgraded versions of CMEIAS were published with options of color segmentation [73], quadrate maker [74] and fractal analysis [75].…”

Section: Single Cellsmentioning

confidence: 99%

Image Analysis in Microbiology: A Review

Pushchino¹

2016

JCC

View full text Add to dashboard Cite

This review is focused on using computer image analysis as a means of objective and quantitative characterizing optical images of the macroscopic (e.g. microbial colonies) and the microscopic (e.g. single cell) objects in the microbiological research. This is the way of making many visual inspection assays more objective and less time and labor consuming. Also, it can provide new visually inaccessible information on relation between some optical parameters and various biological features of the microbial cultures. Of special interest is application of image analysis in fluorescence microscopy as it opens new ways of using fluorescence based methodology for single microbial cell studies. Examples of using image analysis in the studies of both the macroscopic and the microscopic microbiological objects obtained by various imaging techniques are presented and discussed.

show abstract

“…Crossed work Besides the related work above, AM classification approaches using CBMIA methods (Dazzo and Gross 2013a, b;Dazzo and Niccum 2015;Ji et al 2015) mentioned in Sect. 2 are also involved in the EM CBMIA classification domain.…”

Section: Overview Of Em Classificationmentioning

confidence: 99%

“…3 a composite images of microbial communities in this paper is shown, showing the microorganism classification work on the 'microorganism population' level. As a further development, the AM classification system is continuously improved to enhance its functions and stability in Dazzo and Gross (2013a, b), Dazzo and Niccum (2015), Ji et al (2015).…”

Section: Overview Of Am Classificationmentioning

confidence: 99%

A survey for the applications of content-based microscopic image analysis in microorganism classification domains

Wang

2017

Artif Intell Rev

View full text Add to dashboard Cite

Microorganisms such as protozoa and bacteria play very important roles in many practical domains, like agriculture, industry and medicine. To explore functions of different categories of microorganisms is a fundamental work in biological studies, which can assist biologists and related scientists to get to know more properties, habits and characteristics of these tiny but obbligato living beings. However, taxonomy of microorganisms (microorganism classification) is traditionally investigated through morphological, chemical or physical analysis, which is time and money consuming. In order to overcome this, since the 1970s innovative content-based microscopic image analysis (CBMIA) approaches are introduced to microbiological fields. CBMIA methods classify microorganisms into different categories using multiple artificial intelligence approaches, such as machine vision, pattern recognition and machine learning algorithms. Furthermore, because CBMIA approaches are semior full-automatic computer-based methods, they are very efficient and labour cost saving, supporting a technical feasibility for microorganism classification in our current big data age. In this article, we review the development history of microorganism classification using CBMIA approaches with two crossed pipelines. In the first pipeline, all related works are grouped by their corresponding microorganism application domains. By this pipeline, it is easy for microbiologists to have an insight into each special application domain and find their interested applied CBMIA techniques. In the second pipeline, the related works in each application domain are reviewed by time periods. Using this pipeline, computer scientists can see the dynamic of technological development clearly and keep up with the future devel-

show abstract

CMEIAS JFrad: A Digital Computing Tool to Discriminate the Fractal Geometry of Landscape Architectures and Spatial Patterns of Individual Cells in Microbial Biofilms

Cited by 20 publications

References 18 publications

Purification and characterisation of a sulphur rich melanin from edible mushroom Termitomyces albuminosus Heim

Purification and characterisation of a sulphur rich melanin from edible mushroom Termitomyces albuminosus Heim

Image Analysis in Microbiology: A Review

A survey for the applications of content-based microscopic image analysis in microorganism classification domains

Contact Info

Product

Resources

About