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Cyanobacteria

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Artificial intelligence to explain the variables that favor the cyanobacteria steady-state in tropical ecosystems: A Bayeasian network approach.

Anais da Academia Brasileira de Ciencias
The steady-state is a situation of little variability of species dominance and total biomass over time. Maintenance of cyanobacteria are often observed in tropical and eutrophic ecosystems and can cause imbalances in aquatic ecosystem. Bayeasian netw...

Upflow Anaerobic Sludge Blanket Reactor Codigestion of Algae and Acetate to Produce Methane.

Water environment research : a research publication of the Water Environment Federation
  Algae grown in wastewater treatment lagoons are a potentially important substrate for biofuel production. The feasibility of using upflow anaerobic sludge blanket (UASB) reactors in anaerobic digestion of algae to produce methane was investigated. ...

Convolutional neural networks for automated annotation of cellular cryo-electron tomograms.

Nature methods
Cellular electron cryotomography offers researchers the ability to observe macromolecules frozen in action in situ, but a primary challenge with this technique is identifying molecular components within the crowded cellular environment. We introduce ...

Small Molecule Accurate Recognition Technology (SMART) to Enhance Natural Products Research.

Scientific reports
Various algorithms comparing 2D NMR spectra have been explored for their ability to dereplicate natural products as well as determine molecular structures. However, spectroscopic artefacts, solvent effects, and the interactive effect of functional gr...

A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products.

Journal of the American Chemical Society
This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural produc...

PhotoModPlus: A web server for photosynthetic protein prediction from genome neighborhood features.

PloS one
A new web server called PhotoModPlus is presented as a platform for predicting photosynthetic proteins via genome neighborhood networks (GNN) and genome neighborhood-based machine learning. GNN enables users to visualize the overview of the conserved...

Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage.

Water research
Massive cyanobacterial blooms in river water causes adverse impacts on aquatic ecosystems and water quality. Complex and diverse data sources are available to investigate the cyanobacteria phenomena, including in situ data, synthetic measurements, an...

CyanoPATH: a knowledgebase of genome-scale functional repertoire for toxic cyanobacterial blooms.

Briefings in bioinformatics
CyanoPATH is a database that curates and analyzes the common genomic functional repertoire for cyanobacteria harmful algal blooms (CyanoHABs) in eutrophic waters. Based on the literature of empirical studies and genome/protein databases, it summarize...

Simultaneous feature engineering and interpretation: Forecasting harmful algal blooms using a deep learning approach.

Water research
Routine monitoring for harmful algal blooms (HABs) is generally undertaken at low temporal frequency (e.g., weekly to monthly) that is unsuitable for capturing highly dynamic variations in cyanobacteria abundance. Therefore, we developed a model inco...

Research on Cyanobacterial-Bloom Detection Based on Multispectral Imaging and Deep-Learning Method.

Sensors (Basel, Switzerland)
Frequent outbreaks of cyanobacterial blooms have become one of the most challenging water ecosystem issues and a critical concern in environmental protection. To overcome the poor stability of traditional detection algorithms, this paper proposes a m...