AIMC Topic: Fungi

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Automation and artificial intelligence in filamentous fungi-based bioprocesses: A review.

Bioresource technology Nov 30, 2022
By utilizing their powerful metabolic versatility, filamentous fungi can be utilized in bioprocesses aimed at achieving circular economy. With the current digital transformation within the biomanufacturing sector, the interest of automating fungi-bas...
Humans Reproducibility of Results Fungi Automation Artificial Intelligence Technology
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Sequential endoscopic and robot-assisted surgical solutions for a rare fungal spondylodiscitis, secondary lumbar spinal stenosis, and subsequent discal pseudocyst causing acute cauda equina syndrome: a case report.

BMC surgery Jan 29, 2022
BACKGROUND: Fungal spondylodiscitis is a rare infectious disease. The secondary lumbar spinal stenosis and postoperative discal pseudocyst were even rarer. The surgical interventions were disputed, yet endoscopic and robot-assisted techniques may be ...
Humans Female Pedicle Screws Cauda Equina Syndrome Discitis Middle Aged Lumbar Vertebrae Fungi Robotics Spinal Stenosis
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Automatic Fungi Recognition: Deep Learning Meets Mycology.

Sensors (Basel, Switzerland) Jan 14, 2022
The article presents an AI-based fungi species recognition system for a citizen-science community. The system's real-time identification too - FungiVision - with a mobile application front-end, led to increased public interest in fungi, quadrupling t...
Fungi Mycology Deep Learning Mobile Applications Humans Neural Networks, Computer
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Deep learning-based quantification of arbuscular mycorrhizal fungi in plant roots.

The New phytologist Sep 16, 2021
Soil fungi establish mutualistic interactions with the roots of most vascular land plants. Arbuscular mycorrhizal (AM) fungi are among the most extensively characterised mycobionts to date. Current approaches to quantifying the extent of root colonis...
Plant Roots Fungi Symbiosis Deep Learning Mycorrhizae Glomeromycota Lotus
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The design and application of an automated microscope developed based on deep learning for fungal detection in dermatology.

Mycoses Dec 7, 2020
BACKGROUND: Light microscopy to study the infection of fungi in skin specimens is time-consuming and requires automation.
Hair Microscopy, Fluorescence Skin Microscopy Nails Sensitivity and Specificity Fungi Humans Deep Learning Automation, Laboratory Image Processing, Computer-Assisted
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Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Journal of bioinformatics and computational biology Oct 29, 2020
Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an environment. Specific fragments in the DNA sequence of a living organism have been defined as DNA ba...
Animals Birds Algorithms DNA Barcoding, Taxonomic Support Vector Machine Chiroptera Rodentia Phylogeny Databases, Genetic Classification Ferns Deep Learning Fungi
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Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Biomolecules Sep 28, 2020
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...
Fungi Databases, Chemical Bacteria Biological Products Area Under Curve Machine Learning ROC Curve
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Deep learning approach to describe and classify fungi microscopic images.

PloS one Jun 30, 2020
Preliminary diagnosis of fungal infections can rely on microscopic examination. However, in many cases, it does not allow unambiguous identification of the species due to their visual similarity. Therefore, it is usually necessary to use additional b...
Support Vector Machine Deep Learning Fungi Image Processing, Computer-Assisted Microscopy
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Its2vec: Fungal Species Identification Using Sequence Embedding and Random Forest Classification.

BioMed research international May 27, 2020
Fungi play essential roles in many ecological processes, and taxonomic classification is fundamental for microbial community characterization and vital for the study and preservation of fungal biodiversity. To cope with massive fungal barcode data, t...
DNA Barcoding, Taxonomic DNA, Fungal Computational Biology Fungi Machine Learning Algorithms Software
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Optimization of fungi co-fermentation for improving anthraquinone contents and antioxidant activity using artificial neural networks.

Food chemistry Jan 7, 2020
The fermentation products of edible fungi are rich in anthraquinones and have a variety of activities, including the antioxidant activity. Because of the large number of combinations, it is very difficult to obtain the optimal multi-strains co-fermen...
Neural Networks, Computer Algorithms Reproducibility of Results Anthraquinones Fermentation Industrial Microbiology Antioxidants Fungi
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