AIMC Topic: Plants

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Multi-Target Deep Learning for Algal Detection and Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Water quality has a direct impact on industry, agriculture, and public health. Algae species are common indicators of water quality. It is because algal communities are sensitive to changes in their habitats, giving valuable knowledge on variations i...

Deep Residual Neural Networks Resolve Quartet Molecular Phylogenies.

Molecular biology and evolution
Phylogenetic inference is of fundamental importance to evolutionary as well as other fields of biology, and molecular sequences have emerged as the primary data for this task. Although many phylogenetic methods have been developed to explicitly take ...

Machine learning and its applications in plant molecular studies.

Briefings in functional genomics
The advent of high-throughput genomic technologies has resulted in the accumulation of massive amounts of genomic information. However, biologists are challenged with how to effectively analyze these data. Machine learning can provide tools for bette...

An Overview on Predicting Protein Subchloroplast Localization by using Machine Learning Methods.

Current protein & peptide science
The chloroplast is a type of subcellular organelle of green plants and eukaryotic algae, which plays an important role in the photosynthesis process. Since the function of a protein correlates with its location, knowing its subchloroplast localizatio...

PVsiRNAPred: Prediction of plant exclusive virus-derived small interfering RNAs by deep convolutional neural network.

Journal of bioinformatics and computational biology
Plant exclusive virus-derived small interfering RNAs (vsiRNAs) regulate various biological processes, especially important in antiviral immunity. The identification of plant vsiRNAs is important for understanding the biogenesis and function mechanism...

NetGO: improving large-scale protein function prediction with massive network information.

Nucleic acids research
Automated function prediction (AFP) of proteins is of great significance in biology. AFP can be regarded as a problem of the large-scale multi-label classification where a protein can be associated with multiple gene ontology terms as its labels. Bas...

Computational aspects underlying genome to phenome analysis in plants.

The Plant journal : for cell and molecular biology
Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promisi...

Effects of Plant Species, Insecticide, and Exposure Time On the Efficacy Of Barrier Treatments Against .

Journal of the American Mosquito Control Association
The effect of 5 plant species (arborvitae [], boxwood [ sp., Japanese honeysuckle [], rhododendron [ sp.], and zebra grass []) and 2 rates of lambda-cyhalothrin (3.13 ml and 6.25 ml active ingredient [AI]/liter) on knockdown (1 h) and mortality (24 h...

Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Classification of plants based on a multi-organ approach is very challenging. Although additional data provide more information that might help to disambiguate between species, the variability in shape and appearance in plant organs also raises the d...

microRPM: a microRNA prediction model based only on plant small RNA sequencing data.

Bioinformatics (Oxford, England)
MOTIVATION: MicroRNAs (miRNAs) are endogenous non-coding small RNAs (of about 22 nucleotides), which play an important role in the post-transcriptional regulation of gene expression via either mRNA cleavage or translation inhibition. Several machine ...