AIMC Topic: Plants

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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 ...

Gramene 2018: unifying comparative genomics and pathway resources for plant research.

Nucleic acids research
Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,...

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

GigaScience
The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses...

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

GigaScience
In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation...

The plant perceptron connects environment to development.

Nature
Plants cope with the environment in a variety of ways, and ecological analyses attempt to capture this through life-history strategies or trait-based categorization. These approaches are limited because they treat the trade-off mechanisms that underl...