AIMC Topic: Plants

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Phytobial remediation advances and application of omics and artificial intelligence: a review.

Environmental science and pollution research international
Industrialization and urbanization increased the use of chemicals in agriculture, vehicular emissions, etc., and spoiled all environmental sectors. It causes various problems among living beings at multiple levels and concentrations. Phytoremediation...

Synthetic biology advances towards a bio-based society in the era of artificial intelligence.

Current opinion in biotechnology
Synthetic biology is a rapidly emerging field with broad underlying applications in health, industry, agriculture, or environment, enabling sustainable solutions for unmet needs of modern society. With the very recent addition of artificial intellige...

An intelligent model for prediction of abiotic stress-responsive microRNAs in plants using statistical moments based features and ensemble approaches.

Methods (San Diego, Calif.)
This study proposed an intelligent model for predicting abiotic stress-responsive microRNAs in plants. MicroRNAs (miRNAs) are short RNA molecules regulates the stress in genes. Experimental methods are costly and time-consuming, as compare to in-sili...

Unlocking plant bioactive pathways: omics data harnessing and machine learning assisting.

Current opinion in biotechnology
Plant bioactives hold immense potential in the medicine and food industry. The recent advancements in omics applied in deciphering specialized metabolic pathways underscore the importance of high-quality genome releases and the wealth of data in meta...

Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data.

BMC genomics
BACKGROUND: Plant specialized (or secondary) metabolites (PSM), also known as phytochemicals, natural products, or plant constituents, play essential roles in interactions between plants and environment. Although many research efforts have focused on...

ASPTF: A computational tool to predict abiotic stress-responsive transcription factors in plants by employing machine learning algorithms.

Biochimica et biophysica acta. General subjects
BACKGROUND: Abiotic stresses pose serious threat to the growth and yield of crop plants. Several studies suggest that in plants, transcription factors (TFs) are important regulators of gene expression, especially when it comes to coping with abiotic ...

Soft Robots with Plant-Inspired Gravitropism Based on Fluidic Liquid Metal.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Plants can autonomously adjust their growth direction based on the gravitropic response to maximize energy acquisition, despite lacking nerves and muscles. Endowing soft robots with gravitropism may facilitate the development of self-regulating syste...

Robotic monitoring of dunes: a dataset from the EU habitats 2110 and 2120 in Sardinia (Italy).

Scientific data
This data descriptor presents a novel dataset collected using the quadrupedal robot ANYmal C in the Mediterranean coastal dune environment of the European Union (EU) habitats 2110 and 2120 in Sardinia, Italy. The dataset mainly consists of photos, vi...

Multiple marine algae identification based on three-dimensional fluorescence spectroscopy and multi-label convolutional neural network.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Accurate identification of algal populations plays a pivotal role in monitoring seawater quality. Fluorescence-based techniques are effective tools for quickly identifying different algae. However, multiple coexisting algae and their similar photosyn...

Plant microphenotype: from innovative imaging to computational analysis.

Plant biotechnology journal
The microphenotype plays a key role in bridging the gap between the genotype and the complex macro phenotype. In this article, we review the advances in data acquisition and the intelligent analysis of plant microphenotyping and present applications ...