AIMC Topic: Stress, Physiological

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Identification of biomarker genes from multiple studies for abiotic stress in maize through machine learning.

Journal of biosciences
Abiotic stresses are major limiting factors for maize growth. Therefore, exploration of the mechanisms underlying the response to abiotic stress in maize is of great interest. Toward this end, we performed integration of the feature selection method ...

High-throughput image segmentation and machine learning approaches in the plant sciences across multiple scales.

Emerging topics in life sciences
Agriculture has benefited greatly from the rise of big data and high-performance computing. The acquisition and analysis of data across biological scales have resulted in strategies modeling inter- actions between plant genotype and environment, mode...

Collective dynamics in entangled worm and robot blobs.

Proceedings of the National Academy of Sciences of the United States of America
Living systems at all scales aggregate in large numbers for a variety of functions including mating, predation, and survival. The majority of such systems consist of unconnected individuals that collectively flock, school, or swarm. However, some agg...

Prediction of condition-specific regulatory genes using machine learning.

Nucleic acids research
Recent advances in genomic technologies have generated data on large-scale protein-DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has bec...

Ultra-gentle soft robotic fingers induce minimal transcriptomic response in a fragile marine animal.

Current biology : CB
Tessler et al. demonstrate that a 'soft' robot causes less stress to a jellyfish while handling compared to a traditional 'hard' robot.

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...

Combined multivariate analysis and machine learning reveals a predictive module of metabolic stress response in Arabidopsis thaliana.

Molecular omics
Abiotic stress exposure of plants induces metabolic reprogramming which is tightly regulated by signalling cascades connecting transcriptional with translational and metabolic regulation. Complexity of such interconnected metabolic networks impedes t...

Association between 4-day vaginal temperature assessment during the dry period and performance in the subsequent lactation of dairy cows during the warm season.

Journal of animal science
The objective of the study was to investigate the relationships between vaginal temperature during the dry-period and health, milk production, and reproduction in the subsequent lactation of cows during the warm season. A total of 105 nonlactating Ho...