AIMC Topic: Plant Proteins
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Deep Learning Enhances Precision of Citrullination Identification in Human and Plant Tissue Proteomes.
Molecular & cellular proteomics : MCP
Feb 5, 2025
Citrullination is a critical yet understudied post-translational modification (PTM) implicated in various biological processes. Exploring its role in health and disease requires a comprehensive understanding of the prevalence of this PTM at a proteom...
Feedback regulation of mA modification creates local auxin maxima essential for rice microsporogenesis.
Developmental cell
Jan 13, 2025
N-methyladenosine (mA) RNA modification and its effectors control various plant developmental processes, yet whether and how these effectors are transcriptionally controlled to confer functional specificity so far remain elusive. Herein, we show that...
Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models.
Sensors (Basel, Switzerland)
Jan 7, 2025
Wheat is a globally cultivated cereal crop with substantial protein content present in its seeds. This research aimed to develop robust methods for predicting seed protein concentration in wheat seeds using bench-top hyperspectral imaging in the visi...
Machine learning discovery of novel antihypertensive peptides from highland barley protein inhibiting angiotensin I-converting enzyme (ACE).
Food research international (Ottawa, Ont.)
Jan 6, 2025
Hypertension is a major global health concern, and there is a need for new antihypertensive agents derived from natural sources. This study aims to identify novel angiotensin I-converting enzyme (ACE) inhibitors from bioactive peptides derived from f...
Increased chloroplast occupancy in bundle sheath cells of rice hap3H mutants revealed by Chloro-Count: a new deep learning-based tool.
The New phytologist
Dec 12, 2024
There is an increasing demand to boost photosynthesis in rice to increase yield potential. Chloroplasts are the site of photosynthesis, and increasing their number and size is a potential route to elevate photosynthetic activity. Notably, bundle shea...
Barley Grain Proteome Assessment Using Multi-Environment Trial Data and Machine Learning.
Journal of agricultural and food chemistry
Nov 13, 2024
Proteomics can be used to assess individual protein abundances, which could reflect genotypic and environmental effects and potentially predict grain/malt quality. In this study, 79 barley grain samples (genotype-location-year combinations) from Cali...
ProTformer: Transformer-based model for superior prediction of protein content in lablab bean (Lablab purpureus L.) using Near-Infrared Reflectance spectroscopy.
Food research international (Ottawa, Ont.)
Oct 1, 2024
Lablab bean (Lablab purpureus L.), known for its higher protein content provides a promising alternative to reduce reliance on animal-based proteins and support sustainable agriculture. Nowadays, traditional methods for nutritional profiling have bee...
Plant-based egg washes for use in baked goods: Machine learning and visual parameter analysis.
Journal of food science
Sep 27, 2024
Pea protein is one potential environmentally sustainable way of recreating the functionality of eggs in coatings for baked goods. These coatings are commonly applied to enhance visual properties of baked goods that consumers desire, especially color ...
Fusion of convolutional neural network with XGBoost feature extraction for predicting multi-constituents in corn using near infrared spectroscopy.
Food chemistry
Aug 31, 2024
Near-infrared (NIR) spectroscopy has been widely utilized to predict multi-constituents of corn in agriculture. However, directly extracting constituent information from the NIR spectra is challenging due to many issues such as broad absorption band,...
Using AlphaFold Multimer to discover interkingdom protein-protein interactions.
The Plant journal : for cell and molecular biology
Aug 17, 2024
Structural prediction by artificial intelligence can be powerful new instruments to discover novel protein-protein interactions, but the community still grapples with the implementation, opportunities and limitations. Here, we discuss and re-analyse ...
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