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5 results for “seed learning”
Quantification of Fatty Acids in Hemp Seeds (Cannabis sativa L.) and Yield Prediction Using Machine Learning for Soxhlet and Ultrasound Extraction Methods
<p>This study focuses on the quantification of fatty acids present in hemp seeds (Cannabis sativa L.) cultivated in the Ecuadorian Andes using Soxhlet and ultrasound extraction methods. The aim is to evaluate and compare the extraction efficiency of these two techniques. Furthermore, machine learning models are applied to predict extraction yields based on experimental conditions. Using locally cultivated seeds provides valuable insights into the influence of regional agro-climatic conditions on the chemical composition. The integration of predictive algorithms offers a novel approach to optimizing the extraction process, enhancing both precision and efficiency. The findings could contribute to developing sustainable extraction methods for high-value bioactive compounds in the food and pharmaceutical industries.</p>
Ab initio design of microbial communities from large-scale seed pools using deep learning and rapid ptimization
<h4>This repository contains the full results of our paper: <strong><em>Ab initio</em> design of microbial communities from large-scale seed pools using deep learning and rapid ptimization.</strong></h4> <p>Authors: Xiaoqing Jiang#, Jiaheng Hou#, Haoyu Zhang#, Jinyuan Guo, Shaohua Gu, Yulin Liao, Xinrun Yang, Peter X. Geng, Yiyan Zhou, Qian Guo, Chunhui Wang, Mo Li, Alexandre Jousset, Zhong Wei*, and Huaiqiu Zhu*</p> <p>The results including:</p> <p><strong>(1)</strong> <strong>GEM.tar.gz</strong>: The eBiota-GEM dataset, containing 21,514 Genome-Scale Metabolic Models (GEMs) constructed using CarveMe based on RefSeq complete genomes.</p> <p><strong>(2) Baterial_evaluation.tar.gz</strong>: The evaluation of the ability to uptake substrates and secret productions for all 21,514 GEMs.</p> <p><strong>(3) Community_results.tar.gz</strong>: The results calculated from eBiota-GEM includes various combinations for two-bacterial consortia, covering strain IDs, substrates, products, yields, dual-bacterial growth, single-bacterial growth, co-occurrence predictions, interactions and total production.</p> <p><strong>(4) DeepCooc_files.tar.gz</strong>: The parameter files of DeepCooc, required by eBiota platform.</p>
The reliability of environmental cues shapes learning and selection against deleterious alleles in seed beetles
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To Seed or Not to Seed? An Empirical Analysis of Usage of Seeds for Testing in Machine Learning Projects
<p>This contains the experimental dataset for our paper: "To Seed or Not to Seed? An Empirical Analysis of Usage of Seeds for Testing<br> in Machine Learning Projects" published at ICST 2022. Go to <a href="https://github.com/uiuc-arc/xseed">Github</a> for more details.</p>
Identification of Key Genes for seed germination of Astragalus Mongolicus using WGCNA and machine Learning methods
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.