Results 261 to 270 of about 86,959 (305)

Resistant Peanut Genotype Reprograms Rhizosphere Metabolism to Enhance Bacterial Wilt Suppression

Advanced Science, EarlyView.
The resistant peanut genotype selectively recruits beneficial bacteria, which coincides with the activation of salicylic acid (SA)‐dependent systemic acquired resistance (SAR) against Ralstonia solanacearum. Keystone rhizosphere metabolites are positively correlated with both beneficial microbiome assembly and SAR gene expression.
Rui Ren, Xiaogang Li, Hao Li, Zenghui Cao, Mengtian Hou, Chunlei Zhao, Nan Lou, Sasa Hu, Yanzhe Li, Qian Ma, Yaoyao Li, Yi Fan, Kunkun Zhao, Kai Zhao, Ding Qiu, Fangping Gong, Zhongfeng Li, Haitao Liu, Xingli Ma, Xingxiang Wang, Dongmei Yin   +20 more
wiley   +1 more source

Exploring the predictors affecting the sense of community of Korean high school students: application of random forests and SHAP. [PDF]

Front Psychol
Jang E, Chung H.
europepmc   +1 more source

PDIA6–SCD1 Axis Rewires Lipid Metabolism to Drive Gastric Cancer Progression

Advanced Science, EarlyView.
Protein disulfide isomerase A6 (PDIA6) is identified as an oncogenic driver in gastric cancer. PDIA6 directly binds and stabilizes SCD1 by limiting its ubiquitin–proteasome‐mediated degradation, thereby sustaining monounsaturated fatty acid (MUFA)‐enriched lipid homeostasis and lipid metabolic reprogramming.
Zhen Tian, Yifan Cheng, Jiajie Zhou, Ruiqi Li, Shuai Zhao, Ben Li, Zijie Xu, Mengli Zi, Yayan Fu, Chenkai Zhang, Qiannan Sun, Shantanu Baral, Sen Wang, Daorong Wang   +13 more
wiley   +1 more source

Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests. [PDF]

Int J Med Inform
Chan LE, Casiraghi E, Reese J, Harmon QE, Schaper K, Hegde H, Valentini G, Schmitt C, Motsinger-Reif A, Hall JE, Mungall CJ, Robinson PN, Haendel MA.   +12 more
europepmc   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis

Advanced Science, EarlyView.
Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee, Jumi Kim, Taehan Yoon, So Hyun Kwon, Su Chan Park, Dohyun Chun, Dohyeong Kim, Eun Jung Park, Hyunwoo Kim, Ji Min Lee   +9 more
wiley   +1 more source

Quantifying salinity in calcareous soils through advanced spectroscopic models: A comparative study of random forests and regression techniques across diverse land use systems. [PDF]

PLoS One
Tahmoures M, Honarbakhsh A, Afzali SF, Nourzadeh Hadad M, Ostovari Y.   +4 more
europepmc   +1 more source

When do random forests fail?

, 2019
Tang, C., von Luxburg, U., Garreau, D.
core  

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On learning Random Forests for Random Forest-clustering

2020 25th International Conference on Pattern Recognition (ICPR), 2021
In this paper we study the poorly investigated problem of learning Random Forests for distance-based Random Forest clustering. We studied both classic schemes as well as alternative approaches, novel in this context. In particular, we investigated the suitability of Gaussian Density Forests [1], Random Forests specifically designed for density ...
Bicego, M, Escolano, F
openaire   +2 more sources