Application of back propagation artificial neural network on genetic variants in adiponectin ADIPOQ, peroxisome proliferator-activated receptor-γ, and retinoid X receptor-α genes and type 2 diabetes risk in a Chinese Han population
about
Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China.Improved glomerular filtration rate estimation by an artificial neural networkGadd45α: a novel diabetes-associated gene potentially linking diabetic cardiomyopathy and baroreflex dysfunction.Gene-Diet Interaction between SIRT6 and Soybean Intake for Different Levels of Pulse Wave Velocity.The C1431T polymorphism of peroxisome proliferator activated receptor γ (PPARγ) is associated with low risk of diabetes in a Pakistani cohortFamily-Based Association Study of rs17300539 and rs12495941 Polymorphism in Adiponectin Gene and Polycystic Ovary Syndrome in a Chinese Population.Application of the back-error propagation artificial neural network (BPANN) on genetic variants in the PPAR-γ and RXR-α gene and risk of metabolic syndrome in a Chinese Han population.Artificial Intelligence Methodologies and Their Application to Diabetes.The role of Candida albicans in the severity of multiple sclerosis.A novel approach to active compounds identification based on support vector regression model and mean impact value.Association of AdipoQ single-nucleotide polymorphisms and smoking interaction with the risk of coronary heart disease in Chinese Han population.A Novel Approach to Evaluate the Quality and Identify the Active Compounds of the Essential Oil fromCurcuma longaL
P2860
Q30406847-7F785CD3-CA5C-4FD6-879C-12385A0CB756Q30456167-BA78FA55-0E7D-490F-BE3E-7416ADB40909Q34506855-304D3533-8129-40A9-B72C-90DF74688742Q35902378-DF14D6D1-1660-45D1-8B49-74D9B3C1539CQ37251406-1C00B086-3EF2-48B3-981B-9EB321143A4EQ37588155-61846DCC-0D6E-4D8F-931F-FFE1BF0E7F93Q37669815-5637174E-D610-4525-83C3-76F2ECCEB120Q38679699-97F7693E-EFBA-42D1-B324-49FCA242B857Q50671084-0243C1BB-7969-4AB6-92F1-E77D91D3C605Q51273892-798601F0-DA3E-4007-99B4-FD7FA5807C1CQ51837258-531C21DA-FDAD-4746-8AAB-9AE41BF59591Q58285057-C2FA7EB6-E2E7-45A4-AB27-5AB66F0BF449
P2860
Application of back propagation artificial neural network on genetic variants in adiponectin ADIPOQ, peroxisome proliferator-activated receptor-γ, and retinoid X receptor-α genes and type 2 diabetes risk in a Chinese Han population
description
2011 nî lūn-bûn
@nan
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
2011年论文
@zh
2011年论文
@zh-cn
name
Application of back propagatio ...... sk in a Chinese Han population
@ast
Application of back propagatio ...... sk in a Chinese Han population
@en
type
label
Application of back propagatio ...... sk in a Chinese Han population
@ast
Application of back propagatio ...... sk in a Chinese Han population
@en
prefLabel
Application of back propagatio ...... sk in a Chinese Han population
@ast
Application of back propagatio ...... sk in a Chinese Han population
@en
P2093
P2860
P356
P1476
Application of back propagatio ...... sk in a Chinese Han population
@en
P2093
Jianhua Ma
Jinluo Cheng
Wencong Du
Xiaofang Yu
Yanqin Gao
P2860
P304
P356
10.1089/DIA.2011.0071
P577
2011-10-24T00:00:00Z