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TranscriptomicsMulti-level Support Vector Regression analysis to identify condition-specific regulatory networks
The identification of gene regulatory modules is an important yet challenging problem in computational biology. While many computational methods have been proposed to identify regulatory modules, their initial success is largely compromised by a high rate of false positives, especially when applied...
ORGANISM(S): Homo sapiens 
2010-03-23 | E-GEOD-20700 | biostudies-arrayexpress
TranscriptomicsMulti-level Support Vector Regression analysis to identify condition-specific regulatory networks
The identification of gene regulatory modules is an important yet challenging problem in computational biology. While many computational methods have been proposed to identify regulatory modules, their initial success is largely compromised by a high rate of false positives, especially when applied ...
ORGANISM(S): Homo sapiens 
2010-03-10 | GSE20700 | GEO
MetabolomicsCoupled Mass-Spectrometry-Based Lipidomics Machine Learning Approach for Early Detection of Clear Cell Renal Cell Carcinoma

A discovery-based lipid profiling study of serum samples from a cohort that included patients with clear cell Renal Cell Carcinoma (ccRCC) stage I, II, III, and IV (n=112) and controls (n=52) was performed using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spec...

2020-11-20 | MTBLS1839 | MetaboLights
UnknownVisual Analysis of Odor Interaction Based on Support Vector Regression Method.
Not available
S-EPMC7146738 | biostudies-literature
UnknownMulti-level Support Vector Regression analysis to identify condition-specific regulatory networks
Not available
ORGANISM(S): Homo sapiens 
S-ECPF-GEOD-20700 | biostudies-other
GenomicsHomo sapiens
Multi-level Support Vector Regression analysis to identify condition-specific regulatory networks
PRJNA124893 | ENA
UnknownSequential Support Vector Regression with Embedded Entropy for SNP Selection and Disease Classification.
Not available
S-EPMC3110013 | biostudies-literature
UnknownPredicting residue-wise contact orders in proteins by support vector regression.
Not available
S-EPMC1618864 | biostudies-literature
UnknownMultilevel support vector regression analysis to identify condition-specific regulatory networks.
Not available
S-EPMC2872001 | biostudies-literature
UnknownComparing logistic regression, support vector machines, and permanental classification methods in predicting hypertension.
Not available
S-EPMC4143639 | biostudies-literature
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