What is principal component analysis?

Ringnér, Markus

doi:10.1038/nbt0308-303

Cited by 1,697 publications

(1,082 citation statements)

References 11 publications

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“…These principal components represent the largest possible variance in a data set that is then limited to the most relevant parameters, therefore increasing the interpretability of complex data 10. Principal component analysis suggested that the dimensionality of the current cohort could be reduced to 3 dominant principal components that accounted for 56% of variability among women for the characteristics assessed.…”

Section: Resultsmentioning

confidence: 99%

Phenotypes of Pregnant Women Who Subsequently Develop Hypertension in Pregnancy

McLaughlin

Zhang

Lye

et al. 2018

JAHA

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BackgroundHypertensive disorders complicating pregnancy are a major cause of maternal death. Our objective was to evaluate maternal clinical, hemodynamic, and placental prognostic indicators in a consolidated manner to identify women who develop hypertension in pregnancy.Methods and ResultsTwenty‐six normotensive pregnant women from a specialized Placenta Clinic at increased risk of developing de novo hypertension and 20 normotensive healthy pregnant controls were recruited at 22 to 26 weeks' gestation. Fourteen maternal clinical, hemodynamic, and placental characteristics were assessed in the second trimester and aggregated. Principal component analysis of this combined data set determined that 3 dimensions accounted for 56% of the cohort variability. The first dimension accounted for 31% of the cohort variability, with significant contributions from total peripheral resistance, endoglin, and cardiac output. The second dimension was predominantly influenced by body mass index and mean arterial pressure, while uric acid and myeloperoxidase mainly contributed to the third dimension. Unsupervised clustering identified 3 groups within this combined data set. Total peripheral resistance was the most significant distinguishing parameter between these groups (P<0.0001), followed by placental growth factor, endoglin, and cardiac output (P<0.0001). Using these 4 parameters, a receiver operating curve was constructed with an area under the curve of 0.975 (95% confidence interval 0.93–1) for the prediction of developing hypertension in pregnancy.ConclusionsConsolidated assessment of prognostic indicators in the second trimester of pregnancy may be useful to characterize and distinguish pathways by which women may develop hypertension in pregnancy. This approach could contribute to the development of pathway‐specific preventative and antihypertensive treatment strategies.

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Section: Resultsmentioning

confidence: 99%

Phenotypes of Pregnant Women Who Subsequently Develop Hypertension in Pregnancy

McLaughlin

Zhang

Lye

et al. 2018

JAHA

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“…Here, a 2:1 MUX is designed and performed based on DNA hybridization ( Figure 1c). A molecular beacon (MB) labeled with FAM and Dabcyl at each terminus is designed as the original platform, which produces weak or strong FAM fluorescence depending on its closed or open state, 27,28 serving as the signal output. FAM fluorescence is set as the only readout signal.…”

Section: Resultsmentioning

confidence: 99%

DNA-based advanced logic circuits for nonarithmetic information processing

Liu

Dong

et al. 2015

NPG Asia Mater

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DNA has been used as a building block to construct a series of complex logic circuits to perform nonarithmetic functions, including a multiplexer, demultiplexer, encoder and decoder. This is the first time that DNA has been used to cover this broad range of logic circuits, demonstrating the versatility and power of DNA computation to process information on the molecular level. The above logic circuits all share the same DNA platform, indicating the great prospects for DNA computation. The enzyme-free system developed here provides a novel prototype for the design of DNA-based, high-level molecular logic circuits. Considering its biocompatibility, DNA computation could find potential applications in biological and biomedical fields in the not-too-distant future.

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“…The first few components can be interpreted as the direction, which represents the maximum variance of the samples. 50 Within the top eigenvectors, the first two eigenvectors accounted for a significant amount of overall motion in wt β2m and D59P. Each eigenvector has a corresponding eigenvalue, which describes the energetic involvement of each component to the motion.…”

Section: Ef Loop (Phe70-glu77)mentioning

confidence: 99%

Assessing the effect of D59P mutation in the DE loop region in amyloid aggregation propensity of β2‐microglobulin: A molecular dynamics simulation study

Narang

Shuaib

Goyal

2017

J of Cellular Biochemistry

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Dialysis-related amyloidosis (DRA) is a severe condition characterized by the accumulation of amyloidogenic β2-microglobulin (β2m) protein around skeletal joints and bones. The recent studies highlighted a critical role of the DE loop region for β2m stability and amyloid aggregation propensity. Despite significant efforts, the molecular mechanism of enhanced aggregation due to D59P mutation in the DE loop region remain elusive. In the present study, explicit-solvent molecular dynamics (MD) simulations were performed to examine the key changes in the structural and dynamic properties of wild type (wt) β2m upon D59P mutation. MD simulations reveal a decrease in the average number of hydrogen bonds in the loop regions on D59P mutation that enhances conformational flexibility, which lead to higher aggregation propensity of D59P as compare to wt β2m. The principal component analysis (PCA) highlight that D59P covers a larger region of phase space and display a higher trace value than wt β2m, which suggest an overall enhancement in the conformational flexibility. D59P display two minimum energy basins in the free energy landscape (FEL) that are associated with thermodynamically less stable conformational states as compare to single minimum energy basin in wt β2m. The present study provides theoretical insights into the molecular mechanism behind the higher aggregation propensity of D59P as compare to wt β2m. K E Y W O R D Samyloid aggregation, β2-microglobulin, D59P mutation, DE loop, molecular dynamics

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What is principal component analysis?

Cited by 1,697 publications

References 11 publications

Phenotypes of Pregnant Women Who Subsequently Develop Hypertension in Pregnancy

Phenotypes of Pregnant Women Who Subsequently Develop Hypertension in Pregnancy

DNA-based advanced logic circuits for nonarithmetic information processing

Assessing the effect of D59P mutation in the DE loop region in amyloid aggregation propensity of β2‐microglobulin: A molecular dynamics simulation study

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