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PubMed Journals Articles About "Most Efficient Convergent Principal Component Analysis Method Data" RSS

21:47 EDT 24th June 2019 | BioPortfolio

Most Efficient Convergent Principal Component Analysis Method Data PubMed articles on BioPortfolio. Our PubMed references draw on over 21 million records from the medical literature. Here you can see the latest Most Efficient Convergent Principal Component Analysis Method Data articles that have been published worldwide.

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Showing "Most Efficient Convergent Principal Component Analysis Method Data" PubMed Articles 1–25 of 58,000+

HisCoM-GGI: Software for Hierarchical Structural Component Analysis of Gene-Gene Interactions.

Gene-gene interaction (GGI) analysis is known to play an important role in explain missing heritability issue. Many previous studies have already proposed software to analyze GGI, but most methods focus on a binary phenotype in case-control design. In this study, we developed 'Hierarchical structural CoMponent analysis of Gene-Gene Interactions' (HisCoM-GGI) software for gene-gene interaction analysis with a continuous phenotype. The HisCoM-GGI method considers hierarchical structural relationships between ...


A tessellation-based colocalization analysis approach for single-molecule localization microscopy.

Multicolor single-molecule localization microscopy (λSMLM) is a powerful technique to reveal the relative nanoscale organization and potential colocalization between different molecular species. While several standard analysis methods exist for pixel-based images, λSMLM still lacks such a standard. Moreover, existing methods only work on 2D data and are usually sensitive to the relative molecular organization, a very important parameter to consider in quantitative SMLM. Here, we present an efficient, para...

Robust method for detecting convergent shifts in evolutionary rates.

Identifying genomic elements underlying phenotypic adaptations is an important problem in evolutionary biology. Comparative analyses learning from convergent evolution of traits are gaining momentum in accurately detecting such elements. We previously developed a method for predicting phenotypic associations of genetic elements by contrasting patterns of sequence evolution in species showing a phenotype with those that do not. Using this method, we successfully demonstrated convergent evolutionary rate shif...


The Iterative Convergent Design for Mobile Health Usability Testing: Mixed-Methods Approach.

Although patients express an interest in using mobile health (mHealth) interventions to manage their health and chronic conditions, many current mHealth interventions are difficult to use. Usability testing is critical for the success of novel mHealth interventions. Researchers recognize the utility of using qualitative and quantitative approaches for usability testing, but many mHealth researchers lack the awareness of integration approaches from advances in mixed-methods research that can add value to mHe...

Joint Principal Component and Discriminant Analysis for Dimensionality Reduction.

Linear discriminant analysis (LDA) is the most widely used supervised dimensionality reduction approach. After removing the null space of the total scatter matrix St via principal component analysis (PCA), the LDA algorithm can avoid the small sample size problem. Most existing supervised dimensionality reduction methods extract the principal component of data first, and then conduct LDA on it. However, ``most variance'' is very often the most important, but not always in PCA. Thus, this two-step strategy m...

Sparse Principal Component Analysis with Preserved Sparsity Pattern.

Principal component analysis (PCA) is widely used for feature extraction and dimension reduction in pattern recognition and data analysis. Despite its popularity, the reduced dimension obtained from PCA is difficult to interpret due to the dense structure of principal loading vectors. To address this issue, several methods have been proposed for sparse PCA, all of which estimate loading vectors with few non-zero elements. However, when more than one principal component is estimated, the associated loading v...

ParStream-seq: An improved method of handling next generation sequence data.

The exponential growth of next generation sequence (NGS) data has put forward the challenge for its storage as well as its efficient and faster analysis. Storing the entire amount of data for a particular experiment and its alignment to the reference genome is an essential step for any quantitative analysis on NGS data. Here, we introduce streaming access technique 'ParStream-seq' that splits the bulk sequence data, accessed from a remote repository into short manageable packets followed by executing their ...

Two-dimensional local Fourier image reconstruction via domain decomposition Fourier continuation method.

The MRI image is obtained in the spatial domain from the given Fourier coefficients in the frequency domain. It is costly to obtain the high resolution image because it requires higher frequency Fourier data while the lower frequency Fourier data is less costly and effective if the image is smooth. However, the Gibbs ringing, if existent, prevails with the lower frequency Fourier data. We propose an efficient and accurate local reconstruction method with the lower frequency Fourier data that yields sharp im...

Analyzing dwell times with the Generalized Method of Moments.

The Generalized Method of Moments (GMM) is a statistical method for the analysis of samples from random processes. First developed for the analysis of econometric data, the method is here formulated to extract hidden kinetic parameters from measurements of single molecule dwell times. Our method is based on the analysis of cumulants of the measured dwell times. We develop a general form of an objective function whose minimization can return estimates of decay parameters for any number of intermediates direc...

Generic gas chromatography flame ionization detection method using hydrogen as the carrier gas for the analysis of solvents in pharmaceuticals.

Within the pharmaceutical industry, the determination of residual solvents by Gas Chromatography Flame Ionization Detection (GC-FID) is a highly utilized analytical test that often employs helium (He) as the carrier gas. However, many do not realize that helium is a non-renewable resource that will eventually become progressively more difficult to source. In recent years, analytical chemists are increasingly adopting hydrogen (H) in place of helium for routine GC analysis. In this study, a simple and effici...

O2O Method for Fast Shape Retrieval.

A novel post-processing method, O2O (Online to Offline), to improve the result of shape retrieval is proposed in this paper. The essence of this proposed method is to move more work that consumes a lot of calculation to offline. With this essence, the O2O improves the retrieval result online with the help of the analysis offline. The offline analysis has two versions, one is self retrieval and the other is database clustering. The result of this kind of offline analysis can be reused indefinitely, regardles...

A New Data Analysis Method Based on Feature Linear Combination.

In biological data, feature relationships are complex and diverse, they could reflect physiological and pathological changes. Defining simple and efficient classification rules based on feature relationships is helpful for discriminating different conditions and studying disease mechanism. The popular data analysis method, k top scoring pairs (k-TSP), explores the feature relationship by focusing on the difference of the relative level of two features in different groups and classifies samples based on the ...

An efficient light on-off one-pot method for the synthesis of 3-styryl coumarins from aryl alkynoates.

An efficient one-pot stepwise method to synthesize 3-styryl-4-arylcoumarins from simple alkynoates is demonstrated. On the basis of the control experiments, a possible mechanism involving light-driven radical cyclization and Pd-catalysed cross-coupling processes for this synthesis method is proposed. The results of X-ray analysis and spectroscopy experiments prove that the substituent effect has a significant influence on the absorption and emission properties of the synthesized 3-styryl coumarins.

ChIAPoP: a new tool for ChIA-PET data analysis.

Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) is a popular assay method for studying genome-wide chromatin interactions mediated by a protein of interest. The main goal of ChIA-PET data analysis is to detect interactions between DNA regions. Here, we propose a new method and the associated data analysis pipeline, ChIAPoP, to detect chromatin interactions from ChIA-PET data. We compared ChIAPoP with other popular methods, including a hypergeometric model (used in ChIA-PET tool), MICC...

A simple and efficient method to recover isotopically enriched Ni-64 from electrolytic solutions.

Production of Cu via the proton irradiation of Ni, electrodeposited on a suitable backing substrate, remains the most common method to produce this emerging radionuclide. Some unforeseen cases arise when the electrodeposition does not work and the electrolytic solution needs to be reprocessed, but the presence of salt buffers makes it difficult to recover the nickel to prepare a fresh solution. The aim of this work was to develop a simple and efficient method to recover Ni from bath solutions.

Conducting secondary analysis of qualitative data: Should we, can we, and how?

While secondary data analysis of quantitative data has become commonplace and encouraged across disciplines, the practice of secondary data analysis with qualitative data has met more criticism and concerns regarding potential methodological and ethical problems. Though commentary about qualitative secondary data analysis has increased, little is known about the current state of qualitative secondary data analysis or how researchers are conducting secondary data analysis with qualitative data. This critical...

Principal Component Analysis based on Nuclear norm Minimization.

Principal component analysis (PCA) is a widely used tool for dimensionality reduction and feature extraction in the field of computer vision. Traditional PCA is sensitive to outliers which are common in empirical applications. Therefore, in recent years, massive efforts have been made to improve the robustness of PCA. However, many emerging PCA variants developed in the direction have some weaknesses. First, few of them pay attention to the 2D structure of error matrix. Second, to estimate data mean from sa...

A kernel-based image denoising method for improving parametric image generation.

One of the main challenges in the pixel-wise modeling analysis is the presence of high noise levels. Wang and Qi proposed a kernel-based method for dynamic positron emission tomgraphy reconstruction. Inspired by this method, we propose a kernel-based image denoising method based on the minimization of a kernel-based lp-norm regularized problem. To solve the kernel-based image denoising problem, we used the general-threshold filtering algorithm in combination with total difference. In the present study, we i...

Convergent evolution of the army ant syndrome and congruence in big-data phylogenetics Each important word in the title should begin with a capital letter.

Army ants are a charismatic group of organisms characterized by a suite of morphological and behavioral adaptations that includes obligate collective foraging, frequent colony relocation, and highly specialized wingless queens. This "army ant syndrome" underlies the ecological success of army ants and its evolution has been the subject of considerable debate. It has been argued to have arisen once or multiple times within the ant subfamily Dorylinae. To address this question in a phylogenetic framework I ge...

Knowledge-Guided Bayesian Support Vector Machine for High-Dimensional Data with Application to Analysis of Genomics Data.

Support vector machine (SVM) is a popular classification method for the analysis of wide range of data including big data. Many SVM methods with feature selection have been developed under frequentist regularization or Bayesian shrinkage frameworks. On the other hand, the importance of incorporating a priori known biological knowledge, such as gene pathway information which stems from the gene regulatory network, into the statistical analysis of genomic data has been recognized in recent years. In this arti...

CoCo-MD: A Simple and Effective Method for the Enhanced Sampling of Conformational Space.

CoCo ("Complementary Coordinates") is a method for ensemble enrichment based on Principal Component Analysis (PCA) that was developed originally for the investigation of NMR data. Here we investigate the potential of the CoCo method, in combination with molecular dynamics simulations (CoCo-MD), to be used more generally for the enhanced sampling of conformational space. Using the alanine penta-peptide as a model system, we find that an iterative workflow, interleaving short multiple-walker MD simulations wi...

Sliced inverse regression for integrative multi-omics data analysis.

Advancement in next-generation sequencing, transcriptomics, proteomics and other high-throughput technologies has enabled simultaneous measurement of multiple types of genomic data for cancer samples. These data together may reveal new biological insights as compared to analyzing one single genome type data. This study proposes a novel use of supervised dimension reduction method, called sliced inverse regression, to multi-omics data analysis to improve prediction over a single data type analysis. The study...

A method for early detection and identification of fungal contamination of building materials using e-nose.

The aim of the study was to develop a method for early detection and identification of fungal contamination of building materials using an electronic nose. Therefore, the laboratory experiments based on the analysis of the air in the vicinity of fungal isolates potentially found in the building materials were performed. The results revealed that the employed gas sensors array consisting of MOS-type sensors enables the detection of the differences among the examined samples of fungi and distinguishing betwee...

A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data.

Single-cell RNA sequencing (scRNAseq) data always involves various unwanted variables, which would be able to mask the true signal to identify cell-types. More efficient way of dealing with this issue is to extract low dimension information from high dimensional gene expression data to represent cell-type structure. In the past two years, several powerful matrix factorization tools were developed for scRNAseq data, such as NMF, ZIFA, pCMF and ZINB-WaVE. But the existing approaches either are unable to direc...

An overview of blackwater data collection from space life support systems and its comparison to a terrestrial wastewater dataset.

Extraterrestrial colonization is a certain eventuality that would be nearly impossible without the efficient and robust resources of recovering life support systems. Knowledge of inputs is necessary for the development of such systems, especially for the first stages of design such as mass balancing and the selection of unitary processes. One of the most important inputs is blackwater, as this stream is the most polluted and rich in resources and needs to be treated and reused. In the paper, data from space...


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