Shortest-path network analysis is a useful approach toward identifying genetic determinants of longevity. by J R Managbanag, Tarynn M Witten, Danail Bonchev, Lindsay A Fox, Mitsuhiro Tsuchiya, Brian K Kennedy, Matt Kaeberlein

“…To date, however, targeted efforts at identifying longevity-associated genes have been limited by a lack of predictive power, and useful algorithms for candidate gene-identification have also been lacking.<h4>Methodology/principal findings</h4>We have utilized a shortest-path network analysis to identify novel genes that modulate longevity in Saccharomyces cerevisiae. …”
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Evidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis. by Shashwath A Meda, Michael C Stevens, Bradley S Folley, Vince D Calhoun, Godfrey D Pearlson

“…<h4>Background</h4>Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by "functional connectivity" analyses.<h4>Methodology/principal findings</h4>We used independent component analysis (ICA) to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition) of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. …”
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Key parameters and sensitivity analysis of lower limb muscle strength in young men with different gait patterns. by Yifei Wang, Jianbo Sun, Xuesong Guo, Delong Dong, Chuankai Luan, Xiaolin Wang

“…<h4>Objective</h4>To explore the functional characteristics and principal component differences of electromyography in different phases of the gait cycle, to provide key parameters for identifying a complete gait, and to provide a reference for joint moment solving in the lower limb.…”
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Water treatment in an integrated coagulation– microfiltration system, as illustrated with the example of the Water Treatment Plant in Jarosław by Ewa Dacewicz, Mirosław Janowski

“…The application of factor analysis made it possible to reduce the number of random variables down to the set described by four principal components, including two variables related to the bacteriological quality of water. …”
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Comparative analysis of profitability and resource use efficiency between Penaeus monodon and Litopenaeus vannamei in India. by Ubair Nisar, Hongzhi Zhang, Mahida Navghan, Yugui Zhu, Yongtong Mu

“…The study aimed to highlight the profitability and production function analysis of Penaeus monodon and Litopenaeus vannamei in intensified shrimp farms in Gujarat (India). …”
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Psychometric evaluation of the extended inclusion of nature in self scale in Chinese adults through the Rasch analysis by Xuanyi Wang, Shulin Chen

“…Then, using the Rasch model and the classical test theory, we elaborately examined the psychometric properties of the scale with a sample of 786 Chinese adults. Exploratory factor analysis, principal components analysis of Rasch residuals, and confirmative factor analysis together provided robust evidence for the one‐factor structure of the EINS‐C. …”
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Investigating the Effects of Reconstruction Conditions on Image Quality and Radiomic Analysis in Photon-counting Computed Tomography by Miyu Ohata, Ryohei Fukui, Yusuke Morimitsu, Daichi Kobayashi, Takatsugu Yamauchi, Noriaki Akagi, Mitsugi Honda, Aiko Hayashi, Koshi Hasegawa, Katsuhiro Kida, Sachiko Goto, Takao Hiraki

“…Principal component analysis and receiver operating characteristics analysis also showed higher values with increasing QIR intensity. …”
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Comparative Analysis of Microbiological Profiles and Antibiotic Resistance Genes in Subjects with Colorectal Cancer and Healthy Individuals by Li Jun, Zhu Yanyun, Chang Qing, Gong Yuan, Wan Jun, Xu Shiping

“…Fecal samples were obtained from seven CRC patients and six healthy subjects, and the sequencing data were analyzed for similarity, a-diversity, principal component analysis (PCA), and linear discriminant analyses (LDA). …”
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Analysis of Data and Feature Processing on Stroke Prediction using Wide Range Machine Learning Model by Untari Novia Wisesty, Tjokorda Agung Budi Wirayuda, Febryanti Sthevanie, Rita Rismala

“…Pearson Correlation and Principal Component Analysis are also used for dimensional reduction and analyzing the important features that are most influential in predicting stroke. …”
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Quantitative Analysis of Fish Morphology Through Landmark and Outline-based Geometric Morphometrics with Free Software by Du Luo

“…This study presents a comprehensive workflow for conducting geometric morphometric analysis of fish morphology. The step-by-step manual provides detailed instructions for using popular free software, such as the TPS series, MorphoJ, ImageJ, and R, to carry out generalized Procrustes analysis (GPA), principal component analysis (PCA), discriminant function analysis (DFA), canonical variate analysis (CVA), mean shape analysis, and thin plate spline analysis (TPS). …”
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Gene expression profiling and pathway analysis in head and neck squamous cell carcinoma: focus on disulfidptosis by Yajun Tong, Site Bai, Ludi Ou, Qiang Zhou, Songlian Liu, Leilan Yin, Kewei Tang, Ling Long, Qinghua Yin

“…A disulfidptosis score (DRGscore) was developed via principal component analysis of prognosis-associated genes and validated across immunotherapy cohorts. …”
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Elucidating the molecular basis of salt tolerance in potatoes through miRNA expression and phenotypic analysis by Caicai Lin, Shuangshuang Zheng, Kui Liu, Ru Yu, Peiyan Guan, Baigeng Hu, Lingling Jiang, Mengyu Su, Guodong Hu, Qingshuai Chen, Xia Zhang

“…This study evaluated the salt tolerance of 17 diverse potato varieties using principal component analysis, membership function analysis, cluster analysis, and stepwise regression analysis. …”
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Multivariate Statistical Analysis Uncovers Spectrum–Effect Relationship between HPLC Fingerprints and Antioxidant Activity of Saffron by Ya You, Zijin Xu, Qingrou Zhong, Lin Zhu, Susu Lin, Qiaoqiao Li, Yifeng Cao, Yi Tao, Suhong Chen, Ping Wang

“…The fingerprints of 21 batches of saffron collected from different regions were assessed, and the data were further analyzed by chemometric methods, including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. …”
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Analysis of Differences in Metabolite and Antioxidant Activity in Highland Red Raspberry Pulp Based on Widely Targeted Metabolomics by Yangbo Song, Jie Wang, Xiaojian Pu

“…Ultra-high performance liquid chromatography–mass spectrometry (UHPLC-MS/MS), combined with principal component analysis and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), was used to process the data and correlate them with the results of four antioxidant assays. …”
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Comparative Analysis of Bioactive Compounds and Flavor Characteristics in Red Fermentation of Waxy and Non-Waxy Millet Varieties by Zehui Yang, Jie Liu, Xiaopeng Li, Changyu Zhang, Pengliang Li, Yawei Zhu, Jingke Liu, Bin Liu

“…The samples were solid-state-fermented with “<i>Red Ferment</i>” and evaluated for bioactive components. (2) Methods: Multiple analytical methods—including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal PLS-DA (OPLS-DA), cluster analysis, and correlation analysis—were employed to systematically compare bioactive components and VCs. (3) Results: Significant varietal differences were observed: (1) Miao Xiang glutinous millet showed higher monacolin K (MK) and fatty acid contents; (2) Jigu-42 contained significantly more polyphenols; (3) linoleic acid dominated the fatty acid profiles of two varieties; and (4) a total of twenty-seven VCs were identified, including six alcohols, four aldehydes, seven ketones (corrected from duplicated count), two aromatic hydrocarbons, three heterocycles, one acid, three furans, and one ether. (4) Conclusions: The two varieties exhibited significant differences in MK, pigment profiles, fatty acid composition, polyphenol content, and volatile-compound profiles. …”
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In silico analysis of quorum sensing modulators: Insights into molecular docking and dynamics and potential therapeutic applications. by Ali Alisaac

“…Molecular docking and MD simulations assessed binding affinity and structural dynamics, analyzing parameters like docking scores, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), radius of gyration (Rg), principal component analysis (PCA), and covariance analysis. …”
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Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma by Xiang Xiong, Wen Liu, Chuan Yao

“…Calibration curves were generated to illustrate the discrepancies between predicted and observed outcomes. Principal Component Analysis (PCA) was performed to investigate the distribution of LUAD patients across high- and low-risk groups. …”
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Chemical profiling, discriminant analysis, antioxidants, and anti-inflammatory activities of Lonicerae Japonicae Flos tea varieties by Jiao Wu, Xiaoyan Du, Fangchao Tong, Shuangling Zhang, Jiaojie Guo, Changchun Zhu, Rui Cui, Qirong Bai, Mengyao Chen, Li Meng, Linlin Song, Haichuan Yu

“…Multivariate statistical approaches, including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), were employed, with 80 % of variance being explained by PCA (PC1+PC2), while isochlorogenic acid C (VIP=1.32) and secoxyloganin (VIP=1.18) were identified by PLS-DA as the most significant markers for varietal differentiation. …”
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Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data. by Marco Borri, Maria A Schmidt, Ceri Powell, Dow-Mu Koh, Angela M Riddell, Mike Partridge, Shreerang A Bhide, Christopher M Nutting, Kevin J Harrington, Katie L Newbold, Martin O Leach

“…Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. …”
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Detection of single nucleotide polymorphisms associated with litter size in goats using genotyping-by-sequencing and association analysis by Satoshi Kubota, Thara Wongdee, Pramote Paengkoum

“…After filtering, 21,665 SNPs were retained. The first two principal components obtained from individual genotypes classified the 31 goats into three clusters. …”
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