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Li Li, Qifa Song and Xi Yang

risk of missing naturally occurring disease patterns or subgroups ( 14 ). In contrast, K-means clustering method, a type of big data analysis techniques, applies unsupervised clustering algorithms to classify patients according to the distribution of

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Lilit Egshatyan, Daria Kashtanova, Anna Popenko, Olga Tkacheva, Alexander Tyakht, Dmitry Alexeev, Natalia Karamnova, Elena Kostryukova, Vladislav Babenko, Maria Vakhitova and Sergey Boytsov

diagnosed T2D with disease duration <12 months after the diagnosis and the HbA1c level from 6.5 to 9.0%. Patients were also divided into diet clusters depending on the diet nutrients (by using the k -means clustering). Criteria for exclusion from the study

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Anello Marcello Poma, Riccardo Giannini, Paolo Piaggi, Clara Ugolini, Gabriele Materazzi, Paolo Miccoli, Paolo Vitti and Fulvio Basolo

using the RNeasy FFPE Kit (Qiagen) in conformance to the manufacturer’s instructions. RNA was eluted in 20 μL of RNase-free water. RNA and DNA quantification and quality were assessed by means of a spectrophotometer (Xpose Trinean, Gentbrugge, Belgium

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Robert I Menzies, Xin Zhao, Linda J Mullins, John J Mullins, Carolynn Cairns, Nicola Wrobel, Donald R Dunbar, Matthew A Bailey and Christopher J Kenyon

transcripts were analysed with DAVID Bioinformatic Resources ( 23 ). Cluster analysis of genes involved in signalling, sterol and lipid metabolism and cell turnover was carried out with Miru software ( 24 ). Genes of interest that are discussed are listed in

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Aneta Gawlik, Michael Shmoish, Michaela F Hartmann, Stefan A Wudy, Zbigniew Olczak, Katarzyna Gruszczynska and Ze’ev Hochberg

subject’s unique metabolic fingerprint and offers means of metabolomic phenotyping at the individual level ( 9 , 10 ). Thus, each individual has a unique ‘steroidal fingerprint’. A cluster of similar ‘steroidal fingerprints’ related to a disease would be

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Nidan Qiao

2. Studies were included if they evaluated machine learning algorithms (logistic regression with regulation, linear discriminant analysis, k means, k nearest neighbor, cluster analysis, support vector machine, decision tree-based models and neural

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Marieke S Velema, Evie J M Linssen, Ad R M M Hermus, Hans J M M Groenewoud, Gert-Jan van der Wilt, Antonius E van Herwaarden, Jacques W M Lenders, Henri J L M Timmers and Jaap Deinum

adrenocortical remodeling leading to aldosterone-producing cell cluster generation . International Journal of Endocrinology 2016 2016 7834356 . ( https://doi.org/10.1155/2016/7834356 ) 23 Nishimoto K Seki T Kurihara I Yokota K Omura M Nishikawa T Shibata

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Julie Smith, Jan Fahrenkrug, Henrik L Jørgensen, Christina Christoffersen and Jens P Goetze

handling – peroxisomal proliferator-activated receptor alpha (PPARα), PPARγ, lipoprotein lipase (LPL), cluster of differentiation 36 (CD36), fatty acid-binding protein 1 (FATP1), FATP4, carnitine palmitoyltransferase 1 (CPT1), long chain acyl

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Mieke Van Hemelrijck, Thurkaa Shanmugalingam, Cecilia Bosco, Wahyu Wulaningsih and Sabine Rohrmann

population The National Center for Health Statistics (NCHS) conducted NHANES III between 1988 and 1994 (15) , and designed it as a multistage stratified, clustered probability sample of the USA civilian non-institutionalized population who was at least 2

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Mubashir Mulla and Klaus-Martin Schulte

calculation of sensitivity and NPV. Five studies provided clustered results for both central and lateral CLN detection, out of which only one (16) calculated the sensitivity and NPV correctly. Table 1 Ultrasonography in detection of cervical LN in PTC