###### acute treatment

- This study will compare the effectiveness of oxygen delivered via demand valve versus continuous high flow oxygen via non-rebreather face mask in the acute treatment of a cluster headache attack. (clinicaltrials.gov)
- This proof of concept trial will evaluate if oxygen delivered via demand valve with a specific breathing technique is effective as a cluster headache acute treatment and is more effective than the traditional continuous high flow oxygen treatment with a non-rebreather face mask. (clinicaltrials.gov)
- This study's hypothesis is the 4mg StatDose sumatriptan is effective for the acute treatment of cluster headache and provides good safety and tolerability across multiple doses of the study medication as well as across multiple attacks of cluster headache. (clinicaltrials.gov)
- This study seeks to determine the safety and efficacy of the commercially available 4mg StatDose formulation of sumatriptan as an acute treatment of cluster headache. (clinicaltrials.gov)

###### sumatriptan

- Currently, the two most common treatments for cluster headaches are inhaled oxygen and injectable sumatriptan. (clinicaltrials.gov)
- This is an open label trial of sumatriptan 4 mg using the StatDose injector system for the treatment of acute attacks of cluster headache. (clinicaltrials.gov)
- 4mg Sumatriptan Statdose injection for use as acute therapy in a cluster headache. (clinicaltrials.gov)
- The primary efficacy parameters will be the percentage of cluster headache attacks that result in the cluster headache pain being reduced to mild or none following a single dose of 4 mg subcutaneous sumatriptan at 15 minutes and at 30 minutes. (clinicaltrials.gov)

###### patients

- These treatments do not work for all cluster headache patients, and patients who smoke may eventually develop contraindication to triptans. (clinicaltrials.gov)
- All patients will treat one cluster headache with each of the 2 treatment methods. (clinicaltrials.gov)
- Patients with both episodic cluster headache as well as chronic cluster headache will be studied. (clinicaltrials.gov)
- Patients must either not have started preventive treatment for cluster headache or be on a stable dose of preventive medication. (clinicaltrials.gov)
- Patients with episodic cluster headache may have not begun taking preventive medications at the time of study or must be on a stable regimen of preventive medications. (clinicaltrials.gov)
- Patients with chronic cluster headache must be on a stable regimen of preventive medications. (clinicaltrials.gov)
- Patients will be required to treat 3 acute attacks of cluster headache with the study medication or to use more than 1 dose of study medication to fully treat an individual attack of cluster headache with a maximum of 3 doses of the study medication within a 24 hour time frame. (clinicaltrials.gov)

###### relief

- The goal of acute therapy for cluster headache is fast, effective and consistent relief. (clinicaltrials.gov)
- The time meaningful relief of cluster headache. (clinicaltrials.gov)

###### attacks

- Cluster headache is a disorder marked by frequent attacks of short-lasting, severe, unilateral head pain with associated autonomic symptoms. (clinicaltrials.gov)
- They may treat up to 3 attacks of cluster headache with the study medication. (clinicaltrials.gov)

###### trial

- Patient entering the trial must either be in the first 3 weeks of an episodic cluster headache cycle or have chronic cluster headache. (clinicaltrials.gov)

###### system

- This system may be more efficacious at stopping a cluster headache attack than the currently prescribed oxygen delivery system. (clinicaltrials.gov)
- This delivery system may be better at stopping a cluster headache attack than the continuous flow model as it can support hyperventilation which can enhance cerebral arterial vasoconstriction via a state of hyperoxia and hypocapnia. (clinicaltrials.gov)

###### minutes

- In the currently recommended dosing strategy of continuous flow 100% oxygen given via a non-rebreather face mask at 7-15L/min, the time to improvement can sometimes take upwards of 20-30 minutes and is not effective for all cluster headache sufferers. (clinicaltrials.gov)

###### Agglomerative

- Agglomerative clustering starts with each case as a unique cluster, and with each step combines cases to form larger clusters until there is only one or a few larger clusters. (encyclopedia.com)
- It is based on grouping clusters in bottom-up fashion (agglomerative clustering), at each step combining two clusters that contain the closest pair of elements not yet belonging to the same cluster as each other. (wikipedia.org)
- In the beginning of the agglomerative clustering process, each element is in a cluster of its own. (wikipedia.org)
- The definition of 'shortest distance' is what differentiates between the different agglomerative clustering methods. (wikipedia.org)
- The following algorithm is an agglomerative scheme that erases rows and columns in a proximity matrix as old clusters are merged into new ones. (wikipedia.org)
- In the naive algorithm for agglomerative clustering, implementing a different linkage scheme may be accomplished simply by using a different formula to calculate inter-cluster distances in the algorithm. (wikipedia.org)
- Complete-linkage clustering is one of several methods of agglomerative hierarchical clustering. (wikipedia.org)

###### implementing a different linkage

- Alternative linkage schemes include single linkage and average linkage clustering - implementing a different linkage in the naive algorithm is simply a matter of using a different formula to calculate inter-cluster distances in the initial computation of the proximity matrix and in step 4 of the above algorithm. (wikipedia.org)

###### algorithms

- There are two broad types of clustering algorithms: hierarchical clustering and nonhierarchical clustering (partitioning). (encyclopedia.com)
- It can be achieved by various algorithms that differ significantly in their notion of what constitutes a cluster and how to efficiently find them. (wikipedia.org)
- The notion of a "cluster" cannot be precisely defined, which is one of the reasons why there are so many clustering algorithms. (wikipedia.org)
- However, different researchers employ different cluster models, and for each of these cluster models again different algorithms can be given. (wikipedia.org)
- The notion of a cluster, as found by different algorithms, varies significantly in its properties. (wikipedia.org)
- Understanding these "cluster models" is key to understanding the differences between the various algorithms. (wikipedia.org)
- In bioinformatics, sequence clustering algorithms attempt to group biological sequences that are somehow related. (wikipedia.org)
- Some clustering algorithms use single-linkage clustering, constructing a transitive closure of sequences with a similarity over a particular threshold. (wikipedia.org)

###### linkage schemes include

- Alternative linkage schemes include complete linkage clustering, average linkage clustering, and Ward's method. (wikipedia.org)

###### hierarchical cluster analysis

- This document demonstrates, on several famous data sets, how the dendextend R package can be used to enhance Hierarchical Cluster Analysis (through better visualization and sensitivity analysis). (r-project.org)

###### assigns

- The K -means algorithm assigns each case to the cluster having the nearest centroid. (encyclopedia.com)
- The simplest kind of clustering (case 1) assigns genes to prespecified groups. (pnas.org)

###### Zhang

- X. Chen and J. Zhang, "Clustering algorithm based on improved particle swarm optimization," Journal of Computer Research and Development , pp. 287-291, 2012. (hindawi.com)

###### mRNA

- In a cluster analysis we start with raw data y , which we use to estimate the relative expression r of the genes among the mRNA samples. (pnas.org)
- For EST data, clustering is important to group sequences originating from the same gene before the ESTs are assembled to reconstruct the original mRNA. (wikipedia.org)

###### naive algorithm

- The naive algorithm for single linkage clustering is essentially the same as Kruskal's algorithm for minimum spanning trees. (wikipedia.org)

###### algorithm represents

- for example, the k-means algorithm represents each cluster by a single mean vector. (wikipedia.org)
- The slink algorithm represents a clustering on a set of n {\displaystyle n} numbered items by two functions. (wikipedia.org)

###### exploratory

- Searching for groupings, or clusters , is an important exploratory technique. (encyclopedia.com)
- It is a main task of exploratory data mining , and a common technique for statistical data analysis , used in many fields, including machine learning , pattern recognition , image analysis , information retrieval , bioinformatics , data compression , and computer graphics . (wikipedia.org)
- This analysis technique is typically performed during the exploratory phase of research, since unlike techniques such as factor analysis , it doesn't make any distinction between dependent and independent variables. (surveygizmo.com)

###### groupings

- This method uses a cluster algorithm to identify groupings by performing pre-clustering first, and then performing hierarchical methods. (surveygizmo.com)

###### 1967

- J. MacQueen, "Some methods for classification and analysis of multivariate observations," in Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume 1: Statistics , pp. 281-297, University of California Press, Berkeley, Calif, USA, 1967. (hindawi.com)
- Cavalli-Sforza LL, Edwards AWF (1967) Phylogenese analysis: models and estimation procedures. (springer.com)

###### slink

- In May 1976, D. Defays proposed an optimally efficient algorithm of only complexity O ( n 2 ) {\displaystyle O(n^{2})} known as CLINK (published 1977) inspired by the similar algorithm SLINK for single-linkage clustering. (wikipedia.org)

###### bioinformatics

- Integrative Cluster Analysis in Bioinformatics. (wikipedia.org)

###### fuzzy

- This chapter discusses the challenges posed by weather databases and examines the use of fuzzy clustering for analyzing such data. (springer.com)
- It proposes the extension of the fuzzy K-Means clustering algorithm to account for the spatio-temporal nature of weather data. (springer.com)
- It introduces an unsupervised fuzzy clustering algorithm, based on the fuzzy KMeans and defines a cluster validity index which is used to determine an optimal number of clusters. (springer.com)
- Gasch, A.P. and M.B. Eisen, Exploring the Conditional Coregulation of Yeast Gene Expression through Fuzzy K-Means Clustering. (springer.com)
- deGruijter, J.J. and A.B. McBratney, A Modified Fuzzy K Means for Predictive Classification, in Classification and Related Methods of Data Analysis, H.H. Bock, Editor. (springer.com)
- Liu Z., George R. (2005) Mining Weather Data Using Fuzzy Cluster Analysis. (springer.com)

###### statistically

- We propose a bootstrap method to assess the reliability of clustering results in a statistically quantifiable manner. (pnas.org)
- We identify statistically significant clusters with high or low rates in the zip code level using the Getis-Ord statistics. (hindawi.com)

###### drawback

- A drawback of this method is that it tends to produce long thin clusters in which nearby elements of the same cluster have small distances, but elements at opposite ends of a cluster may be much farther from each other than two elements of other clusters. (wikipedia.org)
- X {\displaystyle X} and Y {\displaystyle Y} are two sets of elements (clusters) Complete linkage clustering avoids a drawback of the alternative single linkage method - the so-called chaining phenomenon, where clusters formed via single linkage clustering may be forced together due to single elements being close to each other, even though many of the elements in each cluster may be very distant to each other. (wikipedia.org)

###### simplest

- The simplest Gaussian model is when the covariance matrix of each cluster is constrained to be diagonal. (wias-berlin.de)

###### denotes

- Here n k denotes the number of observations of the k th cluster. (wias-berlin.de)
- We use r̂ to estimate a clustering C . (The ^ notation denotes estimated quantities. (pnas.org)

###### squares

- Joe Ward ' s method (1963) is based on the sum of squares between the two clusters, summed over all variables. (encyclopedia.com)
- A criterion such as between-groups sum of squares or likelihood can be plotted against the number of clusters in a scree plot . (encyclopedia.com)
- The result of a cluster analysis shown as the coloring of the squares into three clusters. (wikipedia.org)

###### classification

- Besides the term clustering , there are a number of terms with similar meanings, including automatic classification , numerical taxonomy , botryology (from Greek βότρυς "grape") and typological analysis . (wikipedia.org)
- MacQueen, J.B. Some Methods for Classification and Analysis of Multivariate Observations. (springer.com)
- Methods of cluster analysis, classification and multivariate graphics can be used in order to extract hidden knowledge from huge data sets containing numerical and non-numerical information. (wias-berlin.de)
- Classification and clustering: Models, software and applications. (wias-berlin.de)

###### Observations

- So, hierarchical clustering of millions of observations is possible. (wias-berlin.de)
- Partitioning methods start with an initial (random) partition and proceed by exchanging observations between clusters. (wias-berlin.de)
- The problem of clustering multivariate observations is viewed as the replacement of a set of vectors with a set of labels and representative vectors. (bell-labs.com)

###### distances

- This can be done by forming all pairs of objects, with one object in one cluster and one in the other, and computing the distances between the members of these pairs. (encyclopedia.com)
- Popular notions of clusters include groups with small distances between cluster members, dense areas of the data space, intervals or particular statistical distributions . (wikipedia.org)
- From data to distances and then finally to results of (hierarchical) clustering. (wias-berlin.de)
- However, in single linkage clustering, the order in which clusters are formed is important, while for minimum spanning trees what matters is the set of pairs of points that form distances chosen by the algorithm. (wikipedia.org)

###### defines

- for example, DBSCAN and OPTICS defines clusters as connected dense regions in the data space. (wikipedia.org)

###### centroid

- The mean profile of a cluster is the centroid , the set of means of the variables, for the individuals in that cluster. (encyclopedia.com)
- The centroid method is based on the distance between cluster centroids. (encyclopedia.com)
- The process begins by partitioning the cases into K initial clusters and assigning each case to the cluster whose centroid is nearest. (encyclopedia.com)

###### pairs

- Find the most similar pair of clusters in the current clustering, say pair (r), (s), according to d[(r),(s)] = min d[(i),(j)] where the minimum is over all pairs of clusters in the current clustering. (wikipedia.org)
- Starcode: a fast sequence clustering algorithm based on exact all-pairs search. (wikipedia.org)
- In complete-linkage clustering, the link between two clusters contains all element pairs, and the distance between clusters equals the distance between those two elements (one in each cluster) that are farthest away from each other. (wikipedia.org)

###### vectors

- In case of big data, the methods based on clustering of cores (representative points, mean vectors) can be recommended. (wias-berlin.de)

###### intervals

- This study evaluates the clustering of hospitalization rates for stroke and compares this clustering with two different time intervals 2009-2010 and 2012-2013, corresponding to the beginning of the French National Stroke Plan 2010-2014. (hindawi.com)

###### essentially

- A "clustering" is essentially a set of such clusters, usually containing all objects in the data set. (wikipedia.org)

###### criterion

- A general criterion for clustering is derived as a measure of representation error. (bell-labs.com)

###### researchers

- It is sometimes suggested that researchers start with hierarchical clustering to generate initial centroids, and then use nonhierarchical clustering. (encyclopedia.com)
- Cluster analysis differs from many other statistical methods due to the fact that it's mostly used when researchers do not have an assumed principle or fact that they are using as the foundation of their research. (surveygizmo.com)
- Clustering allows researchers to identify and define patterns between data elements. (surveygizmo.com)
- Here, researchers define the number of clusters prior to performing the actual study. (surveygizmo.com)

###### methods

- Two-step clustering is best for handling larger datasets that would otherwise take too long a time to calculate with strictly hierarchical methods. (surveygizmo.com)
- In statistics, single-linkage clustering is one of several methods of hierarchical clustering. (wikipedia.org)

###### similarity

- contains all predicted genes from eleven virus families organized into ortholog groups by BLASTP similarity Skipredudant EMBOSS tool to remove redundant sequences from a set PISCES: A Protein Sequence Culling Server RDB90 UniRef: A non-redundant UniProt sequence database Uniclust: A clustered UniProtKB sequences at the level of 90%, 50% and 30% pairwise sequence identity. (wikipedia.org)

###### methodology

- It develops a methodology for clustering a large number of developing countries, identifying and ranking their welfare regimes, assessing their stability over the decade 1990-2000, and relating these to important structural variables. (bath.ac.uk)

###### statistical

- clusters are modeled using statistical distributions, such as multivariate normal distributions used by the expectation-maximization algorithm . (wikipedia.org)
- Cluster analysis is a statistical method used to group similar objects into respective categories. (surveygizmo.com)
- We introduce a general technique for making statistical inference from clustering tools applied to gene expression microarray data. (pnas.org)
- However, another question that is at least as important has received less attention: How does one make statistical inference based on the results of clustering? (pnas.org)
- He worked for the Brain Research Laboratories (New York University) developing neurometric systems based on the multivariate statistical analysis of electroencephalographic signals (EEG). (wikipedia.org)

###### multivariate normal

- If the within-cluster type of distribution is specified (such as multivariate normal), then the method of maximum likelihood can be used to estimate the parameters. (encyclopedia.com)

###### representative

- Clustering techniques based on cores (representative points) are appropriate tools for data mining of large data sets. (wias-berlin.de)
- if a sequence is not matched then it becomes the representative sequence for a new cluster. (wikipedia.org)
- Sequence clustering is often used to make a non-redundant set of representative sequences. (wikipedia.org)
- Determining a representative tertiary structure for each sequence cluster is the aim of many structural genomics initiatives. (wikipedia.org)

###### depend

- The appropriate clustering algorithm and parameter settings (including parameters such as the distance function to use, a density threshold or the number of expected clusters) depend on the individual data set and intended use of the results. (wikipedia.org)
- The specifics of the transformation from r̂ to Ĉ and the structure of C depend on the clustering method. (pnas.org)

###### sequence

- A well-known clustering is that of stars into a main sequence, white giants, and red dwarfs, according to temperature and luminosity. (encyclopedia.com)
- The result of the clustering can be visualized as a dendrogram, which shows the sequence of cluster fusion and the distance at which each fusion took place. (wikipedia.org)
- The algorithm is composed of the following steps: Begin with the disjoint clustering having level L(0) = 0 and sequence number m = 0. (wikipedia.org)
- Sequence clusters are often synonymous with (but not identical to) protein families. (wikipedia.org)

###### neural networks

- the most well known unsupervised neural network is the self-organizing map and these models can usually be characterized as similar to one or more of the above models, and including subspace models when neural networks implement a form of Principal Component Analysis or Independent Component Analysis . (wikipedia.org)

###### genes

- The approach utilizes an analysis of variance model to achieve normalization and estimate differential expression of genes across multiple conditions. (pnas.org)
- Specifically, an assortment of clustering techniques have been developed and applied to identify groups of genes with similar patterns of expression ( 3 - 6 ). (pnas.org)
- Consider two genes that cluster together. (pnas.org)
- Are the patterns of expression for these genes sufficiently similar beyond any reasonable doubts raised by the uncertainty of the estimates, or could these genes have clustered together by chance? (pnas.org)
- By "clustering" genes, we mean organizing genes into groups, which may be predefined or data-driven, or organizing genes into a structure to represent some measure of distance between them. (pnas.org)
- This is the case for our example below, where genes are clustered by calculating the correlation of an observed profile with a collection of fixed target profiles. (pnas.org)

###### namely

- In single-linkage clustering, the distance between two clusters is determined by a single element pair, namely those two elements (one in each cluster) that are closest to each other. (wikipedia.org)

###### displaystyle

- These functions are both determined by finding the smallest cluster C {\displaystyle C} that contains both item i {\displaystyle i} and at least one larger-numbered item. (wikipedia.org)

###### Gene Expression

- The input into any clustering technique is a set of estimates of relative gene expression from a microarray experiment. (pnas.org)

###### different

- The military has used cluster analysis of anthropometric data to reduce the number of different uniform sizes kept in inventory. (encyclopedia.com)
- cases with disparate profiles, in different clusters. (encyclopedia.com)
- The goal of performing a cluster analysis is to sort different objects or data points into groups in a manner that the degree of association between two objects is high if they belong to the same group, and low if they belong to different groups. (surveygizmo.com)
- This approach is useful when testing different models with a different assumed number of clusters. (surveygizmo.com)
- Model-based Gaussian clustering allows to identify clusters of quite different shapes, see the application to ecology in Figure 2. (wias-berlin.de)

###### method

- This is the most common method of clustering. (surveygizmo.com)
- This method is used to quickly cluster large datasets. (surveygizmo.com)
- The rows are ordered based on the order of the hierarchical clustering (using the "complete" method). (r-project.org)
- The method is also known as nearest neighbour clustering. (wikipedia.org)

###### Regimes

- Smyth, P., K. Ide, and M. Ghil, Multiple Regimes in Nothern Hemisphere Height Fields Via Mixture Model Clustering. (springer.com)

###### patterns

- Instead, a cluster analysis algorithm may be able to detect the micro clusters formed by these patterns. (wikipedia.org)

###### Quantitative

- Analysis of quantitative trait loci, or QTL, is a more recent addition to quantitative genetics, linking it more directly to molecular genetics. (wikipedia.org)

###### 1993

- Alonso A, Martfn P, Albarran C, Sancho M (1993) Amplified fragment length polymorphism analysis of the VNTR locus D1S80 in central Spain. (springer.com)
- Chistiakov DA, Gavrilov DK, Ovchinnikov IV, Nosikov W (1993) The use of PCR techniques for the VNTR allele distribution analysis of 120 unrelated russian individuals living in Moscow. (springer.com)

###### nearest

- A New Shared Nearest Neighbor Clustering Algorithm and Its Applications. (springer.com)
- Each of the significant clusters is monitored over time and evaluated according to the nearest stroke unit distance and the socioeconomic profile. (hindawi.com)

###### optimal

- The study of facility location problems, also known as location analysis, is a branch of operations research and computational geometry concerned with the optimal placement of facilities to minimize transportation costs while considering factors like avoiding placing hazardous materials near housing, and competitors' facilities. (wikipedia.org)

###### Research

- For example, when cluster analysis is performed as part of market research , specific groups can be identified within a population. (surveygizmo.com)

###### tends

- Complete linkage tends to find compact clusters of approximately equal diameters. (wikipedia.org)

###### Protocols

- where he developed experimental protocols, conducted data analysis, as well as designed and built low noise instrumentation for a variety of psycho physiological and physical experiments. (wikipedia.org)

###### techniques

- Simulation studies were carried out in order to compare core-based clustering techniques with well-known model-based ones. (wias-berlin.de)
- A great deal of effort has gone into identifying the best clustering techniques for microarray data. (pnas.org)
- The techniques also apply to cluster analysis. (wikipedia.org)

###### Everitt

- Everitt B., Hothorn T. (2011) Cluster Analysis. (springer.com)

###### Discovery

- Cluster analysis as such is not an automatic task, but an iterative process of knowledge discovery or interactive multi-objective optimization that involves trial and failure. (wikipedia.org)
- Discovery of Climate Indices Using Clustering. (springer.com)

###### species

- We can visualize the result of running it by turning the object to a dendrogram and making several adjustments to the object, such as: changing the labels, coloring the labels based on the real species category, and coloring the branches based on cutting the tree into three clusters. (r-project.org)

###### general

- Cluster analysis itself is not one specific algorithm , but the general task to be solved. (wikipedia.org)
- Some have proposed to group symptoms into clusters or into one general functional somatic disorder given the finding of correlations between symptoms and underlying etiologies. (wikipedia.org)

###### mean

- Examining them provides insight as to what the clusters mean. (encyclopedia.com)

###### large

- Divisive clustering begins with one large cluster and splits it into smaller clusters. (encyclopedia.com)

###### similar

- Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster ) are more similar (in some sense) to each other than to those in other groups (clusters). (wikipedia.org)
- Hierarchical clustering can group variables together in a manner similar to factor analysis . (surveygizmo.com)

###### order

- It's easy to overthink cluster analysis, but our brains naturally cluster data on a regular basis in order to simplify the world around us. (surveygizmo.com)

###### interpretation

- A cluster ' s profile can suggest an interpretation and a name for it. (encyclopedia.com)
- Instead, cluster analysis is leveraged mostly to discover structures in data without providing an explanation or interpretation. (surveygizmo.com)

###### results

- Here we apply bootstrapping to assess the stability of results from a cluster analysis. (pnas.org)
- We illustrate the technique with a publicly available data set and draw conclusions about the reliability of clustering results in light of variation in the data. (pnas.org)

###### larger

- The clusters are then sequentially combined into larger clusters, until all elements end up being in the same cluster. (wikipedia.org)
- The resulting motion forms small clusters of small plumes right above the core-mantle boundary that combine to form larger plumes and then contribute to superplumes. (wikipedia.org)

###### find

- company to better position itself, explore new markets, and development products that specific clusters find relevant and valuable. (surveygizmo.com)

###### Group

- For example, a group of friends sitting at the same table in a restaurant can be considered a cluster. (surveygizmo.com)
- In this example, note that as we move down the chain of clusters, humans show less and less similarities to the other members of the group. (surveygizmo.com)

###### Tools

- Jeffrey Owen Katz (born 1950) is an American scientist best known for his pivotal contribution to the field of factor analysis and his development of innovative AI (artificial intelligence) tools. (wikipedia.org)

###### single

- Merge clusters (r) and (s) into a single cluster to form the next clustering m. (wikipedia.org)

###### approach

- In the following, as a special approach in big data clustering, let us propose simple Gaussian core-based clustering. (wias-berlin.de)

###### distance

- for example, hierarchical clustering builds models based on distance connectivity. (wikipedia.org)
- Typical cluster models include: Connectivity models: for example, hierarchical clustering builds models based on distance connectivity. (wikipedia.org)
- At each step, the two clusters separated by the shortest distance are combined. (wikipedia.org)

###### complete

- Relaxations of the complete connectivity requirement (a fraction of the edges can be missing) are known as quasi-cliques, as in the HCS clustering algorithm . (wikipedia.org)

###### mitochondrial

- Using high-density DNA microarrays and Northern analyses, we demonstrated that the activation of a nutrient-sensing pathway, the hexosamine biosynthesis pathway (HBP), rapidly decreased the expression of a cluster of nuclear-encoded mitochondrial genes involved in skeletal muscle oxidative phosphorylation. (jci.org)
- Population structure in Sweden - A Y-chromosomal and mitochondrial DNA analysis. (blogspot.com)
- Bulbeck (2013) likewise noted that the Andamanese's nuclear DNA clusters with that of other Andamanese Islanders, as they carry Haplogroup D-M174 and maternal mitochondrial Haplogroup M unique to their own. (wikipedia.org)

###### gene

- We will start from the FASTQ files, show how these were aligned to the reference genome, prepare gene expression values as a count matrix by counting the sequenced fragments, perform exploratory data analysis (EDA), perform differential gene expression analysis with DESeq2 , and visually explore the results. (bioconductor.org)
- Mammals possess four similar homeobox gene clusters, HOXA, HOXB, HOXC and HOXD, located on different chromosomes, consisting of 9 to 11 genes arranged in tandem. (wikipedia.org)
- This gene is one of several homeobox HOXD genes located in a cluster on chromosome 2. (wikipedia.org)
- Deletions that remove the entire HOXD gene cluster or the 5' end of this cluster have been associated with severe limb and genital abnormalities. (wikipedia.org)

###### density

- Correlation of QuantStudio™ 3D Digital PCR data with that of the Illumina® cluster density data. (thermofisher.com)
- The Soviet Army has based much of its post-war doctrine on the war experience, and had devoted considerable resources to the analysis of troop density, including these in almost all considerations of wartime operations. (wikipedia.org)
- The physical density of troops in the area of combat is not reflective of the average value for any given command because dispersion of troops tends to follow terrain and tactical considerations of the combat planning, and actual location of troops tends to be in clusters of positions. (wikipedia.org)

###### structural

- This apparent discrepancy between structural and sequence based similarities is really intriguing and requires further analysis. (burnham.org)

###### data

- Table 4: Content Validity Index Data Quantitative Analysis. (ezmortgageohio.cf)
- Afterwards, we will load the full count matrix corresponding to all samples and all data, which is already provided in the same package, and will continue the analysis with that full table. (bioconductor.org)
- In the 1990s she started (together with her team) so called grade data analysis, a science of applying copula and rank methods to problems of correspondence and cluster analysis together with outlier detection. (wikipedia.org)
- In the Institute of Computer Science PAS, she had been leader of the Statistical Data Analysis division for many years. (wikipedia.org)
- For the reasons mentioned above, Elżbieta Pleszczyńska is a strong advocate of explorative data analysis and non-parametric statistics, like Spearman's rho, Kendall's tau, or grade data analysis. (wikipedia.org)
- Grade Models and Methods for Data Analysis with Applications for the Analysis of Data Populations. (wikipedia.org)

###### meta-analysis

- The cardiovascular effect of incretin-based therapies among type 2 diabetes: a systematic review and network meta-analysis. (ox.ac.uk)
- Network meta-analysis was performed, followed by subgroup analysis and meta-regression. (ox.ac.uk)
- Published examples that are used in meta analysis are of variable quality with omissions. (wikipedia.org)

###### cases

- Their age at the moment of death has been determined in both cases on the basis of multi-feature analysis of changes occurring in formation of particular morphologic features of skeleton and teeth. (blogspot.com)
- In July 2010, a team in New Delhi reported a cluster of three cases of Acinetobacter baumannii bearing blaNDM-1 that were found in the intensive care unit of a hospital in Chennai, India, in April 2010. (wikipedia.org)

###### almost

- Based on this distribution of values, it would appear from our preliminary analysis that almost half of the individuals sampled from the Harappa cemetery have isotope values outside the local baseline (0.7158-0.7189). (blogspot.com)