Gene expression through fuzzy k means clustering. Medical search. Frequent questions

One of the most widely used fuzzy clustering algorithms is the Fuzzy C-means clustering (FCM) algorithm. (wikipedia.org)
The fuzzy c-means algorithm is very similar to the k-means algorithm: Choose a number of clusters. (wikipedia.org)
Repeat until the algorithm has converged (that is, the coefficients' change between two iterations is no more than ε {\displaystyle \varepsilon } , the given sensitivity threshold) : Compute the centroid for each cluster (shown below). (wikipedia.org)
After preprocessing, Fuzzy C-means (FCM) algorithm is applied for clustering the data. (ijma.info)
The clusters were generated by means of unsupervised clustering of SILAC ratios with the fuzzy c-means algorithm. (idhinhibitor.com)
In this regard, a gene clustering algorithm, termed as robust rough-fuzzy c-means, is proposed judiciously integrating the merits of rough sets and fuzzy sets. (iitj.ac.in)
An efficient method is proposed to select initial prototypes of different gene clusters, which enables the proposed c-means algorithm to converge to an optimum or near optimum solutions and helps to discover coexpressed gene clusters. (iitj.ac.in)
As far as our knowledge goes, this is the first fuzzy clustering algorithm for sequential data. (mecs-press.net)
2]Anuradha, J., B.K.Tripathy and A. Sinha: Hybrid Clustering algorithm using Possibilistic Rough C-means, International journal of Pharma and Bio-informatics, vol.6, issue 4, (2015), pp.799-810. (mecs-press.net)
3]Anuradha, J. and Tripathy, B.K.: An optimal rough fuzzy clustering algorithm using PSO, Int. Jour. (mecs-press.net)
16]Guralnik, V. and Karypis, G., A scalable algorithm for clustering sequential data, In: Proceedings of the 1st IEEE International Conference on Data Mining- ICDM, (2001), 179- 186. (mecs-press.net)
This allows the data to be visualized and an analyst to detect the general trends determined by the particular clustering algorithm employed. (biomedcentral.com)
7 -6 -5 -4 -3 -2 -1 0 1 2 three four five 6494Phosphorylation and Ubiquitylation Dynamics in TOR Signalingbehavior making use of a fuzzy c-means algorithm (Figs. 3B and 3C) (40, 48). (atminhibitor.com)
In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. (biomedcentral.com)
A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. (biomedcentral.com)
This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. (biomedcentral.com)
Fuzzy KNearest Neighbour Algorithm - Only a bit less accurate the far more complicated algorithms. (powershow.com)
A Survey on k-Means Clustering Algorithm Using Different Ranking Methods in Data Mining? (researchbib.com)
A Survey on Various Clustering Techniques with K-means Clustering Algorithm in Detail? (researchbib.com)
The algorithm can effectively remove the noise data reflected by calculating the topological structure characteristic values in the PPI network through the similarity of gene expression patterns, and also properly use the information hidden in the gene expression data. (biomedcentral.com)
ECTG(Evolutionary Clustering Algorithm Based on Topological Features and Gene expression data for Protein Complex Identification). (biomedcentral.com)
This method is based on evolutionary algorithm (EA), which effectively fuses protein topology and gene expression data. (biomedcentral.com)

A practical comparison of two K-Means clustering algorithms. (chinagene.cn)
The clustering algorithms used to analyze the information contained in protein-protein interaction network are effective ways to explore the characteristics of protein functional modules. (biomedcentral.com)
More and more clustering algorithms are proposed to identify protein complexes with the constantly development of proteomics. (biomedcentral.com)

Classification of Microarray Gene Expression Data using Weighted Grey Wolf Optimizer based Fuzzy Clustering", TENCON 2019, 17 - 20 October 2019 at Hotel Grand Hyatt, Bolgatty, Kochi, Kerala, India. (nitmz.ac.in)
Color Image Segmentation using Adaptive Particle Swarm Optimization and Fuzzy C-means" International conference in Recent Trends on Electronics & Computer Science(ICRTECS-2019), 18-19th March, 2019, NIT Silchar. (nitmz.ac.in)
Swathypriyadharsini Palaniswamy, K. Premalatha Kandhasamy, "Rough fuzzy cuckoo search for triclustering microarray gene expression data", Turkish Journal of Electrical Engineering , No. 2019(27), pages. (bitsathy.ac.in)

As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we performed a DNA microarray analysis of human whole blood samples from a five-time point study of subjects administered ethanol orally, followed by breathalyzer analysis, to monitor blood alcohol concentration (BAC) to discover significant gene expression changes in response to the ethanol exposure. (biomedcentral.com)
Microarray analysis of samples representing 0%, 0.04%, 0.08%, return to 0.04%, and 0.02% wt/vol BAC showed that changes in gene expression could be detected across the time course. (biomedcentral.com)
The candidate genes of interest (GOI) identified from the microarray analysis and clustered by expression pattern across the five BAC points showed seven coordinately expressed groups. (biomedcentral.com)

12] Koumakpayi IH, Le Page C, Mes-Masson AM, Saad F. Hierarchical clustering of immunohistochemical analysis of the activated ErbB/PI3K/Akt/NF-κB signalling pathway and prognostic significance in prostate cancer. (chinagene.cn)

For the clusters that contained up-regulated phosphorylation web pages, distinguishably unique sequence motif enrichment was observed, suggesting that these websites could possibly be targeted by kinases which can be inhibited by TOR. (idhinhibitor.com)
B, the bar chart shows the distribution of phosphorylation web pages into seven clusters, whereMolecular Cellular Proteomics 13. (atminhibitor.com)
Regulated phosphorylation web pages were clustered into six PI4KIIIβ Storage & Stability Distinct profiles according to the temporal behavior of those web sites. (atminhibitor.com)

Individual expression patterns are extraordinarily diverse, but by supplementing qualitative in situ hybridization data with quantitative microarray time-course data using a hybrid clustering strategy, we identify groups of genes with similar expression. (biomedcentral.com)
Identifying coexpressed groups of genes represents the basic challenge in gene clustering problem. (iitj.ac.in)

In fuzzy clustering, data points can potentially belong to multiple clusters. (wikipedia.org)
In non-exclusive clusterings, points may belong to multiple clusters. (powershow.com)

It is much cheaper to focus only on the expression of a few genes rather than on thousands of genes for diagnosis [ 16 ]. (biomedcentral.com)

Search among the known diseases for "Waardenburg", or enter the human genes linked to Waardenburg (Entrez gene IDs 4286, 5077, 6591, 7299) to get a feel for how this works. (marcottelab.org)
Reactome ), which we've seen before, links human genes according to reactions and pathways, and also calculated functional linkages from various high-throughput data. (marcottelab.org)

Rough-fuzzy clustering for grouping functionally similar genes from microarray data. (iitj.ac.in)

However, the range of gene expression patterns, the extent of the correlation of expression with function, and the classes of genes whose spatial expression are tightly regulated have been unclear due to the lack of an unbiased, genome-wide survey of gene expression patterns. (biomedcentral.com)
1] Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. (chinagene.cn)

Exploring Differential Evolution and Particle Swarm Optimization to De-velop some Symmetry based automatic clustering techniques: Application to gene clustering", Neural Computing and Applications vol.27,no.10,pp.1-23,2016. (nitmz.ac.in)

Five of the seven clusters showed links to the p38 MAPK pathway. (biomedcentral.com)

While the concept of lower and upper approximations of rough sets deals with uncertainty, vagueness, and incompleteness in cluster definition, the integration of probabilistic and possibilistic memberships of fuzzy sets enables efficient handling of overlapping partitions in noisy environment. (iitj.ac.in)
The concept of possibilistic lower bound and probabilistic boundary of a cluster, introduced in robust rough-fuzzy c-means, enables efficient selection of gene clusters. (iitj.ac.in)

The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. (biomedcentral.com)
This implies that classifiers can be built with a smaller subset of genes. (biomedcentral.com)

Microarray data was analyzed in a pipeline fashion to summarize and normalize and the results evaluated for relative expression across time points with multiple methods. (biomedcentral.com)
Class prediction, involving the assignment of labels to samples based on their expression patterns, is typically based on statistical or supervised machine learning methods. (biomedcentral.com)

E, sequence motifs for distinct clusters had been generated utilizing IceLogo and s. (idhinhibitor.com)
IceLogo (41) was utilised to analyze sequence motifs within the regulated phosphorylation internet site clusters (Fig. 3E). (atminhibitor.com)

A gene's expression pattern can be defined as a series of differential accumulations of its products in subsets of cells as development progresses. (biomedcentral.com)
13] Ma SG, Kosorok MR. Identification of differential gene pathways with principal component analysis. (chinagene.cn)
The amplified cDNA was used in microarray and quantitative real-time polymerase chain reaction (RT-qPCR) analyses to evaluate differential gene expression. (biomedcentral.com)
Differential expression of genes is analyzed statistically and genes are assigned to various classes which may (or not) enhance the understanding of underlying biological processes. (biomedcentral.com)

Analysis showed function-based networks, shared transcription factor binding sites and signaling pathways for members of the clusters. (biomedcentral.com)
The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. (biomedcentral.com)

Clusters are identified via similarity measures. (wikipedia.org)
As a result, in this paper, we used the fuzzy set technique to introduce a similarity measure, which we termed as Kernel and Set Similarity Measure to find the similarity of sequential data and generate overlapping clusters. (mecs-press.net)
Calculating the similarity between gene expression patterns (co-expression degree) by using gene expression data has an important guiding function in understanding the relationship between the corresponding proteins of the gene, and can help to identify whether different proteins have same or similar functions and whether they can be composed as protein complexes or functional modules. (biomedcentral.com)

Clustering or cluster analysis involves assigning data points to clusters such that items in the same cluster are as similar as possible, while items belonging to different clusters are as dissimilar as possible. (wikipedia.org)

The challenge in dealing with microarray data lies in the fact that there are orders of magnitude differences between the number of samples (typically less than a hundred) and the number of genes (typically tens of thousands) that are studied. (biomedcentral.com)

Relational Analysis of CpG Islands Methylation and Gene Expression in Human Lymphomas Using Possibilistic C-Means Clustering and Modified Cluster Fuzzy Density. (auth.gr)
A cluster is a dense region of points, which is separated by low-density regions, from other regions of high density. (powershow.com)

Clusters four and 5 showed increases and decreases in phosphorylation, respectively, suggesting that these phosphorylation web sites are possibly regulated as a consequence of alterations downstream of TOR inhibition, for example, by regulating the activity of downstream kinases and phosphatases upon rapamycin treatment. (atminhibitor.com)
Variance stabilizing transformations applied in conjunction with standard CA and the use of "power deflation" smoothing both improve performance in downstream clustering tasks. (ne.jp)

With fuzzy c-means, the centroid of a cluster is the mean of all points, weighted by their degree of belonging to the cluster, or, mathematically, c k = ∑ x w k ( x ) m x ∑ x w k ( x ) m , {\displaystyle c_{k}={{\sum _{x}{w_{k}(x)}^{m}x} \over {\sum _{x}{w_{k}(x)}^{m}}},} where m is the hyper- parameter that controls how fuzzy the cluster will be. (wikipedia.org)

Saha, S., Das, R. & Pakray, P. "Aggregation of multi-objective fuzzy symmetry-based clustering techniques for improving gene and cancer classification"Soft Comput (2017). (nitmz.ac.in)

Fuzzy c-means (FCM) clustering was developed by J.C. Dunn in 1973, and improved by J.C. Bezdek in 1981. (wikipedia.org)

High throughput gene expression time-course experiments provide a perspective on biological functioning recognized as having huge value for the diagnosis, treatment, and prevention of diseases. (biomedcentral.com)
Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. (scholarly.org)
Alternatively, a reduced set of genes may be singled out and used as biomarkers for diagnosis and prognosis. (biomedcentral.com)

In non-fuzzy clustering (also known as hard clustering), data are divided into distinct clusters, where each data point can only belong to exactly one cluster. (wikipedia.org)
C, six distinct temporal patterns were generated, as well as the match in between the profile of the cluster and phosphorylation alter is described by the membership worth. (idhinhibitor.com)
Distinct associations of GO terms inside each and every cluster (Fig. 3D and supplemental Figs. S2H 2M) indicated that phosphorylation internet sites with specific temporal profiles had been involved inside the regulation of unique biological processes. (atminhibitor.com)

Enrichment evaluation for GO biological method terms overrepresented in these clusters revealed quite a few terms connected to telomere modifications, cell cycle, and DNA replication (Fig. 3D). (idhinhibitor.com)
8] Dembélé D, Kastner P. Fuzzy C-means method for clustering microarray data. (chinagene.cn)
Scasa, an isoform-level quantification method for high-throughput single-cell RNA sequencing by exploiting the concepts of transcription clusters and isoform paralogs. (ne.jp)
Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. (biomedcentral.com)
Fuzzy grouping method. (youdao.com)
Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. (biomedcentral.com)

A rough set based clustering of sequential data was proposed by Kumar et al recently. (mecs-press.net)

Cell and tissue specific gene expression is a defining feature of embryonic development in multi-cellular organisms. (biomedcentral.com)
We describe the tissue specificity of gene expression at each stage range using selected terms from a controlled vocabulary (CV) for embryo anatomy [ 18 ]. (biomedcentral.com)
Tissue clustering, the process of grouping related samples according to gene expression levels, is very useful to the research of gene unknown functions, and is one of the most important foundation of microarray study. (youdao.com)

RT-qPCR was used with representative genes to confirm relative transcript levels across time to those detected in microarrays. (biomedcentral.com)

We determined and documented embryonic expression patterns for 6,003 (44%) of the 13,659 protein-coding genes identified in the Drosophila melanogaster genome with over 70,000 images and controlled vocabulary annotations. (biomedcentral.com)
There are several reasons for choosing Drosophila melanogaster as an organism for the global study of gene expression during embryonic development. (biomedcentral.com)

We have developed a new exploratory analysis tool, MaTSE, that allows users to find unexpected patterns of temporal activity in gene expression time-series data. (biomedcentral.com)
A general methodology employed for the analysis of large scale gene expression data has been to use filtering and clustering to disregard less interesting parts of the data and generate a more 'manageable' data abstraction [ 6 ]. (biomedcentral.com)
4] Sherlock G. Analysis of large-scale gene expression data. (chinagene.cn)
The analysis approach for this study serves as a workflow to investigate the biology linked to expression changes across a time course and from these changes, to identify target genes that could serve as biomarkers linked to pilot performance. (biomedcentral.com)
Through integrative comparative analysis, we define a consensus vocabulary and a consistent set of gene signatures discriminating against the transcriptomic cell types and subtypes of the human prefrontal cortex. (nature.com)

Regulation of gene expression in time and space is a major driving force of this process. (biomedcentral.com)
This cluster incorporated GO terms like "signal transduction," "ubiquitinprotein ligase activity," and "positive regulation of gene expression" (supplemental Fig. S2H). (atminhibitor.com)
Clusters 2 and three contained sites at which the directionality of phosphorylation dynamics switched more than time, suggesting that these internet sites may be subject to a feedback regulation or controlled by a complicated regulatory program. (atminhibitor.com)

Fuzzy clustering (also referred to as soft clustering or soft k-means) is a form of clustering in which each data point can belong to more than one cluster. (wikipedia.org)
These membership grades indicate the degree to which data points belong to each cluster. (wikipedia.org)

In many cases, the wild-type gene expression pattern has informed the interpretation of the phenotype produced by its mutation [ 13 ]. (biomedcentral.com)
Candidate genes showing distinctive expression patterns in response to ethanol were clustered by pattern and further analyzed for related function, pathway membership and common transcription factor binding within and across clusters. (biomedcentral.com)
As part of the decomposition, the relative contribution of these patterns to the transcriptome of each cell is estimated, along with the relative contribution of genes discriminating each pattern from the others. (nature.com)

The resulting software combines a variety of visualization and interaction techniques which work together to allow biologists to explore their data and reveal temporal patterns of gene activity. (biomedcentral.com)
A final evaluation demonstrated the tools effectiveness in allowing users to find unexpected temporal patterns and the benefits of functionality such as the overlay of gene groupings and the ability to store patterns. (biomedcentral.com)

ASD occurs more often in people who have certain genetic conditions and how genes interact with each other and with environmental factors, such as family medical conditions, parental age and complications during birth or pregnancy. (ijma.info)

Gene expression data clustering is one of the important tasks of functional genomics as it provides a powerful tool for studying functional relationships of genes in a biological process. (iitj.ac.in)
Here, a rise then a fall in expression found over a particular interval could suggest that a group of genes are related to a particular biological process and that that process is associated with the experimental conditions. (biomedcentral.com)

In the limit m → 1 {\displaystyle m\rightarrow 1} , the memberships, w i j {\displaystyle w_{ij}} , converge to 0 or 1, and the Fuzzy C-means objective coincides with that of K-means. (wikipedia.org)

13]Dunn, J. C., A fuzzy relative of the ISODATA process and its use in detecting compact, well-separated clusters, J. Cybernetics, 3 (1974) 32-57. (mecs-press.net)

D, the heatmap shows the clustering of GO terms linked using the temporal clusters from C. A a lot more detailed description with the enriched GO terms is provided in supplemental Figs. S2H 2M. (idhinhibitor.com)

The yeast-invertase Suc2 gene, from Saccharomyces cere visiae , was overexpressed in either the cytosol, vacuole or apoplast of transgenic tobacco plants. (sun.ac.za)

This cluster was enriched in GO terms related to nutrient deprivation, such as "cellular response to amino acid starvation," "amino acid transport," "autophagy," and "autophagic vacuole assembly" (supplemental Fig. S2M). (atminhibitor.com)

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Chemicals and Drugs74

Analytical, Diagnostic and Therapeutic Techniques and Equipment35

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