Clustering of high throughput gene expression data
High throughput biological data need to be processed, analyzed, and interpreted to address
problems in life sciences. Bioinformatics, computational biology, and systems biology deal …
problems in life sciences. Bioinformatics, computational biology, and systems biology deal …
[HTML][HTML] A scaleable projection‐based branch‐and‐cut algorithm for the p‐center problem
The p-center problem (pCP) is a fundamental problem in location science, where we are
given customer demand points and possible facility locations, and we want to choose p of …
given customer demand points and possible facility locations, and we want to choose p of …
A Simple but Powerful Heuristic Method for Accelerating -Means Clustering of Large-Scale Data in Life Science
K Ichikawa, S Morishita - IEEE/ACM transactions on …, 2014 - ieeexplore.ieee.org
K-means clustering has been widely used to gain insight into biological systems from large-
scale life science data. To quantify the similarities among biological data sets, Pearson …
scale life science data. To quantify the similarities among biological data sets, Pearson …
Automated generation of user-tailored and time-sensitive music playlists
M Furini, J Martini, M Montangero - 2019 16th IEEE Annual …, 2019 - ieeexplore.ieee.org
Streaming music platforms have changed the way people listen to music. Today, we can
access to millions of songs with a simple internet-connected device. The drawback is that …
access to millions of songs with a simple internet-connected device. The drawback is that …
CLIC: clustering analysis of large microarray datasets with individual dimension-based clustering
Large microarray data sets have recently become common. However, most available
clustering methods do not easily handle large microarray data sets due to their very large …
clustering methods do not easily handle large microarray data sets due to their very large …
Finding best algorithmic components for clustering microarray data
The analysis of microarray data is fundamental to microbiology. Although clustering has long
been realized as central to the discovery of gene functions and disease diagnostic …
been realized as central to the discovery of gene functions and disease diagnostic …
Amic@: all microarray clusterings@ once
Abstract The AMIC@ Web Server offers a light-weight multi-method clustering engine for
microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user …
microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user …
Internal evaluation measures as proxies for external indices in clustering gene expression data
Several external indices that use information not present in the dataset were shown to be
useful for evaluation of representative based clustering algorithms. However, such …
useful for evaluation of representative based clustering algorithms. However, such …
Clustering techniques for revealing gene expression patterns
C Gallo, V Capozzi - … of Information Science and Technology, Third …, 2015 - igi-global.com
The possible applications of modeling and simulation in the field of bioinformatics are very
extensive, ranging from understanding basic metabolic paths to exploring genetic variability …
extensive, ranging from understanding basic metabolic paths to exploring genetic variability …
Ensemble clustering for biological datasets
Recent technologies and tools generated excessive data in bioinformatics domain. For
example, microarrays measure expression levels of ten thousands of genes simultaneously …
example, microarrays measure expression levels of ten thousands of genes simultaneously …