Search results for "Correlation"
showing 10 items of 2282 documents
N-Isopropylacrylamide andN-Isopropylmethacryl-amide: Cloud Points of Mixtures and Copolymers
2001
The cloud point curve of aqueous solutions of poly(N-isopropylacrylamide), poly(N-isopropylmethacrylamide) and their statistical copolymers were determined turbidimetrically. All the Systems demix upon heating at the cloud point temperature and mix reversibly upon cooling. The cloud points are independent of the total concentration of the solutions (dilute range) and of the sample thickness. Mixtures of the homopolymers poly(N-isopropylacrylamide) and poly(N-isopropylmethacrylamide) in water (ternary systems) exhibit two cloud points, which are nearly the same as the cloud points of the two binary systems homopolymer/water. A quantitative correlation was found between the cloud point temper…
SMART: Unique splitting-while-merging framework for gene clustering
2014
© 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named "splitting merging awareness tactics" (SMART), which does not require any a priori knowledge of either the number …
GenClust: A genetic algorithm for clustering gene expression data
2005
Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, …
Data Analysis and Bioinformatics
2007
Data analysis methods and techniques are revisited in the case of biological data sets. Particular emphasis is given to clustering and mining issues. Clustering is still a subject of active research in several fields such as statistics, pattern recognition, and machine learning. Data mining adds to clustering the complications of very large data-sets with many attributes of different types. And this is a typical situation in biology. Some cases studies are also described.
Distance Functions, Clustering Algorithms and Microarray Data Analysis
2010
Distance functions are a fundamental ingredient of classification and clustering procedures, and this holds true also in the particular case of microarray data. In the general data mining and classification literature, functions such as Euclidean distance or Pearson correlation have gained their status of de facto standards thanks to a considerable amount of experimental validation. For microarray data, the issue of which distance function works best has been investigated, but no final conclusion has been reached. The aim of this extended abstract is to shed further light on that issue. Indeed, we present an experimental study, involving several distances, assessing (a) their intrinsic sepa…
Structural clustering of millions of molecular graphs
2014
We propose an algorithm for clustering very large molecular graph databases according to scaffolds (i.e., large structural overlaps) that are common between cluster members. Our approach first partitions the original dataset into several smaller datasets using a greedy clustering approach named APreClus based on dynamic seed clustering. APreClus is an online and instance incremental clustering algorithm delaying the final cluster assignment of an instance until one of the so-called pending clusters the instance belongs to has reached significant size and is converted to a fixed cluster. Once a cluster is fixed, APreClus recalculates the cluster centers, which are used as representatives for…
The Three Steps of Clustering In The Post-Genomic Era
2013
This chapter descibes the basic algorithmic components that are involved in clustering, with particular attention to classification of microarray data.
Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
2020
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…
Probing dynamics of dense suspensions: three-dimensional cross-correlation technique
1997
We describe the realization of a novel three-dimensional (3D) cross-correlation scheme, which provides the possibility to measure dynamic structure factors of highly concentrated colloidal samples without contributions of multiply scattered light. The apparatus is easier to align and more compact than the two-colour cross-correlation apparatus, which is commercially available. This should make the 3D cross-correlation set-up more convenient for routine applications, for example in industrial laboratories. We describe the set-up and discuss some special features of the optical components.
Rotational diffusion of colloid spheres in concentrated suspensions studied by deuteron NMR
1997
We present a study of the application of deuteron-nuclear magnetic resonance spectroscopy (NMR) to the investigation of the rotational diffusion of spherical colloidal particles. We performed NMR pulse experiments on colloidal suspensions of polystyrene latex spheres in water-glycerol mixtures in a wide range of particle volume fractions \ensuremath{\varphi} from the dilute suspension up to \ensuremath{\varphi}=0.504. We have analyzed the stimulated echo NMR signal in the time domain. The full shape of the orientational correlation function deviates from an exponential behavior in the whole \ensuremath{\varphi} range examined. We evaluate the rotational diffusion coefficient and calculate i…