this paper proposes a two-step approach for characterizing the reservoir properties of the world’s largest non-associated gas reservoir. this approach integrates geological and petrophysical data and compares them with the field performance analysis to achieve a practical electrofacies clustering. porosity and permeability prediction is done on the basis of linear functions, succeeding the elec...

MOTIVATION Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, sin...

As part of the Genes, Environment and Development Initiative, the Minnesota Center for Twin and Family Research (MCTFR) undertook a genome-wide association study, which we describe here. A total of 8,405 research participants, clustered in four-member families, have been successfully genotyped on 527,829 single nucleotide polymorphism (SNP) markers using lllumina's Human660W-Ouad array. Quality...

The huge amount of information stored in text form makes methods that deal with texts really interesting. This thesis focuses on dealing with texts using compression distances. More specifically, the thesis takes a small step towards understanding both the nature of texts and the nature of compression distances. Broadly speaking, the way in which this is done is exploring the effects that sever...

This chapter describes the basic concepts and application of a family of methods for class discovery, generically known as clustering, applied to microarray data. Although many clustering methods exist, only a few have been extensively used for microarray data analysis (among them I will revise hierarchical clustering, k-means, SOM, SOTA and model-based clustering). Key aspects in clustering su...

Clustering, which is partitioning data into groups of similar objects, has a wide range of applications. In many cases unstructured data makes up a significant part of the input. Attempting to cluster such part of the data, which can be referred to as noise, can disturb the clustering on the remaining domain points. Despite the practical need for a framework of clustering that allows a portion ...

We describe a family of heuristics-based clustering strategies to support the merging of XML data from multiple sources. As part of this research, we have developed a comprehensive classification for schematic and semantic conflicts that can occur when reconciling related XML data from multiple sources. Given the fact that element clustering is compute-intensive, especially when comparing large...

This paper introduces a family of modular, self-similar, small-world graphs with clustering zero. Relevant properties of this family are comparable to those of some networks associated with technological systems with a low clustering, like the power grid or some electronic circuits. Moreover, the graphs are outerplanar and it is know that many algorithms that are NP-complete for general graphs ...