130 research outputs found
Hierarchical information clustering by means of topologically embedded graphs
We introduce a graph-theoretic approach to extract clusters and hierarchies
in complex data-sets in an unsupervised and deterministic manner, without the
use of any prior information. This is achieved by building topologically
embedded networks containing the subset of most significant links and analyzing
the network structure. For a planar embedding, this method provides both the
intra-cluster hierarchy, which describes the way clusters are composed, and the
inter-cluster hierarchy which describes how clusters gather together. We
discuss performance, robustness and reliability of this method by first
investigating several artificial data-sets, finding that it can outperform
significantly other established approaches. Then we show that our method can
successfully differentiate meaningful clusters and hierarchies in a variety of
real data-sets. In particular, we find that the application to gene expression
patterns of lymphoma samples uncovers biologically significant groups of genes
which play key-roles in diagnosis, prognosis and treatment of some of the most
relevant human lymphoid malignancies.Comment: 33 Pages, 18 Figures, 5 Table
Aspirin inhibits epithelial-to-mesenchymal transition and migration of oncogenic K-ras-expressing non-small cell lung carcinoma cells by down-regulating E-cadherin repressor Slug
21. The Myb oncogene family of transcription factors: potent regulators of hematopoietic cells proliferation and differentiation.
Dissociation between p93-B-myb and p75-c-myb expression during proliferation and differentiation of human myeloid cells lines
B-myb antisense oligonucleotides inhibit proliferation of human hematopoietic cell lines
B-myb antisense oligonucleotides inhibit proliferation of human hematopoietic cell lines
Expression of c-myb and B-myb, but not A-myb, correlates with proliferation in human hematopoietic cells
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