A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

Background: Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure.

Exploring the transcriptomic variation caused by the Finnish founder mutation of lysinuric protein intolerance (LPI).

Lysinuric protein intolerance (LPI) is an autosomal recessive disorder caused by mutations in cationic amino acid transporter gene SLC7A7. Although all Finnish patients share the same homozygous mutation, their clinical manifestations vary greatly. The symptoms range from failure to thrive, protein aversion, anemia and hyperammonaemia, to immunological abnormalities, nephropathy and pulmonary alveolar proteinosis.

Altered expression of p120catenin predicts poor outcome in invasive breast cancer.

Purpose: The study focuses on p120catenin, a regulator of cell adhesion, which has previously been described in many malignancies and suggested with a role in invasion and metastatic behaviour. In this study, we investigate the role of altered immunoexpression of p120catenin isoforms in the prognosis of invasive breast cancer (n = 351).

Methods: We used cDNA microarrays to screen differences in gene expression in invasive breast cancer in general, and between local and metastasized disease particularly.

Proliferation marker securin identifies favourable outcome in invasive ductal breast cancer.

We introduce a new proliferation marker, securin (pituitary tumour-transforming 1 (PTTG1)), analysed in invasive ductal breast carcinomas by cDNA microarrays and immunohistochemistry. In cDNA microarray of a total of 4000 probes of genes, securin was revealed with a significant change in expression among the several proliferation-related genes studied. The value of securin as a proliferation marker was verified immunohistochemically (n=44) in invasive ductal breast cancer.

Missing value imputation improves clustering and interpretation of gene expression microarray data.

Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value imputation approaches are available to the microarray users and new ones are constantly being developed, there is no general consensus on how to choose between the different methods since their performance seems to vary drastically depending on the dataset being used.

Results: We show that this discrepancy can mostly be attributed to the way in which imputation methods have traditionally been developed and evaluated.