Helsinki University of Technology

About: Helsinki University of Technology is a based out in . It is known for research contribution in the topics: Artificial neural network & Finite element method. The organization has 8962 authors who have published 20136 publications receiving 723787 citations. The organization is also known as: TKK & Teknillinen korkeakoulu.

Identification of differentially expressed genes in pulmonary adenocarcinoma by using cDNA array

Abstract: No clear patterns in molecular changes underlying the malignant processes in lung cancer of different histological types have been found so far. To identify critical genes in lung cancer progression we compared the expression profile of cancer related genes in 14 pulmonary adenocarcinoma patients with normal lung tissue by using the cDNA array technique. Principal component analyses (PCA) and permutation test were used to detect the differentially expressed genes. The expression profiles of 10 genes were confirmed by semi-quantitative real-time RT–PCR. In tumour samples, as compared to normal lung tissue, the up-regulated genes included such known tumour markers as CCNB1, PLK, tenascin, KRT8, KRT19 and TOP2A. The down-regulated genes included caveolin 1 and 2, and TIMP3. We also describe, for the first time, down-regulation of the interesting SOCS2 and 3, DOC2 and gravin. We show that silencing of SOCS2 is not caused by methylation of exon 1 of the gene. In conclusion, by using the cDNA array technique we were able to reveal marked differences in the gene expression level between normal lung and tumour tissue and find possible new tumour markers for pulmonary adenocarcinoma.

Polyunsaturation in lipid membranes: dynamic properties and lateral pressure profiles.

Abstract: We elucidate the influence of unsaturation on single-component membrane properties, focusing on their dynamical aspects and lateral pressure profiles across the membrane. To this end, we employ atomistic molecular dynamics simulations to study five different membrane systems with varying degrees of unsaturation, starting from saturated membranes and systematically increasing the level of unsaturation, ending up with a bilayer of phospholipids containing the docosahexaenoic acid. For an increasing level of unsaturation, we find considerable effects on dynamical properties, such as accelerated dynamics of the phosphocholine head groups and glycerol backbones and speeded up rotational dynamics of the lipid molecules. The lateral pressure profile is found to be altered by the degree of unsaturation. For an increasing number of double bonds, the peak in the middle of the bilayer decreases. This is compensated for by changes in the membrane-water interface region in terms of increasing peak heights of the lateral pressure profile. Implications of the findings are briefly discussed.

Dynamic asset trees and portfolio analysis

Abstract: The minimum spanning tree, based on the concept of ultrametricity, is constructed from the correlation matrix of stock returns and provides a meaningful economic taxonomy of the stock market. In order to study the dynamics of this asset tree we characterise it by its normalised length and by the mean occupation layer, as measured from an appropriately chosen centre called the `central node'. We show how the tree evolves over time, and how it shrinks strongly, in particular, during a stock market crisis. We then demonstrate that the assets of the optimal Markowitz portfolio lie practically at all times on the outskirts of the tree. We also show that the normalised tree length and the investment diversification potential are very strongly correlated.

Asset Trees and Asset Graphs in Financial Markets

Abstract: This paper introduces a new methodology for constructing a network of companies called a dynamic asset graph. This is similar to the dynamic asset tree studied recently, as both are based on correlations between asset returns. However, the new modified methodology does not, in general, lead to a tree but a disconnected graph. The asset tree, due to the minimum spanning tree criterion, is forced to "accept" edge lengths that are far less optimal (longer) than the asset graph, thus resulting in higher overall length for the tree. The same criterion also causes asset trees to be more fragile in structure when measured by the single-step survival ratio. Over longer time periods, in the beginning the asset graph decays more slowly than the asset tree, but in the long run the situation is reversed. The vertex degree distributions indicate that the possible scale free behavior of the asset graph is not as evident as it is in the case of the asset tree.