Electron emission from arrays of carbon nanotubes/fibres

The overall aim of this work is to produce arrays of field emitting microguns, based on carbon nanotubes, which can be utilised in the manufacture of large area field emitting displays, parallel e-beam lithography systems and electron sources for high frequency amplifiers. This paper will describe the work carried out to produce patterned arrays of aligned multiwall carbon nanotubes (MWCNTs) using a dc plasma technique and a Ni catalyst. We will discuss how the density of the carbon nanotube/fibres can be varied by reducing the deposition yield through nickel interaction with a diffusion layer or by direct lithographic patterning of the Ni catalyst to precisely define the position of each nanotube/fibre. Details of the field emission behaviour of the different arrays of MWCNTS will also be presented. © 2002 Published by Elsevier Science B.V.

Gene function prediction from synthetic lethality networks via ranking on demand.

MOTIVATION: Synthetic lethal interactions represent pairs of genes whose individual mutations are not lethal, while the double mutation of both genes does incur lethality. Several studies have shown a correlation between functional similarity of genes and their distances in networks based on synthetic lethal interactions. However, there is a lack of algorithms for predicting gene function from synthetic lethality interaction networks. RESULTS: In this article, we present a novel technique called kernelROD for gene function prediction from synthetic lethal interaction networks based on kernel machines. We apply our novel algorithm to Gene Ontology functional annotation prediction in yeast. Our experiments show that our method leads to improved gene function prediction compared with state-of-the-art competitors and that combining genetic and congruence networks leads to a further improvement in prediction accuracy.