Data visualization during the early stages of drug discovery

Multidimensional compound optimization is a new paradigm in the drug discovery process, yielding efficiencies during early stages and reducing attrition in the later stages of drug development. The success of this strategy relies heavily on understanding this multidimensional data and extracting useful information from it. This paper demonstrates how principled visualization algorithms can be used to understand and explore a large data set created in the early stages of drug discovery. The experiments presented are performed on a real-world data set comprising biological activity data and some whole-molecular physicochemical properties. Data visualization is a popular way of presenting complex data in a simpler form. We have applied powerful principled visualization methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), to help the domain experts (screening scientists, chemists, biologists, etc.) understand and draw meaningful decisions. We also benchmark these principled methods against relatively better known visualization approaches, principal component analysis (PCA), Sammon's mapping, and self-organizing maps (SOMs), to demonstrate their enhanced power to help the user visualize the large multidimensional data sets one has to deal with during the early stages of the drug discovery process. The results reported clearly show that the GTM and HGTM algorithms allow the user to cluster active compounds for different targets and understand them better than the benchmarks. An interactive software tool supporting these visualization algorithms was provided to the domain experts. The tool facilitates the domain experts by exploration of the projection obtained from the visualization algorithms providing facilities such as parallel coordinate plots, magnification factors, directional curvatures, and integration with industry standard software. © 2006 American Chemical Society.

Scientists, trade unions and labour movement policies for science and technology, 1947-1964

This thesis describes the history of the scientific Left beginning with the period of its most extensive influence in the mid-1940s as a movement for the planning of science and ending with the Labour Party's programme of 1964 claiming to harness science and socialism. Its central theme is the external and internal pressures involved in the project to align left-wing politics, trade unions and social responsibility in science. The problematic aspects of this project are examined in the evolution of the Association of Scientific Workers and the World Federation of Scientific Workers as organisations committed to trade union and science policy objectives. This is presented also in the broader context of the Association's attempts to influence the Trade Union Congress's policies for science and technology in a more radical direction. The thesis argues that the shift in the balance of political forces in the labour movement, in the scientific community and in the state brought about by the Cold War was crucial in frustrating these endeavours. This led to alternative, but largely unsuccessful attempts, in the form of the Engels Society and subsequently Science for Peace to create the new expressions of the left-wing politics of science. However, the period 1956-1964 was characterised by intensive interest within the Labour Party in science and technology which reopened informal channels of political influence for the scientific Left. This was not matched by any radical renewal within the Association or the Trade Union Congress and thus took place on a narrower basis and lacked the democratic aspects of the earlier generation of socialist science policy.