Advances in Nuclear Magnetic Resonance for Drug Discovery

Background—Drug discovery is a complex and unpredictable endeavor with a high failure rate. Current trends in the pharmaceutical industry have exasperated these challenges and are contributing to the dramatic decline in productivity observed over the last decade. The industrialization of science by forcing the drug discovery process to adhere to assembly-line protocols is imposing unnecessary restrictions, such as short project time-lines. Recent advances in nuclear magnetic resonance are responding to these self-imposed limitations and are providing opportunities to increase the success rate of drug discovery. Objective/Method—A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented. These include fast NMR data collection protocols and high-throughput protein structure determination, rapid protein-ligand co-structure determination, lead discovery using fragment-based NMR affinity screens, NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FASTNMR. Conclusion—NMR is a critical component of the drug discovery process, where the versatility of the technique enables it to continually expand and evolve its role. NMR is expected to maintain this growth over the next decade with advancements in automation, speed of structure calculation, incell imaging techniques, and the expansion of NMR amenable targets

An incremental approach to genetic algorithms based classification

Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental learning with statistical algorithms or neural networks, rather than evolutionary algorithms. The work in this paper employs genetic algorithms (GAs) as basic learning algorithms for incremental learning within one or more classifier agents in a multi-agent environment. Four new approaches with different initialization schemes are proposed. They keep the old solutions and use an “integration” operation to integrate them with new elements to accommodate new attributes, while biased mutation and crossover operations are adopted to further evolve a reinforced solution. The simulation results on benchmark classification data sets show that the proposed approaches can deal with the arrival of new input attributes and integrate them with the original input space. It is also shown that the proposed approaches can be successfully used for incremental learning and improve classification rates as compared to the retraining GA. Possible applications for continuous incremental training and feature selection are also discussed

Incremental multiple objective genetic algorithms

This paper presents a new genetic algorithm approach to multi-objective optimization problemsIncremental Multiple Objective Genetic Algorithms (IMOGA). Different from conventional MOGA methods, it takes each objective into consideration incrementally. The whole evolution is divided into as many phases as the number of objectives, and one more objective is considered in each phase. Each phase is composed of two stages: first, an independent population is evolved to optimize one specific objective; second, the better-performing individuals from the evolved single-objective population and the multi-objective population evolved in the last phase are joined together by the operation of integration. The resulting population then becomes an initial multi-objective population, to which a multi-objective evolution based on the incremented objective set is applied. The experiment results show that, in most problems, the performance of IMOGA is better than that of three other MOGAs, NSGA-II, SPEA and PAES. IMOGA can find more solutions during the same time span, and the quality of solutions is better

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

Explicitness and ellipsis as features of conversational style in British English and Ecuadorian Spanish

In this article I examine differences in conversational style between British English and Ecuadorian Spanish which can be the source of communication conflict among speakers of these two languages in telephone conversations, and, presumably in other types of interaction. I look at the language of mediated and non-mediated telephone conversations and examine one feature that interacts with indirectness, i.e., the degree of explicitness participants employ to realize similar acts or moves in the two languages. In non-mediated telephone interactions both British English and Ecuadorian Spanish speakers appear to display a preference for the use of explicitness in formulating various telephone management moves. On the other hand, in mediated interactions, while the British appear to favour explicitness, Ecuadorians in the present study, make use of elliptical forms. The latter, however, tend to be accompanied by deference markers. Differences in the use of explicit and elliptical utterances are interpreted as reflecting that, in certain types of interactions, Ecuadorians favour a style that can be characterized as fast and deferential, but possibly rather abrupt to the English, whereas the latter appear to favour a less hurried style which emphasizes the expression of consideration rather than deference

The development of an expert system for the diagnosis of diseases in fibre and dairy goats

This thesis details the development of an expert system for the diagnosis of diseases in fibre and dairy goats. Divided into five sections, five appendices, and a bibliography, this thesis centres on the methods used to build the expert system: the decisions taken at the outset of, and during the course of, development; some of the problems encountered, and the solutions to those problems. A detailed appraisal is made of the development process and suggestions are made for future developments over similar domains (for example, the diagnosis of diseases in animals other than goats). Much emphasis is placed on three topics in particular: the selection of the expert system tool(s) to be used (and the rejection of numerous others); the methodology employed for this selection process; and the methodology used for the process of development. Other topics which are routinely found in texts on expert systems (for example, knowledge elicitation techniques, explanatory facilities, expert system evaluation etc) are dealt with only briefly. However, for the reader interested in further information on these topics, references are made in the text to appropriate sources

Vision Science and Technology at NASA: Results of a Workshop

A broad review is given of vision science and technology within NASA. The subject is defined and its applications in both NASA and the nation at large are noted. A survey of current NASA efforts is given, noting strengths and weaknesses of the NASA program

Intelligent Data Storage and Retrieval for Design Optimisation – an Overview

This paper documents the findings of a literature review conducted by the Sir Lawrence Wackett Centre for Aerospace Design Technology at RMIT University. The review investigates aspects of a proposed system for intelligent design optimisation. Such a system would be capable of efficiently storing (and compressing if required) a range of types of design data into an intelligent database. This database would be accessed by the system during subsequent design processes, allowing for search of relevant design data for re-use in later designs, allowing it to become very efficient in reducing the time for later designs as the database grows in size. Extensive research has been performed, in both theoretical aspects of the project, and practical examples of current similar systems. This research covers the areas of database systems, database queries, representation and compression of design data, geometric representation and heuristic methods for design applications.