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However, one of the hurdles has been understanding and quantifying the effects of a particular mutation, and how they translate into a given phenotype.

One approach to overcome this is to use robust, accurate and scalable computational methods to understand and correlate structural effects of mutations with disease.

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In recognition of the commitment of our late colleague, Gill-Chin Lim, to the study of humanistic aspects of globalization, the ACSP Global Planners Educators Interest Group (GPEIG) has established an award in his name: The GPEIG Gill-Chin Lim Award for the Best Dissertation on International Planning.

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The nominees must have received their degree in the two years preceding the deadline.

The award committee will evaluate the submissions based on: a) innovative scholarship and perspective that advance the understanding of the diverse processes of international planning in the global context, with a special focus on low-income countries of the “Global South;” b) relation to global cooperation, global social responsibility, global ethics, and respect for global diversity pursued by GPEIG; c) creativity in exploring/proposing international planning alternatives; and d) organization, structure, style, clarity, and originality.

Despite interest in associating polymorphisms with clinical or experimental phenotypes, functional interpretation of mutation data has lagged behind generation of data from modern high-throughput techniques and the accurate prediction of the molecular impact of a mutation remains a non-trivial task.

We present here an integrated knowledge-driven computational workflow designed to evaluate the effects of experimental and disease missense mutations on protein structure and interactions.

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