Haplotype Inference via Entropy Minimization

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This research explores a novel approach to haplotype inference using entropy minimization techniques. The authors, Ion Mandoiu and Bogdan Pasaniuc from the CSE Department at the University of Connecticut, present algorithms that effectively reduce ambiguity in haplotype reconstruction. By leveraging entropy measures, the proposed methods improve the accuracy of haplotype inference from genotypic data, offering significant advancements for genetic studies and personalized medicine. The paper discusses the theoretical underpinnings, methodological developments, and potential applications in genomics.

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Feb 16, 2026

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Haplotype Inference via Entropy Minimization

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Haplotype Inference by Entropy MinimizationIon Mandoiu and Bogdan Pasaniuc, CSE Department, University of Connecticut

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