The zero exemplar distance problem

Given two genomes with duplicate genes, \textsc{Zero Exemplar Distance} is the problem of deciding whether the two genomes can be reduced to the same genome without duplicate genes by deleting all but one copy of each gene in each genome. Blin, Fertin, Sikora, and Vialette recently proved that \textsc{Zero Exemplar Distance} for monochromosomal genomes is NP-hard even if each gene appears at most two times in each genome, thereby settling an important open question on genome rearrangement in the exemplar model. In this paper, we give a very simple alternative proof of this result. We also study the problem \textsc{Zero Exemplar Distance} for multichromosomal genomes without gene order, and prove the analogous result that it is also NP-hard even if each gene appears at most two times in each genome. For the positive direction, we show that both variants of \textsc{Zero Exemplar Distance} admit polynomial-time algorithms if each gene appears exactly once in one genome and at least once in the other genome. In addition, we present a polynomial-time algorithm for the related problem \textsc{Exemplar Longest Common Subsequence} in the special case that each mandatory symbol appears exactly once in one input sequence and at least once in the other input sequence. This answers an open question of Bonizzoni et al. We also show that \textsc{Zero Exemplar Distance} for multichromosomal genomes without gene order is fixed-parameter tractable if the parameter is the maximum number of chromosomes in each genome.Comment: Strengthened and reorganize

Critical Issues in the Development of Health Information Systems in Supporting Environmental Health: A Case Study of Ciguatera

Emerging environmental pressures resulting from climate change and globalization challenge the capacity of health information systems (HIS) in the Pacific to inform future policy and public health interventions. Ciguatera, a globally common marine food-borne illness, is used here to illustrate specific HIS challenges in the Pacific and how these might be overcome proactively to meet the changing surveillance needs resulting from environmental change.We review and highlight inefficiencies in the reactive nature of existing HIS in the Pacific to collect, collate, and communicate ciguatera fish poisoning data currently used to inform public health intervention. Further, we review the capacity of existing HIS to respond to new data needs associated with shifts in ciguatera disease burden likely to result from coral reef habitat disruption.Improved knowledge on the ecological drivers of ciguatera prevalence at local and regional levels is needed, combined with enhanced surveillance techniques and data management systems, to capture environmental drivers as well as health outcomes data.The capacity of public HIS to detect and prevent future outbreaks is largely dependent on the future development of governance strategies that promote proactive surveillance and health action. Accordingly, we present an innovative framework from which to stimulate scientific debate on how this might be achieved by using existing larger scale data sets and multidisciplinary collaborations

Author manuscript, published in "Proc. 3rd Workshop on Algorithms and Computation (WALCOM 2009), Kolkata: Inde (2009)" The Exemplar Breakpoint Distance for non-trivial genomes cannot be approximated

Abstract. A promising and active field of comparative genomics consists in comparing two genomes by establishing a one-to-one correspondence (i.e., a matching) between their genes. This correspondence is usually chosen in order to optimize a predefined measure. One such problem is the Exemplar Breakpoint Distance problem (or EBD, for short), which asks, given two genomes modeled by signed sequences of characters, to keep and match exactly one occurrence of each character in the two genomes (a process called exemplarization), so as to minimize the number of breakpoints of the resulting genomes. Bryant [6] showed that EBD is NP-complete. In this paper, we close the study of the approximation of EBD by showing that no approximation factor can be derived for EBD considering non-trivial genomes – i.e. genomes that contain duplicated genes.