Heuristic algorithm for computing reversal distance with multigene families via binary integer programming

Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE

Efficient spatial clustering algorithm using binary tree

In this paper we present an efficient k-Means clustering algorithm for two dimensional data. The proposed algorithm re-organizes dataset into a form of nested binary tree*. Data items are compared at each node with only two nearest means with respect to each dimension and assigned to the one that has the closer mean. The main intuition of our research is as follows: We build the nested binary tree. Then we scan the data in raster order by in-order traversal of the tree. Lastly we compare data item at each node to the only two nearest means to assign the value to the intendant cluster. In this way we are able to save the computational cost significantly by reducing the number of comparisons with means and also by the least use to Euclidian distance formula. Our results showed that our method can perform clustering operation much faster than the classical ones. © Springer-Verlag Berlin Heidelberg 2005

Further evidence of linkage at 7p22 with familial hyperaldosteronism type II and exclusion of genetic defects in the RBAK coding regions

Once thought rare, primary aldosteronism (PAL) is now reported to be responsible for 5–10% of hypertension. Unlike familial hyperaldosteronism type I (FH-I), FH-II is not glucocorticoidremediable and not associated with the hybrid CYP11B1/CYP11B2 gene mutation. At least five times more common than FH-I, FH-II is clinically indistinguishable from apparently sporadic PAL, suggesting an even higher incidence. Studies performed in collaboration with C Stratakis (NIH, Bethesda) on our largest Australian family (eight affected members) demonstrated linkage at chromosome 7p22. Linkage at this region was also found in a South American family (DNA provided by MI New, Mount Sinai School of Medicine, New York) and in a second Australian family. The combined multipoint LOD score for these 3 families is 4.61 (q = 0) with markers D7S462 and D7S517, providing strong support for this locus harbouring mutations responsible for FH-II. A newly identified recombination event in our largest Australian family has narrowed the region of linkage by 1.8 Mb, permitting exclusion of approximately half the genes residing in the originally reported 5 Mb linked locus. Candidate genes that are involved in cell cycle control are of interest as adrenal hyperplasia and adrenal adenomas are common in FH-II patients. A novel candidate gene in this linked region produces the retinoblastoma-associated Kruppel-associated box protein (RBaK) which interacts with the retinoblastoma gene product to repress the expression of genes activated by members of the E2F family of transcription factors.

Rough Notes on Programming AVR Microcontrollers in C

These notes follow on from the material that you studied in CSSE1000 Introduction to Computer Systems. There you studied details of logic gates, binary numbers and instruction set architectures using the Atmel AVR microcontroller family as an example. In your present course (METR2800 Team Project I), you need to get on to designing and building an application which will include such a microcontroller. These notes focus on programming an AVR microcontroller in C and provide a number of example programs to illustrate the use of some of the AVR peripheral devices.

Geographic variation and positive selection on M7 lysin, an acrosomal sperm protein in mussels (Mytilus spp.)

Successful fertilization in free-spawning marine organisms depends on the interactions between genes expressed on the surfaces of eggs and sperm. Positive selection frequently characterizes the molecular evolution of such genes, raising the possibility that some common deterministic process drives the evolution of gamete recognition genes and may even be important for understanding the evolution of prezygotic isolation and speciation in the marine realm. One hypothesis is that gamete recognition genes are subject to selection for prezygotic isolation, namely reinforcement. In a previous study, positive selection on the gene coding for the acrosomal sperm protein M7 lysin was demonstrated among allopatric populations of mussels in the Mytilus edulis species group (M. edulis, M. galloprovincialis, and M. trossulus). Here, we expand sampling to include M7 lysin haplotypes from populations where mussel species are sympatric and hybridize to determine whether there is a pattern of reproductive character displacement, which would be consistent with reinforcement driving selection on this gene. We do not detect a strong pattern of reproductive character displacement; there are no unique haplotypes in sympatry nor is there consistently greater population structure in comparisons involving sympatric populations. One distinct group of haplotypes, however, is strongly affected by natural selection and this group of haplotypes is found within M. galloprovincialis populations throughout the Northern Hemisphere concurrent with haplotypes common to M. galloprovincialis and M. edulis. We suggest that balancing selection, perhaps resulting from sexual conflicts between sperm and eggs, maintains old allelic diversity within M. galloprovincialis.