Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

Analysis of the CDKN2A, CDKN2B and CDK4 genes in 48 Australian melanoma kindreds

Germline mutations within the cyclin-dependent kinase inhibitor 2A (CDKN2A) gene and one of its targets, the cyclin dependent kinase 4 (CDK4) gene, have been identified in a proportion of melanoma kindreds. In the case of CDK4, only one specific mutation, resulting in the substitution of a cysteine for an arginine at codon 24 (R24C), has been found to be associated with melanoma. We have previously reported the identification of germline CDKN2A mutations in 7/18 Australian melanoma kindreds and the absence of the R24C CDK4 mutation in 21 families lacking evidence of a CDKN2A mutation. The current study represents an expansion of these efforts and includes a total of 48 melanoma families from Australia. All of these families have now been screened for mutations within CDKN2A and CDK4, as well as for mutations within the CDKN2A homolog and 9p21 neighbor, the CDKN2B gene, and the alternative exon 1 (E1beta) of CDKN2A. Families lacking CDKN2A mutations, but positive for a polymorphism(s) within this gene, were further evaluated to determine if their disease was associated with transcriptional silencing of one CDKN2A allele. Overall, CDKN2A mutations were detected in 3/30 (10%) of the new kindreds. Two of these mutations have been observed previously: a 24 bp duplication at the 5' end of the gene and a G to C transversion in exon 2 resulting in an M531 substitution. A novel G to A transition in exon 2, resulting in a D108N substitution was also detected. Combined with our previous findings, we have now detected germline CDKN2A mutations in 10/48 (21%) of our melanoma kindreds. In none of the 'CDKN2A-negative' families was melanoma found to segregate with either an untranscribed CDKN2A allele, an R24C CDK4 mutation, a CDKN2B mutation, or an E1beta mutation. The last three observations suggest that these other cell cycle control genes (or alternative gene products) are either not involved at all, or to any great extent, in melanoma predisposition.

Mutation analysis of the CDKN2A promoter in Australian melanoma families

Approximately 50% of all melanoma families worldwide show linkage to 9p21-22, but only about half of these have been shown to contain germ line CDKN2A mutations. It has been hypothesized that a proportion of these families carry mutations in the noncoding regions of CDKN2A. Several Canadian families have been reported to carry a mutation in the 5' UTR, at position -34 relative to the start site, which gives rise to a novel AUG translation initiation codon that markedly decreases translation from the wild-type AUG (Liu et al., 1999). Haplotype sharing in these Canadian families suggested that this mutation is of British origin. We sequenced 1,327 base pairs (bp) of CDKN2A, making up 1,116 bp of the 5' UTR and promoter, all of exon 1, and 61 bp of intron 1, in at least one melanoma case from 110 Australian families with three or more affected members known not to carry mutations within the p16 coding region. In addition, 431 bp upstream of the start codon was sequenced in an additional 253 affected probands from two-case melanoma families for which the CDKN2A mutation status was unknown. Several known polymorphisms at positions -33, -191, -493, and -735 were detected, in addition to four novel variants at positions 120, -252, -347, and -981 relative to the start codon. One of the probands from a two-case family was found to have the previously reported Q50R mutation. No family member was found to carry the mutation at position -34 or any other disease-associated mutation. For further investigation of noncoding CDKN2A mutations that may affect transcription, allele-specific expression analysis was carried out in 31 of the families with at least three affected members who showed either complete or "indeterminate" 9p haplotype sharing without CDKN2A exonic mutations. Reverse transcription polymerase chain reaction and automated sequencing showed expression of both CDKN2A alleles in all family members tested. The lack of CDKN2A promoter mutations and the absence of transcriptional silencing in the germ line of this cohort of families suggest that mutations in the promoter and 5' UTR play a very limited role in melanoma predisposition.

p53 prevents progression of nevi to melanoma predominantly through cell cycle regulation

p53 is the central member of a critical tumor suppressor pathway in virtually all tumor types, where it is silenced mainly by missense mutations. In melanoma, p53 predominantly remains wild type, thus its role has been neglected. To study the effect of p53 on melanocyte function and melanomagenesis, we crossed the 'high-p53'Mdm4+/- mouse to the well-established TP-ras0/+ murine melanoma progression model. After treatment with the carcinogen dimethylbenzanthracene (DMBA), TP-ras0/+ mice on the Mdm4+/- background developed fewer tumors with a delay in the age of onset of melanomas compared to TP-ras0/+ mice. Furthermore, we observed a dramatic decrease in tumor growth, lack of metastasis with increased survival of TP-ras0/+: Mdm4+/- mice. Thus, p53 effectively prevented the conversion of small benign tumors to malignant and metastatic melanoma. p53 activation in cultured primary melanocyte and melanoma cell lines using Nutlin-3, a specific Mdm2 antagonist, supported these findings. Moreover, global gene expression and network analysis of Nutlin-3-treated primary human melanocytes indicated that cell cycle regulation through the p21WAF1/CIP1 signaling network may be the key anti-melanomagenic activity of p53.

Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks

This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

Modeling intrinsic noise and delays in chemical kinetics of coupled autoregulated oscillating cells

Delays are an important feature in temporal models of genetic regulation due to slow biochemical processes, such as transcription and translation. In this paper, we show how to model intrinsic noise effects in a delayed setting by either using a delay stochastic simulation algorithm (DSSA) or, for larger and more complex systems, a generalized Binomial τ-leap method (Bτ-DSSA). As a particular application, we apply these ideas to modeling somite segmentation in zebra fish across a number of cells in which two linked oscillatory genes (her1 and her7) are synchronized via Notch signaling between the cells.

Population genetic structure and patterns of dispersal in the Giant Long-Armed Prawn, Macrobrachium lar (Fabricius, 1798) (Decapoda : Palaemonidae)

The Giant Long-Armed Prawn, Macrobrachium lar is a freshwater species native to the Indo-Pacific. M. lar has a long-lived, passive, pelagic marine larval stage where larvae need to colonise freshwater within three months to complete their development. Dispersal is likely to be influenced by the extensive distances larvae must transit between small oceanic islands to find suitable freshwater habitat, and by prevailing east to west wind and ocean currents in the southern Pacific Ocean. Thus, both intrinsic and extrinsic factors are likely to influence wild population structure in this species. The present study sought to define the contemporary broad and fine-scale population genetic structure of Macrobrachium lar in the south-western Pacific Ocean. Three polymorphic microsatellite loci were used to assess patterns of genetic variation within and among 19 wild adult sample sites. Statistical procedures that partition variation implied that at both spatial scales, essentially all variation was present within sample sites and differentiation among sites was low. Any differentiation observed also was not correlated with geographical distance. Statistical approaches that measure genetic distance, at the broad-scale, showed that all south-western Pacific Islands were essentially homogeneous, with the exception of a well supported divergent Cook Islands group. These findings are likely the result of some combination of factors that may include the potential for allelic homoplasy, through to the effects of sampling regime. Based on the findings, there is most likely a divergent M. lar Cook Islands clade in the south-western Pacific Ocean, resulting from prevailing ocean currents. Confirmation of this pattern will require a more detailed analysis of nDNA variation using a larger number of loci and, where possible, use of larger population sizes.

A Krylov-based finite state projection algorithm for solving the chemical master equation arising in the discrete modelling of biological systems

Biochemical reactions underlying genetic regulation are often modelled as a continuous-time, discrete-state, Markov process, and the evolution of the associated probability density is described by the so-called chemical master equation (CME). However the CME is typically difficult to solve, since the state-space involved can be very large or even countably infinite. Recently a finite state projection method (FSP) that truncates the state-space was suggested and shown to be effective in an example of a model of the Pap-pili epigenetic switch. However in this example, both the model and the final time at which the solution was computed, were relatively small. Presented here is a Krylov FSP algorithm based on a combination of state-space truncation and inexact matrix-vector product routines. This allows larger-scale models to be studied and solutions for larger final times to be computed in a realistic execution time. Additionally the new method computes the solution at intermediate times at virtually no extra cost, since it is derived from Krylov-type methods for computing matrix exponentials. For the purpose of comparison the new algorithm is applied to the model of the Pap-pili epigenetic switch, where the original FSP was first demonstrated. Also the method is applied to a more sophisticated model of regulated transcription. Numerical results indicate that the new approach is significantly faster and extendable to larger biological models.