Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

CFD simulations of flow and heat transfer through the porous interface of a metal foam heat exchanger

This paper offers numerical modelling of a waste heat recovery system. A thin layer of metal foam is attached to a cold plate to absorb heat from hot gases leaving the system. The heat transferred from the exhaust gas is then transferred to a cold liquid flowing in a secondary loop. Two different foam PPI (Pores Per Inch) values are examined over a range of fluid velocities. Numerical results are then compared to both experimental data and theoretical results available in the literature. Challenges in getting the simulation results to match those of the experiments are addressed and discussed in detail. In particular, interface boundary conditions specified between a porous layer and a fluid layer are investigated. While physically one expects much lower fluid velocity in the pores compared to that of free flow, capturing this sharp gradient at the interface can add to the difficulties of numerical simulation. The existing models in the literature are modified by considering the pressure gradient inside and outside the foam. Comparisons against the numerical modelling are presented. Finally, based on experimentally-validated numerical results, thermo-hydraulic performance of foam heat exchangers as waste heat recovery units is discussed with the main goal of reducing the excess pressure drop and maximising the amount of heat that can be recovered from the hot gas stream.

The Australian rise of esomeprazole - was expenditure on samples a contributor?

Background Administrative data from the Australian Pharmaceutical Benefits Scheme (PBS) showed rapid growth of esomeprazole dispensing when it was launched. Australia has universal prescription medicine coverage (the PBS), which included esomeprazole from August 2002. Free samples of new medicines are commonly provided to doctors. Objectives To determine if a relationship exists between marketing expenditure on samples and the dispensing rate for esomeprazole in Australia between June 2002 and September 2006. Methods Quarterly sample expenditures at product/brand level for proton pump inhibitors (PPIs) for Australian general practitioners were obtained for July 2002 to September 2006. Corresponding PBS dispensing data were obtained for all PPIs and converted to defined daily dose (DDD)/1000 population/day. Spending on samples was calculated as dollars per dispensed prescription and plotted against time on the Australian market. Results: Total PPI usage increased from 34.2 to 50.8 DDD/1000 population/ day over the study period. Expenditure on samples per dispensed prescription was higher when a PPI was new on the market and diminished over 5-6 years to a relatively constant level. The rapid decline in this ratio was demonstrated by a case study following esomeprazole from launch in Australia for almost 5 years clearly demonstrating the initial investment to drive sales. Conclusion A relationship appears to exist between expenditure on esomeprazole samples and its usage in Australia. A high initial investment was followed by a rapid reduction in cost per prescription dispensed, predominantly due to growth in market share. This trend was consistent with other PPIs

Primary and secondary neural networks of auditory prepulse inhibition: a functional magnetic resonance imaging study of sensorimotor gating of the human acoustic startle response

Feedforward inhibition deficits have been consistently demonstrated in a range of neuropsychiatric conditions using prepulse inhibition (PPI) of the acoustic startle eye-blink reflex when assessing sensorimotor gating. While PPI can be recorded in acutely decerebrated rats, behavioural, pharmacological and psychophysiological studies suggest the involvement of a complex neural network extending from brainstem nuclei to higher order cortical areas. The current functional magnetic resonance imaging study investigated the neural network underlying PPI and its association with electromyographically (EMG) recorded PPI of the acoustic startle eye-blink reflex in 16 healthy volunteers. A sparse imaging design was employed to model signal changes in blood oxygenation level-dependent (BOLD) responses to acoustic startle probes that were preceded by a prepulse at 120 ms or 480 ms stimulus onset asynchrony or without prepulse. Sensorimotor gating was EMG confirmed for the 120-ms prepulse condition, while startle responses in the 480-ms prepulse condition did not differ from startle alone. Multiple regression analysis of BOLD contrasts identified activation in pons, thalamus, caudate nuclei, left angular gyrus and bilaterally in anterior cingulate, associated with EMGrecorded sensorimotor gating. Planned contrasts confirmed increased pons activation for startle alone vs 120-ms prepulse condition, while increased anterior superior frontal gyrus activation was confirmed for the reverse contrast. Our findings are consistent with a primary pontine circuitry of sensorimotor gating that interconnects with inferior parietal, superior temporal, frontal and prefrontal cortices via thalamus and striatum. PPI processes in the prefrontal, frontal and superior temporal cortex were functionally distinct from sensorimotor gating.

Early maternal deprivation reduces prepulse inhibition and impairs spatial learning ability in adulthood: No further effect of post-pubertal chronic corticosterone treatment

Prolonged maternal deprivation leads to long-term alterations in hypothalamic–pituitary–adrenal (HPA) axis activity, disturbances of auditory information processing and neurochemical changes in the adult brain, some of which are similar to that observed in schizophrenia. Here we report the adult behavioural effects of maternal deprivation (12 h on postnatal days 9 and 11) in Wistar rats on paradigms of auditory information processing (prepulse inhibition), sensitivity to dopamimetics (amphetamine-induced hyper-locomotion) and cognition (T-maze delayed alternation and Morris water-maze). In addition, we examined the long-lasting effect of chronic 21-day corticosterone treatment during the post-pubertal period (i.e., postnatal days 56–76) on each of these behavioural paradigms in maternally deprived and control rats. Behavioural testing commenced 2 weeks after the termination of corticosterone treatment. Maternal deprivation led to a significant reduction in PPI and impaired spatial learning ability in adulthood, but did not affect the behavioural response to amphetamine. Post-pubertal chronic corticosterone treatment did not have any major long-lasting effects on any of the behavioural measures in either maternally deprived or control rats. Our findings further support maternal deprivation as an animal model of specific aspects of schizophrenia.

Neurodevelopmental animal models of schizophrenia: Effects on prepulse inhibition

Epidemiological studies have shown increased incidence of schizophrenia in patients subjected to different forms of pre- or perinatal stress. However, as the onset of schizophrenic illness does not usually occur until adolescence or early adulthood, it is not yet fully understood how disruption of early brain development may ultimately lead to malfunction years later. In order to elucidate a possible role for neurodevelopmental factors in the pathogenesis of schizophrenia and to highlight potential new treatments, animal models are needed. Prepulse inhibition (PPI) is a model of sensorimotor gating mechanisms in the brain. It is disrupted in schizophrenia patients and the disruption can be reversed with atypical antipsychotics. It has been widely used in animal studies to explore central mechanisms possibly involved in schizophrenia. There has been a recent surge of behavioural and neurochemical animal studies on neurodevelopmental models, particularly on the effects of postweaning isolation, maternal separation and neonatal lesions of the hippocampus. In these models, long lasting alterations in behaviour and/or molecular changes in specific brain regions are observed, comparable to those seen in schizophrenia. The aim of this article is to critically review the available literature on such neurodevelopmental animal models with special focus on the effects on PPI and brain regions that are putatively involved in regulation of PPI.

Autosomal dominant familial calcium pyrophosphate dihydrate deposition disease is caused by mutation in the transmembrane protein ANKH

Familial autosomal dominant calcium pyrophosphate dihydrate (CPPD) chondrocalcinosis has previously been mapped to chromosome 5pl5. We have identified a mutation in the ANKH gene that segregates with the disease in a family with this condition. ANKH encodes a putative transmembrane inorganic pyrophosphate (PPi) transport channel. We postulate that loss of function of ANKH causes elevated extracellular PPi levels, predisposing to CPPD crystal deposition.

Association of sporadic chondrocalcinosis with a -4-basepair G-to-A transition in the 5′-untranslated region of ANKH that promotes enhanced expression of ANKH protein and excess generation of extracellular inorganic pyrophosphate

Objective Certain mutations in ANKH, which encodes a multiple-pass transmembrane protein that regulates inorganic pyrophosphate (PPi) transport, are linked to autosomal-dominant familial chondrocalcinosis. This study investigated the potential for ANKH sequence variants to promote sporadic chondrocalcinosis. Methods ANKH variants identified by genomic sequencing were screened for association with chondrocalcinosis in 128 patients with severe sporadic chondrocalcinosis or pseudogout and in ethnically matched healthy controls. The effects of specific variants on expression of common markers were evaluated by in vitro transcription/translation. The function of these variants was studied in transfected human immortalized CH-8 articular chondrocytes. Results Sporadic chondrocalcinosis was associated with a G-to-A transition in the ANKH 5′-untranslated region (5′-UTR) at 4 bp upstream of the start codon (in homozygotes of the minor allele, genotype relative risk 6.0, P = 0.0006; overall genotype association P = 0.02). This -4-bp transition, as well as 2 mutations previously linked with familial and sporadic chondrocalcinosis (+14 bp C-to-T and C-terminal GAG deletion, respectively), but not the French familial chondrocalcinosis kindred 143-bp T-to-C mutation, increased reticulocyte ANKH transcription/ANKH translation in vitro. Transfection of complementary DNA for both the wild-type ANKH and the -4-bp ANKH protein variant promoted increased extracellular PPi in CH-8 cells, but unexpectedly, these ANKH mutants had divergent effects on the expression of extracellular PPi and the chondrocyte hypertrophy marker, type X collagen. Conclusion A subset of sporadic chondrocalcinosis appears to be heritable via a -4-bp G-to-A ANKH 5′-UTR transition that up-regulates expression of ANKH and extracellular PPi in chondrocyte cells. Distinct ANKH mutations associated with heritable chondrocalcinosis may promote disease by divergent effects on extracellular PPi and chondrocyte hypertrophy, which is likely to mediate differences in the clinical phenotypes and severity of the disease.

Cuff tear arthropathy: Evidence of functional variation in pyrophosphate metabolism genes

We investigated the role of two genes, ANKH and TNAP, in patients with cuff tear arthropathy. These genes encode proteins which regulate the extracellular concentration of inorganic pyrophosphate, fluctuations of which can lead to calcium crystal formation. Variants were detected by direct sequencing of DNA and their frequencies compared with healthy controls. The effect of variants on protein function was further studied by in vitro approaches. Variant genotypes were observed more frequently in the cases when compared with controls in ANKH (45% and 20%) and TNAP (32% and 9%). Variants in ANKH altered inorganic pyrophosphate (PPi) concentrations in transfected human chondrocytes. There was a higher mean serum concentration of TNAP detected in female patients compared with normal ranges. Cuff tear arthropathy is associated with variants in ANKH and TNAP that alter extracellular inorganic pyrophosphate concentrations causing calcium crystal deposition. This supports a theory that genetic variants predispose patients to primary crystal deposition which when combined with a massive rotator cuff tear leads to the development of arthritis.

Genetic studies of chondrocalcinosis

Purpose of review Our understanding of the causation of the chondrocalcinosis and other disorders characterized by ectopic mineralization is rapidly increasing, and genetic studies have contributed substantially to recent major advances in the field. This review will discuss what is known about the genetics of chondrocalcinosis and what we have learned from genetic studies to date. Recent findings: Chondrocalcinosis is one of a family of conditions associated with ectopic mineralization. This family also includes disorders of mineralization of bone and spinal and other ligaments, and vascular calcification. There has been increasing evidence of the key role of transport and metabolism of inorganic pyrophosphate (PPi) in control of mineralization, and as the likely explanation for the association of a variety of genetic variants with chondrocalcinosis and ectopic mineralization elsewhere. This may be an overly simplistic view of this family of conditions, with recent evidence suggesting that, for example, ANKH variants may not all predispose to chondrocalcinosis by effects on PPi transport, but may also influence chondrocyte maturation. Summary: Understanding the control of the process of mineralization and its tissue specificity are important steps in the search for rational therapies for these conditions.