ORCID Profile
0000-0003-2570-5966
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Artificial Intelligence and Image Processing | Neural, Evolutionary and Fuzzy Computation | Neural Networks, Genetic Alogrithms And Fuzzy Logic | Analysis Of Algorithms And Complexity | Neurogenetics | Biochemistry and Cell Biology | Computation Theory and Mathematics | Central Nervous System | Analytical Biochemistry | Gene Expression | Protein Targeting And Signal Transduction | Neurology And Neuromuscular Diseases | Plant Physiology | Medical Genetics | Neurosciences |
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in the Information and Computing Sciences | Cancer and related disorders | Diagnostic methods | Computer Software and Services not elsewhere classified | Nervous system and disorders | Men’s health | Biological sciences | Computer software and services not elsewhere classified | Disease distribution and transmission | Preventive medicine | Diagnostics
Related Links
Publications
An information theoretic clustering approach for unveiling authorship affinities in Shakespearean era plays and poems
Publisher: Public Library of Science (PLoS)
Date: 27-10-2014
Genome-wide analysis of long noncoding RNA stability.
Publisher: Cold Spring Harbor Laboratory
Date: 09-03-2012
Abstract: Transcriptomic analyses have identified tens of thousands of intergenic, intronic, and cis -antisense long noncoding RNAs (lncRNAs) that are expressed from mammalian genomes. Despite progress in functional characterization, little is known about the post-transcriptional regulation of lncRNAs and their half-lives. Although many are easily detectable by a variety of techniques, it has been assumed that lncRNAs are generally unstable, but this has not been examined genome-wide. Utilizing a custom noncoding RNA array, we determined the half-lives of ∼800 lncRNAs and ∼12,000 mRNAs in the mouse Neuro-2a cell line. We find only a minority of lncRNAs are unstable. LncRNA half-lives vary over a wide range, comparable to, although on average less than, that of mRNAs, suggestive of complex metabolism and widespread functionality. Combining half-lives with comprehensive lncRNA annotations identified hundreds of unstable (half-life 2 h) intergenic, cis -antisense, and intronic lncRNAs, as well as lncRNAs showing extreme stability (half-life 16 h). Analysis of lncRNA features revealed that intergenic and cis -antisense RNAs are more stable than those derived from introns, as are spliced lncRNAs compared to unspliced (single exon) transcripts. Subcellular localization of lncRNAs indicated widespread trafficking to different cellular locations, with nuclear-localized lncRNAs more likely to be unstable. Surprisingly, one of the least stable lncRNAs is the well-characterized paraspeckle RNA Neat1 , suggesting Neat1 instability contributes to the dynamic nature of this subnuclear domain. We have created an online interactive resource ( stability.matticklab.com ) that allows easy navigation of lncRNA and mRNA stability profiles and provides a comprehensive annotation of ∼7200 mouse lncRNAs.
Separating sets of strings by finding matching patterns is almost always hard
Publisher: Elsevier BV
Date: 02-2017
Benchmarking a memetic algorithm for ordering microarray data
Publisher: Elsevier BV
Date: 03-2007
DOI: 10.1016/J.BIOSYSTEMS.2006.04.005
Abstract: This work introduces a new algorithm for "gene ordering". Given a matrix of gene expression data values, the task is to find a permutation of the gene names list such that genes with similar expression patterns should be relatively close in the permutation. The algorithm is based on a combined approach that integrates a constructive heuristic with evolutionary and Tabu Search techniques in a single methodology. To evaluate the benefits of this method, we compared our results with the current outputs provided by several widely used algorithms in functional genomics. We also compared the results with our own hierarchical clustering method when used in isolation. We show that the use of images, corrupted with known levels of noise, helps to illustrate some aspects of the performance of the algorithms and provide a complementary benchmark for the analysis. The use of these images, with known high-quality solutions, facilitates in some cases the assessment of the methods and helps the software development, validation and reproducibility of results. We also propose two quantitative measures of performance for gene ordering. Using these measures, we make a comparison with probably the most used algorithm (due to Eisen and collaborators, PNAS 1998) using a microarray dataset available on the public domain (the complete yeast cell cycle dataset).
Extensive Transcriptomic and Genomic Analysis Provides New Insights about Luminal Breast Cancers
Publisher: Public Library of Science (PLoS)
Date: 24-06-2016
Optimising weights for heterogeneous ensemble of classifiers with differential evolution
Publisher: IEEE
Date: 07-2016
Is there more than one proctitis syndrome? A revisitation using data from the TROG 96.01 trial
Publisher: Elsevier BV
Date: 03-2009
DOI: 10.1016/J.RADONC.2008.09.019
Abstract: We sought to categorize longitudinal radiation-induced rectal toxicity data obtained from men participating in a randomised controlled trial for locally advanced prostate cancer. Data from self-assessed questionnaires of rectal symptoms and clinician recorded remedial interventions were collected during the TROG 96.01 trial. In this trial, volunteers were randomised to radiation with or without neoadjuvant androgen deprivation. Characterization of longitudinal variations in symptom intensity was achieved using prevalence data. An integrated visualization and clustering approach based on memetic algorithms was used to define the compositions of symptom clusters occurring before, during and after radiation. The utility of the CTC grading system as a means of identifying specific injury profiles was evaluated using concordance analyses. Seven well-defined clusters of rectal symptoms were present prior to treatment, 25 were seen immediately following radiation and 7 at years 1, 2 and 3 following radiation. CTC grading did not concord with the degree of rectal 'distress' and 'problems' at all time points. Concordance was not improved by adding urgency to the CTC scale. The CTC scale has serious shortcomings. A powerful new technique for non-hierarchical clustering may contribute to the categorization of rectal toxicity data for genomic profiling studies and detailed patho-physiological studies.
Evolving Robust Gene Regulatory Networks
Publisher: Public Library of Science (PLoS)
Date: 23-01-2015
Brain transcriptome perturbations in the Hfe -/- mouse model of genetic iron loading
Publisher: Elsevier BV
Date: 04-2012
DOI: 10.1016/J.BRAINRES.2012.02.006
Abstract: Severe disruption of brain iron homeostasis can cause fatal neurodegenerative disease, however debate surrounds the neurologic effects of milder, more common iron loading disorders such as hereditary hemochromatosis, which is usually caused by loss-of-function polymorphisms in the HFE gene. There is evidence from both human and animal studies that HFE gene variants may affect brain function and modify risks of brain disease. To investigate how disruption of HFE influences brain transcript levels, we used microarray and real-time reverse transcription polymerase chain reaction to assess the brain transcriptome in Hfe(-/-) mice relative to wildtype AKR controls (age 10 weeks, n≥4/group). The Hfe(-/-) mouse brain showed numerous significant changes in transcript levels (p<0.05) although few of these related to proteins directly involved in iron homeostasis. There were robust changes of at least 2-fold in levels of transcripts for prominent genes relating to transcriptional regulation (FBJ osteosarcoma oncogene Fos, early growth response genes), neurotransmission (glutamate NMDA receptor Grin1, GABA receptor Gabbr1) and synaptic plasticity and memory (calcium/calmodulin-dependent protein kinase IIα Camk2a). As previously reported for dietary iron-supplemented mice, there were altered levels of transcripts for genes linked to neuronal ceroid lipofuscinosis, a disease characterized by excessive lipofuscin deposition. Labile iron is known to enhance lipofuscin generation which may accelerate brain aging. The findings provide evidence that iron loading disorders can considerably perturb levels of transcripts for genes essential for normal brain function and may help explain some of the neurologic signs and symptoms reported in hemochromatosis patients.
Identifying Communities of Trust and Confidence in the Charity and Not-for-Profit Sector: A Memetic Algorithm Approach
Publisher: IEEE
Date: 12-2014
Uncovering Molecular Biomarkers That Correlate Cognitive Decline with the Changes of Hippocampus' Gene Expression Profiles in Alzheimer's Disease
Publisher: Public Library of Science (PLoS)
Date: 13-04-2010
Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification
Publisher: Public Library of Science (PLoS)
Date: 14-01-2016
A memetic algorithm for the total tardiness single machine scheduling problem
Publisher: Elsevier BV
Date: 07-2001
Unveiling Clusters of RNA Transcript Pairs Associated with Markers of Alzheimer’s Disease Progression
Publisher: Public Library of Science (PLoS)
Date: 21-09-2012
Multiple regression techniques for modelling dates of first performances of Shakespeare-era plays
Publisher: Elsevier BV
Date: 08-2022
Impact of androgen suppression and zoledronic acid on bone mineral density and fractures in the Trans‐Tasman Radiation Oncology Group (TROG ) 03.04 Randomised Androgen Deprivation and Radiot
Publisher: Wiley
Date: 11-02-2014
DOI: 10.1111/BJU.12497
Abstract: To study the influence of adjuvant androgen suppression and bisphosphonates on incident vertebral and non-spinal fracture rates and bone mineral density (BMD) in men with locally advanced prostate cancer. Between 2003 and 2007, 1071 men with locally advanced prostate cancer were randomly allocated, using a 2 × 2 trial design, to 6 months i.m. leuprorelin (androgen suppression [AS]) before radiotherapy alone ± 12 months additional leuprorelin ± 18 months zoledronic acid (ZdA), commencing at randomization. The main endpoint was incident thoraco-lumbar vertebral fractures, which were assessed radiographically at randomization and at 3 years, then reassessed by centralized review. Subsidiary endpoints included incident non-spinal fractures, which were documented throughout follow-up, and BMD, which was measured in 222 subjects at baseline, 2 years and 4 years. Incident vertebral fractures at 3 years were observed in 132 subjects. Their occurrence was not increased by 18 months' AS, nor reduced by ZdA. Incident non-spinal fractures occurred in 72 subjects and were significantly related to AS duration but not to ZdA. Osteopenia and osteoporosis prevalence rates at baseline were 23.4 and 1.4%, respectively, at the hip. Treatment for 6 and 18 months with AS caused significant reductions in hip BMD at 2 and 4 years (P < 0.01) and ZdA prevented these losses at both time points. In an AS-naïve population, 18 months of ZdA treatment prevented the sustained BMD losses caused by 18 months of AS treatment however, the study power was insufficient to show that AS duration or ZdA influenced vertebral fracture rates.
GPU-FS-kNN: A Software Tool for Fast and Scalable kNN Computation Using GPUs
Publisher: Public Library of Science (PLoS)
Date: 28-08-2012
Relative neighborhood graphs uncover the dynamics of social media engagement
Publisher: Springer International Publishing
Date: 2016
Learning to Extrapolate Using Continued Fractions: Predicting the Critical Temperature of Superconductor Materials
Publisher: MDPI AG
Date: 08-08-2023
DOI: 10.3390/A16080382
Abstract: In the field of Artificial Intelligence (AI) and Machine Learning (ML), a common objective is the approximation of unknown target functions y=f(x) using limited instances S=(x(i),y(i)), where x(i)∈D and D represents the domain of interest. We refer to S as the training set and aim to identify a low-complexity mathematical model that can effectively approximate this target function for new instances x. Consequently, the model’s generalization ability is evaluated on a separate set T={x(j)}⊂D, where T≠S, frequently with T∩S=∅, to assess its performance beyond the training set. However, certain applications require accurate approximation not only within the original domain D but in an extended domain D′ that encompasses D as well. This becomes particularly relevant in scenarios involving the design of new structures, where minimizing errors in approximations is crucial. For ex le, when developing new materials through data-driven approaches, the AI/ML system can provide valuable insights to guide the design process by serving as a surrogate function. Consequently, the learned model can be employed to facilitate the design of new laboratory experiments. In this paper, we propose a method for multivariate regression based on iterative fitting of a continued fraction, incorporating additive spline models. We compare the performance of our method with established techniques, including AdaBoost, Kernel Ridge, Linear Regression, Lasso Lars, Linear Support Vector Regression, Multi-Layer Perceptrons, Random Forest, Stochastic Gradient Descent, and XGBoost. To evaluate these methods, we focus on an important problem in the field, namely, predicting the critical temperature of superconductors based on their physical–chemical characteristics.
A memetic algorithm for the quadratic assignment problem with parallel local search
Publisher: IEEE
Date: 05-2015
Distinguishing childhood absence epilepsy patients from controls by the analysis of their background brain electrical activity (II): A combinatorial optimization approach for electrode selection
Publisher: Elsevier BV
Date: 07-2009
DOI: 10.1016/J.JNEUMETH.2009.04.028
Abstract: In this sequel to our previous work [Rosso OA, Mendes A, Rostas JA, Hunter M, Moscato P. Distinguishing childhood absence epilepsy patients from controls by the analysis of their background brain electrical activity. J. Neurosci. Methods 2009 :461-68], we extend the analysis of background electroencephalography (EEG), recorded with scalp electrodes in a clinical setting, in children with childhood absence epilepsy (CAE) and control in iduals. The same set of in iduals was considered-five CAE patients, all right-handed females and aged 6-8 years. The EEG was obtained using bipolar connections from a standard 10-20 electrode placement. The functional activity between electrodes was evaluated using a wavelet decomposition in conjunction with the Wootters distance. In the previous study, a Kruskal-Wallis statistical test was used to select the pairs of electrodes with differentiated behavior between CAE and control s les (classes). In this contribution, we present the results for a combinatorial optimization approach to select the pairs of electrodes. The new method produces a better separation between the classes, and at the same time uses a smaller number of features (pairs of electrodes). It managed to almost halve the number of features and also improves the separation between the CAE and control s les. The new results strengthen the hypothesis that mostly fronto-central electrodes carry useful information and patterns that can help to discriminate CAE cases from controls. Finally, we provide a comprehensive set of tests and in-depth explanation of the method and results.
Engagement in Motion: Exploring Short Term Dynamics in Page-Level Social Media Metrics
Publisher: IEEE
Date: 12-2014
Clustering nodes in large-scale biological networks using external memory algorithms
Publisher: Springer Berlin Heidelberg
Date: 2011
Basal-like breast cancer: molecular profiles, clinical features and survival outcomes
Publisher: Springer Science and Business Media LLC
Date: 28-03-2017
The multiple sclerosis whole blood mRNA transcriptome and genetic associations indicate dysregulation of specific T cell pathways in pathogenesis
Publisher: Oxford University Press (OUP)
Date: 27-02-2010
DOI: 10.1093/HMG/DDQ090
Abstract: Multiple sclerosis (MS) is an autoimmune disease with a genetic component, caused at least in part by aberrant lymphocyte activity. The whole blood mRNA transcriptome was measured for 99 untreated MS patients: 43 primary progressive MS, 20 secondary progressive MS, 36 relapsing remitting MS and 45 age-matched healthy controls. The ANZgene Multiple Sclerosis Genetics Consortium genotyped more than 300 000 SNPs for 115 of these s les. Transcription from genes on translational regulation, oxidative phosphorylation, immune synapse and antigen presentation pathways was markedly increased in all forms of MS. Expression of genes tagging T cells was also upregulated (P < 10(-12)) in MS. A T cell gene signature predicts disease state with a concordance index of 0.79 with age and gender as co-variables, but the signature is not associated with clinical course or disability. The ANZgene genome wide association screen identified two novel regions with genome wide significance: one encoding the T cell co-stimulatory molecule, CD40 the other a region on chromosome 12q13-14. The CD40 haplotype associated with increased MS susceptibility has decreased gene expression in MS (P < 0.0007). The second MS susceptibility region includes 17 genes on 12q13-14 in tight linkage disequilibrium. Of these, only 13 are expressed in leukocytes, and of these the expression of one, FAM119B, is much lower in the susceptibility haplotype (P < 10(-14)). Overall, these data indicate dysregulation of T cells can be detected in the whole blood of untreated MS patients, and supports targeting of activated T cells in therapy for all forms of MS.
Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups
Publisher: Elsevier BV
Date: 05-2005
kNN-Borůvka-GPU: A fast and scalable MST construction from kNN graphs on GPU
Publisher: Springer Berlin Heidelberg
Date: 2012
Polymorphisms in the receptor tyrosine kinase MERTK gene are associated with Multiple Sclerosis susceptibility
Publisher: Public Library of Science (PLoS)
Date: 08-02-2011
QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization
Publisher: Public Library of Science (PLoS)
Date: 18-01-2011
A Kernelisation Approach for Multiple d-Hitting Set and Its Application in Optimal Multi-Drug Therapeutic Combinations
Publisher: Public Library of Science (PLoS)
Date: 18-10-2010
Hierarchical clustering using the arithmetic-harmonic cut: Complexity and experiments
Publisher: Public Library of Science (PLoS)
Date: 02-12-2010
Augmented intuition: a bridge between theory and practice
Publisher: Springer Science and Business Media LLC
Date: 31-01-2021
kNN-MST-Agglomerative: A fast and scalable graph-based data clustering approach on GPU
Publisher: IEEE
Date: 07-2012
Common variants at 6p21.1 are associated with large artery atherosclerotic stroke
Publisher: Springer Science and Business Media LLC
Date: 02-09-2012
DOI: 10.1038/NG.2397
Computing large-scale distance matrices on GPU
Publisher: IEEE
Date: 07-2012
Sifting the wheat from the chaff: prioritizing GWAS results by identifying consistency across analytical methods
Publisher: Wiley
Date: 28-11-2011
DOI: 10.1002/GEPI.20622
Abstract: The curse of multiple testing has led to the adoption of a stringent Bonferroni threshold for declaring genome-wide statistical significance for any one SNP as standard practice. Although justified in avoiding false positives, this conservative approach has the potential to miss true associations as most studies are drastically underpowered. As an alternative to increasing s le size, we compare results from a typical SNP-by-SNP analysis with three other methods that incorporate regional information in order to boost or d en an otherwise noisy signal: the haplotype method (Schaid et al. [2002] Am J Hum Genet 70:425-434), the gene-based method (Liu et al. [2010] Am J Hum Genet 87:139-145), and a new method (interaction count) that uses genome-wide screening of pairwise SNP interactions. Using a modestly sized case-control study, we conduct a genome-wide association studies (GWAS) of age-related macular degeneration, and find striking agreement across all methods in regions of known associated variants. We also find strong evidence of novel associated variants in two regions (Chromosome 2p25 and Chromosome 10p15) in which the in idual SNP P-values are only suggestive, but where there are very high levels of agreement between all methods. We propose that consistency between different analysis methods may be an alternative to increasingly larger s le sizes in sifting true signals from noise in GWAS.
The CYP27B1 variant associated with an increased risk of autoimmune disease is underexpressed in tolerizing dendritic cells
Publisher: Oxford University Press (OUP)
Date: 08-04-2031
DOI: 10.1093/HMG/DDT529
Abstract: Genome-wide association studies have identified a linkage disequilibrium (LD) block on chromosome 12 associated with multiple sclerosis (MS), type 1 diabetes and other autoimmune diseases. This block contains CYP27B1, which catalyzes the conversion of 25 vitamin D3 (VitD3) to 1,25VitD3. Fine-mapping analysis has failed to identify which of the 17 genes in this block is most associated with MS. We have previously used a functional approach to identify the causal gene. We showed that the expression of several genes in this block in whole blood is highly associated with the MS risk allele, but not CYP27B1. Here, we show that CYP27B1 is predominantly expressed in dendritic cells (DCs). Its expression in these cells is necessary for their response to VitD, which is known to upregulate pathways involved in generating a tolerogenic DC phenotype. Here, we utilize a differentiation protocol to generate inflammatory (DC1) and tolerogenic (DC2) DCs, and show that for the MS risk allele CYP27B1 is underexpressed in DCs, especially DC2s. Of the other Chr12 LD block genes expressed in these cells, only METT21B expression was as affected by the genotype. Another gene associated with autoimmune diseases, CYP24A1, catabolizes 1,25 VitD3, and is predominantly expressed in DCs, but equally between DC1s and DC2s. Overall, these data are consistent with the hypothesis that reduced VitD pathway gene upregulation in DC2s of carriers of the risk haplotype of CYP27B1 contributes to autoimmune diseases. These data support therapeutic approaches aimed at targeting VitD effects on DCs.
The gene interaction miner: A new tool for data mining contextual information for protein-protein interaction analysis
Publisher: Oxford University Press (OUP)
Date: 04-12-2009
DOI: 10.1093/BIOINFORMATICS/BTP652
Abstract: Motivation: This work was motivated by the need for an automated tool for discovery of genetic networks and the availability of extensive contextual protein–protein interaction information in the iHOP repository. At the moment, this information cannot be explored to its full potential due to the lack of software tools to reliably collect, process and display that information in a way that life scientists can quickly analyze genes of interest and search for potential interaction networks. Commercial tools can perform a similar job, but results appear to be less informative than those obtained using contextual information. Results: The Gene Interaction Miner (GIM) could successfully uncover complex network structures of protein–protein interactions for a test dataset composed of genes already related to Alzheimer's disease. That same set, when examined using two other analysis tools, namely STRING and Pathway Studio, resulted in incomplete protein–protein interaction networks, which indicate that the use of curated databases only gives a partial picture of the biological processes behind the disease. Availability: The dataset used in this work and a running version of the software tool is available for download from the web site www.cs.newcastle.edu.au/∼mendes/softwareGIM.html. Contact: alexandre.mendes@newcastle.edu.au
Mining disjunctive minimal generators with TitanicOR
Publisher: Elsevier BV
Date: 07-2012
Genetic Signatures for a Rodent Model of Parkinson's Disease Using Combinatorial Optimization Methods
Publisher: Humana Press
Date: 2008
DOI: 10.1007/978-1-60327-429-6_20
Abstract: This chapter illustrates the use of the combinatorial optimization models presented in Chapter 19 for the Feature Set selection and Gene Ordering problems to find genetic signatures for diseases using micro-array data. We demonstrate the quality of this approach by using a microarray dataset from a mouse model of Parkinson's disease. The results are accompanied by a description of the currently known molecular functions and biological processes of the genes in the signatures.
Identification of a 5-Protein Biomarker Molecular Signature for Predicting Alzheimer's Disease
Publisher: Public Library of Science (PLoS)
Date: 03-09-2008
Identification of Genome-Wide SNP–SNP and SNP–Clinical Boolean Interactions in Age-Related Macular Degeneration
Publisher: Springer New York
Date: 03-11-2014
DOI: 10.1007/978-1-4939-2155-3_12
Abstract: We propose here a methodology to uncover modularities in the network of SNP-SNP interactions most associated with disease. We start by computing all possible Boolean binary SNP interactions across the whole genome. By constructing a weighted graph of the most relevant interactions and via a combinatorial optimization approach, we find the most highly interconnected SNPs. We show that the method can be easily extended to find SNP/environment interactions. Using a modestly sized GWAS dataset of age-related macular degeneration (AMD), we identify a group of only 19 SNPs, which include those in previously reported regions associated to AMD. We also uncover a larger set of loci pointing to a matrix of key processes and functions that are affected. The proposed integrative methodology extends and overlaps traditional statistical analysis in a natural way. Combinatorial optimization techniques allow us to find the kernel of the most central interactions, complementing current methods of GWAS analysis and also enhancing the search for gene-environment interaction.
Are Myocardial Infarction–Associated Single-Nucleotide Polymorphisms Associated With Ischemic Stroke?
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 04-2012
DOI: 10.1161/STROKEAHA.111.632075
Abstract: Ischemic stroke (IS) shares many common risk factors with coronary artery disease (CAD). We hypothesized that genetic variants associated with myocardial infarction (MI) or CAD may be similarly involved in the etiology of IS. To test this hypothesis, we evaluated whether single-nucleotide polymorphisms (SNPs) at 11 different loci recently associated with MI or CAD through genome-wide association studies were associated with IS. Meta-analyses of the associations between the 11 MI-associated SNPs and IS were performed using 6865 cases and 11 395 control subjects recruited from 9 studies. SNPs were either genotyped directly or imputed in a few cases a surrogate SNP in high linkage disequilibrium was chosen. Logistic regression was performed within each study to obtain study-specific βs and standard errors. Meta-analysis was conducted using an inverse variance weighted approach assuming a random effect model. Despite having power to detect odds ratio of 1.09–1.14 for overall IS and 1.20–1.32 for major stroke subtypes, none of the SNPs were significantly associated with overall IS and/or stroke subtypes after adjusting for multiple comparisons. Our results suggest that the major common loci associated with MI risk do not have effects of similar magnitude on overall IS but do not preclude moderate associations restricted to specific IS subtypes. Disparate mechanisms may be critical in the development of acute ischemic coronary and cerebrovascular events.
‘Neuroinflammation’ differs categorically from inflammation: transcriptomes of Alzheimer's disease, Parkinson's disease, schizophrenia and inflammatory diseases compared
Publisher: Springer Science and Business Media LLC
Date: 15-06-2014
DOI: 10.1007/S10048-014-0409-X
Abstract: 'Neuroinflammation' has become a widely applied term in the basic and clinical neurosciences but there is no generally accepted neuropathological tissue correlate. Inflammation, which is characterized by the presence of perivascular infiltrates of cells of the adaptive immune system, is indeed seen in the central nervous system (CNS) under certain conditions. Authors who refer to microglial activation as neuroinflammation confuse this issue because autoimmune neuroinflammation serves as a synonym for multiple sclerosis, the prototypical inflammatory disease of the CNS. We have asked the question whether a data-driven, unbiased in silico approach may help to clarify the nomenclatorial confusion. Specifically, we have examined whether unsupervised analysis of microarray data obtained from human cerebral cortex of Alzheimer's, Parkinson's and schizophrenia patients would reveal a degree of relatedness between these diseases and recognized inflammatory conditions including multiple sclerosis. Our results using two different data analysis methods provide strong evidence against this hypothesis demonstrating that very different sets of genes are involved. Consequently, the designations inflammation and neuroinflammation are not interchangeable. They represent different categories not only at the histophenotypic but also at the transcriptomic level. Therefore, non-autoimmune neuroinflammation remains a term in need of definition.
Novel Biomarkers for Prostate Cancer Revealed by (α,β)-k-Feature Sets
Publisher: Springer Berlin Heidelberg
Date: 2009
A Novel Clustering Methodology Based on Modularity Optimisation for Detecting Authorship Affinities in Shakespearean Era Plays
Publisher: Public Library of Science (PLoS)
Date: 29-08-2016
Differences in Abundances of Cell-Signalling Proteins in Blood Reveal Novel Biomarkers for Early Detection Of Clinical Alzheimer's Disease
Publisher: Public Library of Science (PLoS)
Date: 24-03-2011
Multivariate protein signatures of pre-clinical Alzheimer's disease in the Alzheimer's disease neuroimaging initiative (ADNI) plasma proteome dataset.
Publisher: Public Library of Science (PLoS)
Date: 02-04-2012
A rare P2X7 variant Arg307Gln with absent pore formation function protects against neuroinflammation in multiple sclerosis
Publisher: Oxford University Press (OUP)
Date: 17-07-2015
DOI: 10.1093/HMG/DDV278
Abstract: Multiple sclerosis (MS) is a chronic relapsing-remitting inflammatory disease of the central nervous system characterized by oligodendrocyte damage, demyelination and neuronal death. Genetic association studies have shown a 2-fold or greater prevalence of the HLA-DRB1*1501 allele in the MS population compared with normal Caucasians. In discovery cohorts of Australasian patients with MS (total 2941 patients and 3008 controls), we examined the associations of 12 functional polymorphisms of P2X7, a microglial/macrophage receptor with proinflammatory effects when activated by extracellular adenosine triphosphate (ATP). In discovery cohorts, rs28360457, coding for Arg307Gln was associated with MS and combined analysis showed a 2-fold lower minor allele frequency compared with controls (1.11% for MS and 2.15% for controls, P = 0.0000071). Replication analysis of four independent European MS case-control cohorts (total 2140 cases and 2634 controls) confirmed this association [odds ratio (OR) = 0.69, P = 0.026]. A meta-analysis of all Australasian and European cohorts indicated that Arg307Gln confers a 1.8-fold protective effect on MS risk (OR = 0.57, P = 0.0000024). Fresh human monocytes heterozygous for Arg307Gln have >85% loss of 'pore' function of the P2X7 receptor measured by ATP-induced ethidium uptake. Analysis shows Arg307Gln always occurred with 270His suggesting a single 307Gln-270His haplotype that confers dominant negative effects on P2X7 function and protection against MS. Modeling based on the homologous zP2X4 receptor showed Arg307 is located in a region rich in basic residues located only 12 Å from the ligand binding site. Our data show the protective effect against MS of a rare genetic variant of P2RX7 with heterozygotes showing near absent proinflammatory 'pore' function.
A Transcription Factor Map as Revealed by a Genome- Wide Gene Expression Analysis of Whole-Blood mRNA Transcriptome in Multiple Sclerosis
Publisher: Public Library of Science (PLoS)
Date: 12-2010
An automatic graph layout procedure to visualize correlated data
Publisher: Springer US
Date: 2006
Genetic biomarkers for brain hemisphere differentiation in Parkinson's Disease
Publisher: AIP
Date: 2007
DOI: 10.1063/1.2816624
Disclosed: An efficient depth-first, top-down algorithm for mining disjunctive closed itemsets in high-dimensional data
Publisher: Elsevier BV
Date: 10-2014
The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set
Publisher: Public Library of Science (PLoS)
Date: 22-04-2026
A parallel memetic algorithm applied to the total tardiness machine scheduling problem
Publisher: IEEE
Date: 2006
Distinguishing childhood absence epilepsy patients from controls by the analysis of their background brain electrical activity
Publisher: Elsevier BV
Date: 03-2009
DOI: 10.1016/J.JNEUMETH.2008.10.017
Abstract: Background electroencephalography (EEG), recorded with scalp electrodes, in children with childhood absence epilepsy (CAE) and control in iduals has been analyzed. We considered 5 CAE patients, all right-handed females and aged 6-8 years. The 15 control in iduals had the same characteristics of the CAE ones, but presented a normal EEG. The EEG was obtained using bipolar connections from a standard 10-20 electrode placement (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1 and O2). Recordings were undertaken in the resting state with eyes closed. EEG hallmarks of absence seizure activity are widely accepted, but there is a recognition that the bulk of interictal EEG in CAE appears normal to visual inspection. The functional activity between electrodes was evaluated using a wavelet decomposition in conjunction with the Wootters distance. Then, pairs of electrodes with differentiated behavior between CAE and controls were identified using a test statistic-based feature selection technique. This approach identified clear differences between CAE and healthy control background EEG in the frontocentral electrodes, as measured by Principal Component Analysis. The findings of this pilot study can have strong implications in future clinical practice.
Iteratively refining breast cancer intrinsic subtypes in the METABRIC dataset
Publisher: Springer Science and Business Media LLC
Date: 13-01-2016
A new method for mining disjunctive emerging patterns in high-dimensional datasets using hypergraphs
Publisher: Elsevier BV
Date: 03-2014
The MS risk allele of CD40 is associated with reduced cell-membrane bound expression in antigen presenting cells: Implications for gene function
Publisher: Public Library of Science (PLoS)
Date: 11-06-2015
Resequencing and fine-mapping of the chromosome 12q13-14 locus associated with multiple sclerosis refines the number of implicated genes
Publisher: Oxford University Press (OUP)
Date: 12-02-2013
DOI: 10.1093/HMG/DDT062
Abstract: Multiple sclerosis (MS) is a common chronic inflammatory disease of the central nervous system. Susceptibility to the disease is affected by both environmental and genetic factors. Genetic factors include haplotypes in the histocompatibility complex (MHC) and over 50 non-MHC loci reported by genome-wide association studies. Amongst these, we previously reported polymorphisms in chromosome 12q13-14 with a protective effect in in iduals of European descent. This locus spans 288 kb and contains 17 genes, including several candidate genes which have potentially significant pathogenic and therapeutic implications. In this study, we aimed to fine-map this locus. We have implemented a two-phase study: a variant discovery phase where we have used next-generation sequencing and two target-enrichment strategies [long-range polymerase chain reaction (PCR) and Nimblegen's solution phase hybridization capture] in pools of 25 s les and a genotyping phase where we genotyped 712 variants in 3577 healthy controls and 3269 MS patients. This study confirmed the association (rs2069502, P = 9.9 × 10(-11), OR = 0.787) and narrowed down the locus of association to an 86.5 kb region. Although the study was unable to pinpoint the key-associated variant, we have identified a 42 (genotyped and imputed) single-nucleotide polymorphism haplotype block likely to harbour the causal variant. No evidence of association at previously reported low-frequency variants in CYP27B1 was observed. As part of the study we compared variant discovery performance using two target-enrichment strategies. We concluded that our pools enriched with Nimblegen's solution phase hybridization capture had better sensitivity to detect true variants than the pools enriched with long-range PCR, whilst specificity was better in the long-range PCR-enriched pools compared with solution phase hybridization capture enriched pools this result has important implications for the design of future fine-mapping studies.
Gene Ordering in Microarray Data Using Parallel Memetic Algorithms
Publisher: IEEE
Date: 2005
A Data-Driven Approach to Reverse Engineering Customer Engagement Models: Towards Functional Constructs
Publisher: Public Library of Science (PLoS)
Date: 18-07-2014
Familial recurrence risks for multiple sclerosis in Australia
Publisher: BMJ
Date: 07-05-2011
Abstract: Genetic susceptibility to multiple sclerosis (MS) has been recognised for many years. Considerable data exist from the northern hemisphere regarding the familial recurrence risks for MS, but there are few data for the southern hemisphere and regions at lower latitude such as Australia. To investigate the interaction between environmental and genetic causative factors in MS, the authors undertook a familial recurrence risk study in three latitudinally distinct regions of Australia. Immediate and extended family pedigrees have been collected for three cohorts of people with MS in Queensland, Victoria and Tasmania spanning 15° of latitude. Age of onset data from Queensland were utilised to estimate age-adjusted recurrence rates. Recurrence risks in Australia were significantly lower than in studies from northern hemisphere populations. The age-adjusted risk for siblings across Australia was 2.13% compared with 3.5% for the northern hemisphere. A similar pattern was seen for other relatives. The risks to relatives were proportional to the population risks for each site, and hence the sibling recurrence-risk ratio (λ(s)) was similar across all sites. The familial recurrence risk of MS in Australia is lower than in previously reported studies. This is directly related to the lower population prevalence of MS. The overall genetic susceptibility in Australia as measured by the λ(s) is similar to the northern hemisphere, suggesting that the difference in population risk is explained largely by environmental factors rather than by genetic admixture.
Computer-aided breast cancer diagnosis with optimal feature sets: Reduction rules and optimization techniques
Publisher: Springer New York
Date: 29-11-2017
DOI: 10.1007/978-1-4939-6613-4_17
Abstract: This chapter introduces a new method for knowledge extraction from databases for the purpose of finding a discriminative set of features that is also a robust set for within-class classification. Our method is generic and we introduce it here in the field of breast cancer diagnosis from digital mammography data. The mathematical formalism is based on a generalization of the k-Feature Set problem called (α, β)-k-Feature Set problem, introduced by Cotta and Moscato (J Comput Syst Sci 67(4):686-690, 2003). This method proceeds in two steps: first, an optimal (α, β)-k-feature set of minimum cardinality is identified and then, a set of classification rules using these features is obtained. We obtain the (α, β)-k-feature set in two phases first a series of extremely powerful reduction techniques, which do not lose the optimal solution, are employed and second, a metaheuristic search to identify the remaining features to be considered or disregarded. Two algorithms were tested with a public domain digital mammography dataset composed of 71 malignant and 75 benign cases. Based on the results provided by the algorithms, we obtain classification rules that employ only a subset of these features.
Using the QAPgrid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic Signatures
Publisher: Springer New York
Date: 29-11-2016
DOI: 10.1007/978-1-4939-6613-4_16
Abstract: In this chapter, we illustrate the use of an integrated mathematical method for joint clustering and visualization of large-scale datasets. In applying these clustering methodologies to biological datasets, we aim to identify differentially expressed genes according to cell type by building molecular signatures supported by statistical scores. In doing so, we also aim to find a global map of highly co-expressed clusters. Variations in these clusters may well indicate other pathological trends and changes.
Comparing meta-heuristic approaches for parallel machine scheduling problems
Publisher: Informa UK Limited
Date: 2002
Related Organisations
No related organisations have been discovered for Pablo Moscato.
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