90 research outputs found
Biology helps you to win a game
We present a game of interacting agents which mimics the complex dynamics
found in many natural and social systems. These agents modify their strategies
periodically, depending on their performances using genetic crossover
mechanisms, inspired by biology. We study the performances of the agents under
different conditions, and how they adapt themselves. In addition the dynamics
of the game is investigated.Comment: 4 pages including 6 figures. Uses REVTeX4. Submitted for Conference
Proceedings of the "Unconventional Applications of Statistical Physics",
Kolkat
Searching good strategies in adaptive minority games
In this paper we introduce adaptation mechanism based on genetic algorithms
in minority games. If agents find their performances too low, they modify their
strategies in hope to improve their performances and become more successful.
One aim of this study is to find out what happens at the system as well as at
the individual agent level. We observe that adaptation remarkably tightens the
competition among the agents, and tries to pull the collective system into a
state where the aggregate utility is the largest. We first make a brief
comparative study of the different adaptation mechanisms and then present in
more detail parametric studies. These different adaptation mechanisms broaden
the scope of the applications of minority games to the study of complex
systems.Comment: 8 pages including 9 figures. Uses REVTeX
Gender, Contraceptives and Individual Metabolic Predisposition Shape a Healthy Plasma Lipidome
Lipidomics of human blood plasma is an emerging biomarker discovery approach that compares lipid profiles under pathological and physiologically normal conditions, but how a healthy lipidome varies within the population is poorly understood. By quantifying 281 molecular species from 27 major lipid classes in the plasma of 71 healthy young Caucasians whose 35 clinical blood test and anthropometric indices matched the medical norm, we provided a comprehensive, expandable and clinically relevant resource of reference molar concentrations of individual lipids. We established that gender is a major lipidomic factor, whose impact is strongly enhanced by hormonal contraceptives and mediated by sex hormone-binding globulin. In lipidomics epidemiological studies should avoid mixed-gender cohorts and females taking hormonal contraceptives should be considered as a separate sub-cohort. Within a gender-restricted cohort lipidomics revealed a compositional signature that indicates the predisposition towards an early development of metabolic syndrome in ca. 25% of healthy male individuals suggesting a healthy plasma lipidome as resource for early biomarker discovery
Altered Metabolic Signature in Pre-Diabetic NOD Mice
Altered metabolism proceeding seroconversion in children progressing to Type 1 diabetes has previously been demonstrated. We tested the hypothesis that non-obese diabetic (NOD) mice show a similarly altered metabolic profile compared to C57BL/6 mice. Blood samples from NOD and C57BL/6 female mice was collected at 0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 13 and 15 weeks and the metabolite content was analyzed using GC-MS. Based on the data of 89 identified metabolites OPLS-DA analysis was employed to determine the most discriminative metabolites. In silico analysis of potential involved metabolic enzymes was performed using the dbSNP data base. Already at 0 weeks NOD mice displayed a unique metabolic signature compared to C57BL/6. A shift in the metabolism was observed for both strains the first weeks of life, a pattern that stabilized after 5 weeks of age. Multivariate analysis revealed the most discriminative metabolites, which included inosine and glutamic acid. In silico analysis of the genes in the involved metabolic pathways revealed several SNPs in either regulatory or coding regions, some in previously defined insulin dependent diabetes (Idd) regions. Our result shows that NOD mice display an altered metabolic profile that is partly resembling the previously observation made in children progressing to Type 1 diabetes. The level of glutamic acid was one of the most discriminative metabolites in addition to several metabolites in the TCA cycle and nucleic acid components. The in silico analysis indicated that the genes responsible for this reside within previously defined Idd regions
Mesoscopic effects in an agent-based bargaining model in regular lattices
The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based
model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The
model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global
interaction. Each agent is endowed with a memory and plays the best reply against the opponent’s most frequent demand.
We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which
the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global
interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction
networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can
lead to new persistent regimes different from those found in previous research. In particular, community structure in the
intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the
hindering diffusion effect of fluctuating agents at their borders.Spanish Ministry of Science and Innovation, references TIN2008-06464-C03-02 and CSD2010-00034 (CONSOLIDER-INGENIO 2010), and by the Junta de Castilla y Leon, references VA006A009, BU034A08 and GREX251-200
COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access
Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative ‘coordination of standards in metabolomics’ (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities’ participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards
Bioinformatics tools for cancer metabolomics
It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages
Metabolic Regulation in Progression to Autoimmune Diabetes
Recent evidence from serum metabolomics indicates that specific metabolic disturbances precede β-cell autoimmunity in humans and can be used to identify those children who subsequently progress to type 1 diabetes. The mechanisms behind these disturbances are unknown. Here we show the specificity of the pre-autoimmune metabolic changes, as indicated by their conservation in a murine model of type 1 diabetes. We performed a study in non-obese prediabetic (NOD) mice which recapitulated the design of the human study and derived the metabolic states from longitudinal lipidomics data. We show that female NOD mice who later progress to autoimmune diabetes exhibit the same lipidomic pattern as prediabetic children. These metabolic changes are accompanied by enhanced glucose-stimulated insulin secretion, normoglycemia, upregulation of insulinotropic amino acids in islets, elevated plasma leptin and adiponectin, and diminished gut microbial diversity of the Clostridium leptum group. Together, the findings indicate that autoimmune diabetes is preceded by a state of increased metabolic demands on the islets resulting in elevated insulin secretion and suggest alternative metabolic related pathways as therapeutic targets to prevent diabetes
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