Microarray Gene Expression Analysis Using Fuzzy Logic (MGA-FL)

In the past decade, DNA microarrays have fundamentally changed the way we study complex biological systems. By measuring the expression levels of thousands of transcripts, the paradigm of studying organisms has shifted from focusing on the local phenomena of a few genes to surveying the whole genome. DNA microarrays are used in a variety of ways, from simple comparisons between two samples to more intricate time-series studies. With the large number of genes being studied, the dimensionality of the problem is inevitably high. The analysis of microarray data thus requires specific approaches. In the case of time-series microarray studies, data analysis is further complicated by the correlation between successive time points in a series.In this review, we survey the methodologies used in the analysis of static and time-series microarray data, covering data pre-processing, identification of differentially expressed genes, profile pattern recognition, pathway analysis, and network reconstruction. When available, examples of their use in mammalian cell cultures are presented.

A photochemical/chemical direct method of synthesizing high-performance deoxyribonucleic acid chips for rapid and parallel gene analysis

Development of public toxicogenomics software for microarray data management and analysis

The nucleosome remodeling and deacetylation (NuRD) complex is required for modulating the transcription of essential pluripotency genes in ESC self-renewal. MBD3 is considered a key player in the formation of a functional NuRD complex. The recruitment of MBD3 to methylated promoters may require other prerequisite factors. We show that cyclin-dependent kinase 2-associated protein 1 (CDK2AP1), an essential gene for early embryonic development, plays a role in pluripotency of ESC by engaging MBD3 to the promoter region of Wnt signaling genes. The occupancy of MBD3 on several promoters of Wnt genes was significantly lost in the absence of CDK2AP1, resulting in hyperactivation of Wnt. We propose that the transcriptional modulation of the Wnt pathway mediated by NuRD requires the presence of essential auxiliary components such as CDK2AP1, which may aid the association of the complex with specific focal regions of the target promoters.

Spotted cDNA microarrays are emerging as a powerful and cost-effective tool for large-scale analysis of gene expression. Microarrays can be used to measure the relative quantities of specific mRNAs in two or more tissue samples for thousands of genes simultaneously. While the power of this technology has been recognized, many open questions remain about appropriate analysis of microarray data. One question is how to make valid estimates of the relative expression for genes that are not biased by ancillary sources of variation. Recognizing that there is inherent "noise" in microarray data, how does one estimate the error variation associated with an estimated change in expression, i.e., how does one construct the error bars? We demonstrate that ANOVA methods can be used to normalize microarray data and provide estimates of changes in gene expression that are corrected for potential confounding effects. This approach establishes a framework for the general analysis and interpretation of microarray data.

Application of the S-score algorithm for analysis of oligonucleotide microarrays

DNA Microarray Technique Current Analytical Methods of DNA Microarray Data Advantages and Disadvantages Current Application of DNA Microarray Technique in Medicine A Novel Method for DNA Microarray Data Analysis Future Directions.

Fuzzy logic is an approach that helps in computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic. Recommender systems represent user preferences for the purpose of suggesting items to read or browse. They have become fundamental applications in electronic commerce and information access, providing suggestions that effectively prune large information spaces so that users are directed toward those items that best meet their needs and preferences. A variety of techniques have been proposed for performing recommendation, including content-based, collaborative, knowledge-based and other techniques. Our method implements fuzzy logic to find a set of articles related to other articles which can be recommended to a reader. There is a simple reason behind using fuzzy logic. Related or recommendable news articles are not easily translated into the absolute terms of 0 and 1. We cannot absolutely point out a certain article 'X' and say that it is related to 'Y'. That is why we tried to develop a fuzzy system from several attributes of a news article which will eventually describe whether an article is worth for recommendation to a user or not.

Deoxyribonucleic acid (DNA) transposons are mobile elements that move via a DNA intermediate. The (haploid) human genome harbours more than 300 000 DNA transposon copies, accounting for approximately 3% of the total genomic DNA. Nearly one‐third of these elements are specific to the primate lineage, but there is no evidence for transposition activity within the past 40 million years. However, there is growing evidence that DNA transposons have contributed in shaping the current genome architecture of humans and have been a recurrent source of new regulatory and coding DNA throughout mammalian evolution. Notably, more than 50 human genes are currently known to descend from transposase sequences recycled to perform diverse cellular functions. Key Concepts: DNA (or class 2) transposons represent a minority of the mobile genetic elements populating mammalian genomes, but still account for more DNA in our genome than all protein‐coding sequences. DNA transposition was once very active in mammals and has generated approximately 100 000 primate‐specific insertions in our genome. DNA transposon germline activity suddenly ceased ∼40 million years ago in the human lineage, but has persisted in other mammalian lineages – most prominently and recently in vesper bats. Despite the lack of current transposition activity, DNA transposons may still be promoting genomic rearrangements, including recurrent ectopic recombination events associated with pathologies. Like many other mobile elements in the human genome, some DNA transposons have been incorporated into the regulatory apparatus of the genome through the donation of enhancers and regulatory elements modulating adjacent gene expression. Transposases have been a source of coding sequences for the assembly of several new genes during vertebrate evolution, including at least 50 genes in the human genome. The function of most human transposase‐derived genes remains unknown or poorly understood, but some have emerged as key regulators for a variety of cellular processes.

Expression profiling: Opportunities and pitfalls and impact on the study and management of allergic diseases

We introduce methods for the exploratory analysis of microarray data, especially focusing on cluster algorithms. Benefits and problems are discussed. We describe application and suitability of unsupervised learning methods for the classification of gene expression data. Cluster algorithms are treated in more detail, including assessment of cluster quality. When dealing with microarray data, most cluster algorithms must be applied with caution. As long as the structure of the true generating models of such data is not fully understood, the use of simple algorithms seems to be more appropriate than the application of complex black-box algorithms. New methods explicitly targeted to the analysis of microarray data are increasingly being developed in order to increase the amount of useful information extracted from the experiments. Unsupervised methods can be a helpful tool for the analysis of microarray data, but a critical choice of the algorithm and a careful interpretation of the results are required in order to avoid false conclusions.

Implementing asset-wide intelligent digital oilfield (iDOF) solutions is more complex than simply "integrating technology." For iDOF to be truly successful and achieve expectations, concepts from different fields, such as artificial intelligence (AI) or soft computing techniques, must be used to help orchestrate the technology and required functionality to deliver the "intelligence" required to meet the challenges associated with optimizing oil production. Fuzzy logic (FzL) is a type of probabilistic logic that is approximate as opposed to being precise or exact. FzL can have a range of truth values or determine a likelihood of being true. The process of diagnosis for artificial lift systems has always relied solely on the engineer’s criteria when analyzing data. It is not uncommon for two engineers with similar backgrounds to have, on the basis of the same data, differing opinions of a well problem. It is, however, uncommon that both engineers are either completely incorrect or correct in their judgment, which begs the question as to why this occurs. When traditional binary logic (true or false) is used for well analysis, the outcomes must be either this or that, simply because of the nature of binary logic. Unfortunately, most of the time, the results of well diagnoses, especially when attempting to use a predictive approach, cannot be properly represented with a yes-no approach, which means both engineers would be correct to a certain degree; in FzL, this is called the "degree of truth." FzL incorporates the rationale of having different degrees of truth into the world of well diagnosis and adds tremendous value by raising the issue of different conditions having certain degrees of truth of being in development. The FzL in this solution was built on a set of worldwide expert rules and converts these rules to their mathematical equivalents. Production operation’s expert rules are used to formulate the conditional statements that comprise FzL (e.g., if the motor temperature exceeds a certain limit, the pump can burn out). This paper discusses how the AI tool determines trends by calculating a slope for a predetermined period of time for the different sensor signals and compares these sets of trends with pre-established sets of rules. The closeness of the measured trends to the models is expressed as "conditioners" that represent the likelihood of each trend occurring over a period of time. This technique has proven to be very useful in real-time monitoring for production engineers, helping them to perform fast predictions and pump diagnostics to predict unexpected problems, such as pump wear, gas interference, tubing leaks, viscous forces, and solids-plugged intakes. Several case histories are discussed in this paper. The ultimate goal of this smart flow is to deliver field-level actions that extend pump life and reduce pump downtime.

The multiplicity of heavy-chain variable-region (VH) genes in mouse and human DNA has been estimated using a mouse heavy-(H) chain cDNA clone. We found about 10 hybridization components in mouse DNA and about 20 components in human DNA. Cross-hybridization studies of variable region (V) genes indicate that these components represent the numbers of genes within the VH subgroups of each of these species. The arrangement and rearrangement of the H-chain gamma subclasses have been studied in order to assess possible mechanisms of the H-chain switch. Evidence has been found for rearrangement events involving the gamma 2a and gamma 2b constant-region (CH) genes in DNA from cells making IgG2a and IgG2b respectively. In addition we found that cells making IgG2a lack detectable genes for gamma1 and gamma 2b. Both sets of observations are discussed in relation to H-chain diversity and the switch.

Erosion-hazard assessment is an important aspect in the management of a river basin such as Siak River Basin, Riau Province, Indonesia. This study presents an application of fuzzy logic approach to develop erosion risk map based on geographic information system. Fuzzy logic is a computing approach based on “degrees of truth” rather than the usual “true or false” (1 or 0) Boolean logic on which the modern computer is based. The results of the erosion risk map were verified by using field measurements. The verification result shows that the parameter of soil-erodibility (K) indicates a good agreement with field measurement data. The classification of soil-erodibility (K) as the result of validation were: very low (0.0–0.1), medium (0.21-0.32), high (0.44-0.55) and very high (0.56-0.64). The results obtained from this study show that the erosion risk map of Siak River Basin were dominantly classified as medium level which cover about 68.54%. The other classifications were high and very low erosion level which cover about 28.84% and 2.61% respectively.

This chapter deals with fuzzy logic in Zadeh’s ‘narrow sense’ [27], pointing to t-norm based truth functional logics, where the truth values model ‘degrees of truth’, identified with reals from the unit interval [0,1]. In particular, we are interested in Łukasiewicz logic Ł and some of its variants, but also in Godel logic G, and in Product logic P. The literature on formal deduction systems for these and related many-valued logics is vast and even more has been written about their algebraic background. We refer to the monographs [23], [22], and [10] for more information and references. Most authors take the usefulness of these logics in the context of approximate reasoning, i.e., reasoning with vague and imprecise notions for granted. However the corresponding proof systems are hardly ever explicitly related to models of correct reasoning with vague information. In other words: the challenge to derive particular fuzzy logics from first principles about approximate reasoning is not addressed explicitly. The reference to general models of reasoning and to theories of vagueness – a prolific discourse in contemporary analytic philosophy – is only implicit, if not simply missing, in most presentations of inference systems for fuzzy logics. Some notable exceptions, where an explicit semantic foundation for particular fuzzy logics is aimed at, are: Ruspini’s similarity semantics [35]; voting semantics [25]; ‘re-randomizing semantics’ [24]; measurement-theoretic justifications [7]; the Ulam-Renyi game based interpretation of D. Mundici [29]; and ‘acceptability semantics’ of J. Paris [31]. As we have argued elsewhere [12], these formal semantics for various t-norm based logics (in particular Łukasiewicz logic) should be placed in the wider discourse about adequate theories of vagueness, a prolific subfield of analytic philosophy.