Volume 15, Issue 4
Editorial
New books
Bioinformatics
Interacting Psycho-economic Expectations Ratios with Equity/debt Realities Suggests a Crisis Warning Method215-222
Barry Thornton, Elysia Thornton-Benko, Layna Groen
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The recent April 2011 meeting of the G20 countries considered possible development of a global early warning system to avoid any future financial crisis. Psycho-economic factors are strong drivers of greed, fear and non-rational behavior and experience shows that they should not be excluded from such a project. Rational, logical behavior for attitude and actions has been an assumption in most financial models prior to the advent of the 2008 crisis. In recent years there has been an increasing interest in relating financial activity to phenomena in physics, turbulence, neurology and recent fMRI experiments show that cortical interactions for decisions are affected by previous experience. We use an extension of two Lotka-Volterra (LV) interactive equations used in a model for the 2008 crisis but now with fluctuation theory from chemical physics to interact the two previously used heterogenous interacting agents, the psycho-economic ratio CE of investor expectations (favourable/unfavourable) and the reality ratio of equity/debt. The model provides a variable, M, for uncertainties in CE arising from the ability of the economy to affect the financial sector. A condition obtained for keeping rates of change in M small to avoid divergence of spontaneous fluctuations, provides a quantifiable time dependent entity which can act as a warning of impending crisis. The conditional expression appears to be related to an extension of Ohm's law as in a recently discovered "chip" and memory; the memristor. The possible role of subthreshold legacies in CE from the previous crisis appears to be possible and related to recent neurological findings.
Bioactive Peptides: A Review -- Paper rectracted due to Copyright violation223-250
Shrikant Sharma, Raghvendar Singh, Shashank Rana
Comparative Analysis using Bayesian Approach to Neural Network of Translational Initiation Sites in Alternative Polymorphic Context251-260
Nurul Arneida Husin, Nanna Suryana Herman, Burairah Hussin
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Widely accepted as an important signal for gene discovery, translation initiation sites (TIS) in weak context has been the main focus in this paper. Many TIS prediction programs have been developed for optimal context, but they fail to successfully predict the start codon if the contexts conditions are in weak positions. The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study. The first approach of neural network includes training on algorithms of Resilient Backpropagation, Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt. The outputs are used in comparison with Bayesian Neural Network for efficiency comparison. The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy. In second approach, the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%. The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method, and increasing the length of the window sequence to 201. The result shows that the built model successfully increases the accuracy by 96.0%. In comparison, the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%.
Development of a Tool for the Analysis of Plant Stress Proteins261-266
Muhammad Ali, Rana Rehan Khalid, Muhammad Nawaz, Nauman Qamar
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The recent explosion of biological data and the accompaniment proliferation of distributed databases make it challenging for biologists and bioinformatists to discover the best and concise data resources for their needs, and the most efficient way to access and use them. For the biologist, running bioinformatics analyses involve a time-consuming management of data and tools. Users need support to organize their work, retrieve parameters and reproduce their analyses. They also need to be able to combine their analytic tools using a safe data flow software mechanism. Finally we have designed a system, Stress Gene catalog, to provide a flexible and usable web environment for defining and running bioinformatics analyses for the ease of researchers working in plants sciences. It embeds simple yet powerful data management features that allow the user to reproduce analyses and to combine tools using an adobe flex tool. Rice Stress gene catalog can also act as a front end to provide a unified view of already-existing rice stress gene families and their protein members along with their FASTA sequences. Users can analyze genomic and proteomic data by using the tools that has been integrated in the software (tools for alignments, multiple sequence comparison and to compare a novel sequence with those contained in nucleotide and protein databases).
Bioprocess systems
Optical Biosensor with Multienzyme System Immobilized onto Hybrid Membrane for Pesticides Determination267-276
Lyubov Yotova, Nourelhoda Medhat
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A construction of optical biosensor based on simultaneous immobilization of acetylcholinesterase and choline oxidase enzymes for the detection of pesticides residues is described. Different kinds of novel SiO2 hybrid membranes were synthesized to be suitable for optical biosensors using sol-gel techniques. The bioactive component of the sensor consists of a multi-enzyme system including acetylcholinesterase and choline oxidase covalently immobilized on new hybrid membranes. The sensor exhibited a linear response to acetylcholine in a concentration range of 2.5 - 30 mM. Inhibition plots obtained from testing carbamate (carbofuran) pesticides exhibited concentration dependent behaviour and showed linear profiles in concentration ranges between 5x10-8 - 5x10-7 M for carbofuran. The factors affecting the constructed optical biosensors were investigated.
Biomedical systems
Optimization of Substitution Matrix for Sequence Alignment of Major Capsid Proteins of Human Herpes Simplex Virus277-284
Vipan Kumar Sohpal, Amarpal Singh, Apurba Dey
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Protein sequence alignment has become an informative tool in modern molecular biology research. A number of substitution matrices have been readily available for sequence alignments, but it is challenging task to compute optimal matrices for alignment accuracy. Here, we used the parameter optimization procedure to select the optimal Q of substitution matrices for major viral capsid protein of human herpes simplex virus. Results predict that Blosum matrix is most accurate on alignment benchmarks, and Blosum 60 provides the optimal Q in all substitution matrices. PAM 200 matrices results slightly below than Blosum 60, while VTML matrices are intermediate of PAM and VT matrices under dynamic programming.

© 2011, BAS, Institute of Biophysics and Biomedical Engineering