Method for Excluding Noise Features in Applying a Learning Machine

Previous works have demonstrated that a computerized learning machine could be successfully applied to predicting the presence or absence of a certain microbial feature in a microorganism. To achieve the prediction, however, the presence or absence of many other features must be examined beforehand. This paper deals with the method for decreasing the number of characters that must be examined prior to the prediction. In the six instances studied, this number could be decreased from 93 to 11 in the most fortunate case and to 26 in the most unfortunate case, without causing deterioration of the prediction results.     

An Algorithmic Method for Reducing Conductance-based Neuron Models

Although conductance-based neural models provide a realistic depiction of neuronal activity, their complexity often limits effective implementation and analysis. Neuronal model reduction methods provide a means to reduce model complexity while retaining the original model’s realism and relevance. Such methods, however, typically include ad hoc components that require that the modeler already be intimately familiar with the dynamics of the original model. We present an automated, algorithmic method for reducing conductance-based neuron models using the method of equivalent potentials (Kelper et al., Biol Cybern 66(5):381–387, 1992) Our results demonstrate that this algorithm is able to reduce the complexity of the original model with minimal performance loss, and requires minimal prior knowledge of the model’s dynamics. Furthermore, by utilizing a cost function based on the contribution of each state variable to the total conductance of the model, the performance of the algorithm can be significantly improved.     

Calcium Oscillations

Calcium signaling results from a complex interplay between activation and inactivation of intracellular and extracellular calcium permeable channels. This complexity is obvious from the pattern of calcium signals observed with modest, physiological concentrations of calcium-mobilizing agonists, which typically present as sequential regenerative discharges of stored calcium, a process referred to as calcium oscillations. In this review, we discuss recent advances in understanding the underlying mechanism of calcium oscillations through the power of mathematical modeling. We also summarize recent findings on the role of calcium entry through store-operated channels in sustaining calcium oscillations and in the mechanism by which calcium oscillations couple to downstream effectors.Calcium ions participate in a multiplicity of physiological and pathological functions. Among the most intensely studied, and the major focus of this article, is the role of Ca²⁺ as a cellular signal. Elevations in cytoplasmic Ca²⁺ mediate a plethora of cellular responses, ranging from extremely rapid events (muscle contraction, neurosecretion), to slower more subtle responses (cell division, differentiation, apoptosis). In contrast to most cellular signals, it is a relatively simple matter to observe changes in cytoplasmic Ca²⁺ in real time in living cells. As a result, the truly complex nature of Ca²⁺ signaling pathways has been revealed. The challenge is to understand what regulates these signals and what the biological significance of their complexity is.In the majority of laboratory experiments examining effects of various stimulants on Ca²⁺ signaling, supramaximal concentrations of activating agonists are employed resulting in rapid, robust, and often sustained increases in cytoplasmic Ca²⁺. It has long been appreciated that these signals result from a coordinated release of intracellular stores and increased Ca²⁺ influx across the plasma membrane (Bohr, 1973; Putney et al. 1981). The intracellular release of Ca²⁺ most commonly results from the Ca²⁺ releasing action of the phospholipase C-derived second messenger, inositol 1,4,5-trisphosphate (InsP₃) (Streb et al. 1983), whereas the entry of Ca²⁺ is because of the activation of store-operated channels in the plasma membrane (Putney 1986). However, it is becoming increasingly clear that these large sustained elevations seldom occur with physiological levels of stimulants. Rather the more common pattern of Ca²⁺ signaling, in both excitable and nonexcitable cells is a pattern of periodic discharges and/or entry of Ca²⁺. In excitable cells, such as the heart for example, these may be comprised of, or initiated by regenerative all-or-none plasma membrane channel activation, the Ca²⁺ action potential (Tsien et al. 1986) with amplification by intracellular Ca²⁺ release (Fabiato 1983). In nonexcitable cells, these spikes of cytoplasmic Ca²⁺ arise from regenerative discharge of stored Ca²⁺, a process generally termed Ca²⁺ oscillations (Prince and Berridge 1973; Woods et al. 1986). Like Ca²⁺ action potentials, these all-or-none discharges of Ca²⁺ represent a form of excitable behavior of the intracellular Ca²⁺ release signaling mechanism. However, because it is not possible to easily monitor and control the transmembrane chemical and biophysical parameters, as is the case for excitable plasma membrane behavior, it has been more difficult to fully understand the basic mechanisms by which these Ca²⁺ oscillations arise. Thus, although the question has been exhaustively studied for well over twenty years, there is still uncertainty and controversy over the underlying processes that give rise to Ca²⁺ oscillations. A number of reviews have discussed these issues at some length (Berridge and Galione 1988; Rink and Jacob 1989; Berridge 1990; Petersen and Wakui 1990; Berridge 1991; Cuthbertson and Cobbold 1991; Meyer and Stryer 1991; Hellman et al. 1992; Tepikin and Petersen 1992; Thomas et al. 1992; Dupont and Goldbeter 1993; Keizer 1993; Sneyd et al. 1994; Li et al. 1995; Thomas et al. 1996; Shuttleworth 1999; Lewis 2003; Dupont et al. 2007). In the current treatment, we have chosen to focus on two important aspects of Ca²⁺ oscillations. First, we review the available evidence for various computational models of Ca²⁺ oscillations that employ a quantitative approach to validate or repudiate specific mechanisms. Second, we consider the interrelationship between Ca²⁺ oscillations and plasma membrane Ca²⁺ influx mechanisms, with the view that we may learn more of the physiological function that these intracellular discharges of Ca²⁺ provide.     

Algorithmic Optimisation Method for Improving Use Case Points Estimation

This paper presents a new size estimation method that can be used to estimate size level for software engineering projects. The Algorithmic Optimisation Method is based on Use Case Points and on Multiple Least Square Regression. The method is derived into three phases. The first phase deals with calculation Use Case Points and correction coefficients values. Correction coefficients are obtained by using Multiple Least Square Regression. New project is estimated in the second and third phase. In the second phase Use Case Points parameters for new estimation are set up and in the third phase project estimation is performed. Final estimation is obtained by using newly developed estimation equation, which used two correction coefficients. The Algorithmic Optimisation Method performs approximately 43% better than the Use Case Points method, based on their magnitude of relative error score. All results were evaluated by standard approach: visual inspection, goodness of fit measure and statistical significance.     

Algorithmic approaches for identification of RNA editing sites.

Recently a number of groups have introduced computational methods for the detection of A-to-I RNA editing sites. These approaches have resulted in finding thousands of editing sites within the genomic repeats, as well as a few novel genetic recoding sites. We review these recent advancements, emphasizing the principles underlying the various methods used. Possible directions for extending these methods are discussed.     

Algorithmic method for assessing urinary incontinence in elderly women.

In young patients the assessment of urinary incontinence is based increasingly on the results of complex urodynamic investigations. The value of such techniques in the elderly, however, is as yet unproved. Based on the clinical and urodynamic findings in 100 incontinent elderly women an algorithmic method for managing such patients was devised. A retrospective study comparing the algorithmic outcome with the results of standard urodynamic assessment showed that 60% of invasive investigations could be avoided by this method with minimal loss of diagnostic accuracy.     

Algorithmic strategies for the single nucleotide polymorphism haplotype assembly problem

With the consensus human genome sequenced and many other sequencing projects at varying stages of completion, greater attention is being paid to the genetic differences among individuals and the abilities of those differences to predict phenotypes. A significant obstacle to such work is the difficulty and expense of determining haplotypes--sets of variants genetically linked because of their proximity on the genome--for large numbers of individuals for use in association studies. This paper presents some algorithmic considerations in a new approach for haplotype determination: inferring haplotypes from localised polymorphism data gathered from short genome 'fragments.' Formalised models of the biological system under consideration are examined, given a variety of assumptions about the goal of the problem and the character of optimal solutions. Some theoretical results and algorithms for handling haplotype assembly given the different models are then sketched. The primary conclusion is that some important simplified variants of the problem yield tractable problems while more general variants tend to be intractable in the worst case.     

Choosing Priority-Setting Criteria for Carcinogens

For priority-setting purposes, simple criteria are needed to estimate, provisionally, the inherent properties of potential carcinogens for which adequate data are not available. Expected utility analysis is used to evaluate three such criteria from a decision-theoretic point of view: (1) the species criterion, which assigns lower priority to experimental than to epidemiological carcinogens, (2) the genotoxicity criterion, which prioritizes substances known to be genotoxic, and (3) the potency criterion, which apportions priorities according to carcinogenic potencies that are derived from animal experiments. The outcome of this analysis is favorable to the potency criterion. It is concluded that considerations of potency should have a much more prominent role than what they have in current regulatory practice.     

Algorithmic specification as a technique for computing with informal biological models

Conceptual biological models can sometimes be usefully expressed in algorithmic form. Models expressed in this way are often capable of capturing more aspects of the complete system than could be captured by other modeling approaches, though in general each aspect is captured in a highly simplified way. Two examples are given. The first involves algorithmic specification of the theory of evolution. The second involves a recently implemented computational model of the brain. Work with such models has, to some extent, the style of experimental work. It often suggests interesting problems or exposes subtle features of the system whose importance has been overlooked.