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PubMed1998

Spectrophotometric quantitative analysis of the main hemoglobin derivatives.

A spectrophotometric multiwavelength method for the simultaneous determination of the main hemoglobin derivatives including oxyhemoglobin, deoxyhemoglobin, carboxyhemoglobin, and methemoglobin has been developed. The choice of analytical wavelengths was made by the methods of information factors and linear programming. The software for the quantitative analysis was developed considering the least square method, linear programming, algebraic background correction, and combined methods including linear programming and algebraic background correction.

Carboxyhemoglobin↗
PubMed2005

Evolving evolutionary algorithms using linear genetic programming.

A new model for evolving Evolutionary Algorithms is proposed in this paper. The model is based on the Linear Genetic Programming (LGP) technique. Every LGP chromosome encodes an EA which is used for solving a particular problem. Several Evolutionary Algorithms for function optimization, the Traveling Salesman Problem and the Quadratic Assignment Problem are evolved by using the considered model. Numerical experiments show that the evolved Evolutionary Algorithms perform similarly and sometimes even better than standard approaches for several well-known benchmarking problems.

Algorithms↗
PubMed1984

Programmable calculator program for linear somatic cell scores to estimate mastitis yield losses.

A programmable calculator program calculates loss of milk yield in dairy cows based on linear somatic cell count scores. The program displays the distribution of the herd by lactation number and linear score for present and optimal goal situations. Loss of yield is in pounds and dollars by cow and herd. The program estimates optimal milk production and numbers of fewer cows at the goal for mastitis infection.

Animals↗
PubMedDate not supplied

A computer program for linear nonparametric and parametric identification of biological data.

A computer program package for parametric ad nonparametric linear system identification of both static and dynamic biological data, written for an LSI-11 minicomputer with 28 K of memory, is described. The program has 11 possible commands including an instructional help command. A user can perform nonparametric spectral analysis and estimation of autocorrelation and partial autocorrelation functions of univariate data and estimate nonparametrically the transfer function and possibly an associated noise series of bivariate data. In addition, the commands provide the user the means to derive a parametric autoregressive moving average model for univariate data, to derive a parametric transfer function and noise model for bivariate data, and to perform several model evaluation tests such as pole-zero cancellation, examination of residual whiteness and uncorrelatedness with the input. The program, consisting of a main program and driver subroutine as well as six overlay segments, may be run interactively or automatically.

Computers↗
PubMed1999

An exact solution for the segment-to-segment multiple sequence alignment problem.

MOTIVATION: In molecular biology, sequence alignment is a crucial tool in studying the structure and function of molecules, as well as the evolution of species. In the segment-to-segment variation of the multiple alignment problem, the input can be seen as a set of non-gapped segment pairs (diagonals). Given a weight function that assigns a weight score to every possible diagonal, the goal is to choose a consistent set of diagonals of maximum weight. We show that the segment-to-segment multiple alignment problem is equivalent to a novel formulation of the Maximum Trace problem: the Generalized Maximum Trace (GMT) problem. Solving this problem to optimality, therefore, may improve upon the previous greedy strategies that are used for solving the segment-to-segment multiple sequence alignment problem. We show that the GMT can be stated in terms of an integer linear program and then solve the integer linear program using methods from polyhedral combinatorics. This leads to a branch-and-cut algorithm for segment-to-segment multiple sequence alignment. RESULTS: We report on our first computational experiences with this novel method and show that the program is able to find optimal solutions for real-world test examples.

Algorithms↗
PubMed2004

Prediction of retention times and efficiency in linear gradient programmed pressure analysis on capillary columns.

A method for the prediction of the retention time and the resolution of chromatographic peaks in different experimental conditions by starting from few experimental data measured in isothermal and isobaric analyses was published previously. In this paper, the same mathematical model was implemented for calculating the retention times and the column efficiency in programmed pressure runs. Some models originated from the Golay equation and reported in the literature are compared, and a new modified equation for the calculation of the peak width at half height is proposed. The procedure for the prediction of the retention time and the peak width at half height at programmed pressure of the carrier gas and different column temperature and linear gradient by using retention data of different compounds obtained in few isobaric runs is described. The prediction of the retention time and the separation efficiency of compounds with different polarity gave good results for the programmed pressure runs with linear gradient. The effect of the variation of the initial parameters of the experimental analyses and of the mathematical model on the accuracy of the prediction has been evaluated.

Chromatography, Gas↗
PubMed1986

Estimating enzyme kinetic parameters: a computer program for linear regression and non-parametric analysis.

An IBM computer program, WILMAN4, is described which calculates the estimates, Km, V and Km/V from initial velocity measurements according to one of four statistical methods. Three of these methods involve linear regression analysis using weights given by assuming: (i) constant absolute error (G.N. Wilkinson, 1961, Biochem J., 80, 324-332), (ii) constant relative error (G. Johansen and R. Lumry, 1961, C.R. Trav. Lab. Carlsberg, 32, 185-214) and (iii) an error function in between the above two cases. (A. Cornish-Bowden, 1976, Principles of Enzyme Kinetics, Butterworths Inc, Boston, Mass., pp. 168-193). The fourth method is a non-parametric procedure derived by Eisenthal and Cornish-Bowden (Biochim. Biophys. Acta, 532 (1974) 268-272). Residuals are obtained by subtracting the experimental and the calculated velocities. Outliers, or residuals which are greater than two experimental standard deviations, can be identified and removed from the data set. If the sequence of positive and negative signs of the residuals is random as determined by a statistical probability calculation, the data set is assumed to obey the Michaelis-Menten equation.

Biometry↗
PubMed1999

Thermal inactivation kinetics of Bacillus stearothermophilus spores using a linear temperature program.

A systematic study of the inactivation kinetics of Bacillus stearothermophilus spores was carried out in nonisothermic heating conditions using a linear temperature increase program and analyzing the experimental data by means of a one-step nonlinear regression. The D and z values estimated are close to those obtained in isothermic conditions and estimated by using a two-step model, first D values are calculated, and then in the second step a z value is deduced (D(121 degrees C) = 3.08 and 4.38 min, respectively, and z = 7 and 7.9 degrees C, respectively). No convergence problems were observed when using the one-step nonlinear regression proposed. The results indicated that the methodology applied in this study can be used to obtain kinetic data for bacterial spores, which could mean a significant reduction in the amount of experimental work employed to generate these data.

Colony Count, Microbial↗
PubMed1977

A new model for measuring breeding genetic distance.

A model is proposed for measuring the genetic 'distance' between two populations having gene frequencies p and p. The measure of distance is based on a hypothetical selection process as follows: From population P a subpopulation P can be selected having gene frequency p. Let Po be the largest subpopulation yielding gene frequency p, then the relative size of Po to p--denoted by thetao (p,p)--is a measure of the 'closeness' of populations having gene frequencies p and p, and 1-thetao (p,p) whould be a reasonable measure of genetic distance. We show that the calculation of thetao (p,p) is a special case of the linear programming problem and derive algebraic expressions for thetao (p,p) in the two-allele case. We discuse some of the implications of the use of this measure of distance and compare it to others which have been proposed. We use linear programming methods to calculate genetic distance for three alleles.

Alleles↗
PubMedDate not supplied

A primary shift rotation nurse scheduling using zero-one linear goal programming.

In this study, the author discusses the effect of nurse shift schedules on circadian rhythm and some important ergonomics criteria. The author also reviews and compares different nurse shift scheduling methods via the criteria of flexibility, fairness, continuity in shift assignments, nurses' preferences, and ergonomics principles. In this article, a primary shift rotation system is proposed to provide better continuity in shift assignments to satisfy nurses' preferences. The primary shift rotation system is modeled as a zero-one linear goal programming (LGP) problem. To generate the shift assignment for a unit with 13 nurses, the zero-one LGP model takes less than 3 minutes on average, whereas the head nurses spend approximately 2 to 3 hours on shift scheduling. This study reports the process of implementing the primary shift rotation system.

Circadian Rhythm↗
PubMed2004

Optimization models for cancer classification: extracting gene interaction information from microarray expression data.

MOTIVATION: Microarray data appear particularly useful to investigate mechanisms in cancer biology and represent one of the most powerful tools to uncover the genetic mechanisms causing loss of cell cycle control. Recently, several different methods to employ microarray data as a diagnostic tool in cancer classification have been proposed. These procedures take changes in the expression of particular genes into account but do not consider disruptions in certain gene interactions caused by the tumor. It is probable that some genes participating in tumor development do not change their expression level dramatically. Thus, they cannot be detected by simple classification approaches used previously. For these reasons, a classification procedure exploiting information related to changes in gene interactions is needed. RESULTS: We propose a MAximal MArgin Linear Programming (MAMA) method for the classification of tumor samples based on microarray data. This procedure detects groups of genes and constructs models (features) that strongly correlate with particular tumor types. The detected features include genes whose functional relations are changed for particular cancer types. The proposed method was tested on two publicly available datasets and demonstrated a prediction ability superior to previously employed classification schemes. AVAILABILITY: The MAMA system was developed using the linear programming system LINDO http://www.lindo.com. A Perl script that specifies the optimization problem for this software is available upon request from the authors.

Algorithms↗
PubMed1983

Radon daughter plateout--II. Prediction model.

By a linear programming procedure, we have optimized the Jacobi room model to fit our data on the partitioning of radon daughters between air and wall surfaces (plateout), obtained at high radon concentrations in a small chamber. Subsequently, the optimized model yielded estimates that compared well with plateout data obtained at lower concentrations in a room-sized chamber. (The experimental work is described separately.) The major change made in the Jacobi model was to reduce the deposition velocity of free airborne radon daughters from 1 to 0.05 cm/sec. This value was obtained by using a fast algorithm to solve the linear programming to arrive at the "best fit". Lesser changes were made in other parameters.

Air↗
PubMed1987

Optimization of beam weights under dose-volume restrictions.

A basic problem in treatment planning is the selection of weights for a set of beams which will yield the largest tumor dose under constraints limiting the doses received in specified fractions of different normal tissue structures. This report describes a method for formulating and solving this optimization problem as a combinatorial linear program. An illustration is provided by a problem in planning treatment of a thoracic tumor, in which no more than 1/2 or 2/3 of the lung is permitted to receive greater than 20 Gy and no part of the spinal cord allowed to receive greater than 45 Gy. The optimization technique was applied to this example to determine how the maximum tumor dose is affected by changes in the normal tissue constraints and the addition of a tumor dose homogeneity restriction. The linear programming technique yielded a rigorous and efficient determination of the beam weights for the thoracic plan considered. An exhaustive specification of all the underlying linear programs allows problems of moderate dimensions to be solved, while developments in mathematical programming and computer processing suggest approaches to problems of greater complexity.

Humans↗
PubMed2006

Scaling and universality of the complexity of analog computation.

We apply a probabilistic approach to study the computational complexity of analog computers which solve linear programming problems. We numerically analyze various ensembles of linear programming problems and obtain, for each of these ensembles, the probability distribution functions of certain quantities which measure the computational complexity, known as the convergence rate, the barrier and the computation time. We find that in the limit of very large problems these probability distributions are universal scaling functions. In other words, the probability distribution function for each of these three quantities becomes, in the limit of large problem size, a function of a single scaling variable, which is a certain composition of the quantity in question and the size of the system. Moreover, various ensembles studied seem to lead essentially to the same scaling functions, which depend only on the variance of the ensemble. These results extend analytical and numerical results obtained recently for the Gaussian ensemble, and support the conjecture that these scaling functions are universal.

Journal Article↗
PubMedDate not supplied

MLTIDOSE: a multiple-dose simulation program for linear systems characterized by exponential functions.

MLTIDOSE is a multiple-dose simulation program for use on IBM PC (and compatible) computers. It assumes dose-independent disposition and absorption (i.e., a linear system) and simulates blood concentration-time profiles (over a range of times or at specific times) upon administration of any combination of intravascular (i.v.) (bolus and/or intermittent constant rate infusions) and extravascular (e.v.) doses of fixed or variable size, administered at fixed or variable intervals. Input requirements include pharmacokinetic parameters obtained following single-dose administration (entered from the keyboard or from a data file). Options for printing data to files (e.g., ASCII and DIF) for further use are also provided.

Computer Simulation↗
PubMedDate not supplied

INAKT--an interactive non-linear regression program for enzyme inactivation and affinity labelling studies.

An interactive program for analysing enzyme activity-time data using non-linear regression analysis is described. Protection studies can also be dealt with. The program computes inactivation rates, dissociation constants and promotion or inhibition parameters with their standard errors. It can also be used to distinguish different inactivation models. The program is written in SIMULA and is menu-oriented for refining or correcting data at the different levels of computing.

Affinity Labels↗
PubMed2005

Neighborliness of randomly projected simplices in high dimensions.

Let A be a d x n matrix and T = T(n-1) be the standard simplex in Rn. Suppose that d and n are both large and comparable: d approximately deltan, delta in (0, 1). We count the faces of the projected simplex AT when the projector A is chosen uniformly at random from the Grassmann manifold of d-dimensional orthoprojectors of Rn. We derive rhoN(delta) > 0 with the property that, for any rho < rhoN(delta), with overwhelming probability for large d, the number of k-dimensional faces of P = AT is exactly the same as for T, for 0 < or = k < or = rhod. This implies that P is left floor rhod right floor-neighborly, and its skeleton Skel(left floor rhod right floor)(P) is combinatorially equivalent to Skel( left floor rhod right floor)(T). We also study a weaker notion of neighborliness where the numbers of k-dimensional faces f(k)(P) > or = f(k)(T)(1-epsilon). Vershik and Sporyshev previously showed existence of a threshold rhoVS(delta) > 0 at which phase transition occurs in k/d. We compute and display rhoVS and compare with rhoN. Corollaries are as follows. (1) The convex hull of n Gaussian samples in Rd, with n large and proportional to d, has the same k-skeleton as the (n-1) simplex, for k < rhoN (d/n)d(1 + oP(1)). (2) There is a "phase transition" in the ability of linear programming to find the sparsest nonnegative solution to systems of underdetermined linear equations. For most systems having a solution with fewer than rhoVS(d/n)d(1 + o(1)) nonzeros, linear programming will find that solution.

Journal Article↗