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Results for “Programming, Linear”

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PubMed1986

A discrete model of bacterial metabolism.

This paper describes a computer model of the intermediary metabolism of bacteria during steady-state growth and during adaptations, e.g. to new carbon sources. Metabolic regulation is represented as a process of optimisation, in which the trend is towards improved metabolic performance. The model uses linear programming techniques for the optimisation. The implementation falls into four phases: (i) assembly of model parameters; (ii) calculations; (iii) storage of solutions and (iv) projection of solutions. The use of a commercial database and a commercial spreadsheet has proved to be of great assistance in the first and third phases. A metabolic map format, with the optional addition of conversion values, names of enzymes or co-factors has been used to project the results in a form convenient for inspection.

Algorithms↗

PubMed1992

Using fragment lengths from incomplete digestion by multiply cleaving enzymes to map antibody binding sites on a protein.

The problem of mapping the positions of the unique binding sites of several monoclonal antibodies on a linear protein structure is considered. Data giving the incidence of binding of individual antibodies to fragments of the protein obtained from it by the incomplete chemical or enzymatic digestion are used to formulate a series of linear programming problems. The solution to these problems shows which orderings of binding sites are possible, and gives upper and lower bounds for the relative positions of the sites.

Algorithms↗

PubMed2026

Detecting and reconstructing breakage-fusion-bridge cycles from long-read sequencing using BFBArchitect.

MOTIVATION: Focal oncogene amplification is a key driver of tumor progression. Remarkably, the increased pathology depends on the context-whether the amplification is extrachromosomal (ecDNA) or intrachromosomal. EcDNA amplifications promote heterogeneity, therapy resistance, and poor prognosis. Focal intrachromosomal amplifications often arise through breakage-fusion-bridge (BFB) cycles, which produce highly rearranged but stable chromosomes. Distinguishing BFB from ecDNA remains challenging due to overlapping genomic signatures. To address this, we present BFBArchitect, a computational method leveraging long-read Oxford Nanopore data to identify BFB sequences consistent with both copy number and structural variations. RESULTS: We provide a novel combinatorial characterization of BFB, which naturally leads to an integer linear programming (ILP) optimization. The ILP optimization generates a BFB sequence that best explains experimentally observed copy numbers and foldback structural variants. We implement this idea in a tool called BFBArchitect, which achieves near-perfect accuracy in distinguishing BFB from non-BFB structures in extensive simulations as well as on 18 validated tumor samples. Moreover, it generates sequence-level BFB reconstructions that provide mechanistic insights into BFB formation, including repair mechanisms with template switching and other structural variants, and recapture of telomere for stabilization. AVAILABILITY AND IMPLEMENTATION: BFBArchitect is available at https://github.com/AmpliconSuite/BFBArchitect.

Sequence Analysis, DNA↗

PubMed2004

A model-based optimization framework for the inference on gene regulatory networks from DNA array data.

MOTIVATION: Identification of the regulatory structures in genetic networks and the formulation of mechanistic models in the form of wiring diagrams is one of the significant objectives of expression profiling using DNA microarray technologies and it requires the development and application of identification frameworks. RESULTS: We have developed a novel optimization framework for identifying regulation in a genetic network using the S-system modeling formalism. We show that balance equations on both mRNA and protein species led to a formulation suitable for analyzing DNA-microarray data whereby protein concentrations have been eliminated and only mRNA relative concentrations are retained. Using this formulation, we examined if it is possible to infer a set of possible genetic regulatory networks consistent with observed mRNA expression patterns. Two origins of changes in mRNA expression patterns were considered. One derives from changes in the biophysical properties of the system that alter the molecular-interaction kinetics and/or message stability. The second is due to gene knock-outs. We reduced the identification problem to an optimization problem (of the so-called mixed-integer non-linear programming class) and we developed an algorithmic procedure for solving this optimization problem. Using simulated data generated by our mathematical model, we show that our method can actually find the regulatory network from which the data were generated. We also show that the number of possible alternate genetic regulatory networks depends on the size of the dataset (i.e. number of experiments), but this dependence is different for each of the two types of problems considered, and that a unique solution requires fewer datasets than previously estimated in the literature. This is the first method that also allows the identification of every possible regulatory network that could explain the data, when the number of experiments does not allow identification of unique regulatory structure.

Algorithms↗

PubMed2004

Extracting multiple structural alignments from pairwise alignments: a comparison of a rigorous and a heuristic approach.

MOTIVATION: Multiple structural alignments (MSTAs) provide position-specific information on the sequence variability allowed by protein folds. This information can be exploited to better understand the evolution of proteins and the physical chemistry of polypeptide folding. Most MSTA methods rely on a pre-computed library of pairwise alignments. This library will in general contain conflicting residue equivalences not all of which can be realized in the final MSTA. Hence to build a consistent MSTA, these methods have to select a conflict-free subset of equivalences. RESULTS: Using a dataset with 327 families from SCOP 1.63 we compare the ability of two different methods to select an optimal conflict-free subset of equivalences. One is an implementation of Reinert et al.'s integer linear programming formulation (ILP) of the maximum weight trace problem (Reinert et al., 1997, Proc. 1st Ann. Int. Conf. Comput. Mol. Biol. (RECOMB-97), ACM Press, New York). This ILP formulation is a rigorous approach but its complexity is difficult to predict. The other method is T-Coffee (Notredame et al., 2000) which uses a heuristic enhancement of the equivalence weights which allow it to use the speed and simplicity of the progressive alignment approach while still incorporating information of all alignments in each step of building the MSTA. We find that although the ILP formulation consistently selects a more optimal set of conflict-free equivalences, the differences are small and the quality of the resulting MSTAs are essentially the same for both methods. Given its speed and predictable complexity, our results show that T-Coffee is an attractive alternative for producing high-quality MSTAs.

Algorithms↗

PubMed2005

Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data.

MOTIVATION: Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algorithms have been proposed, more robust techniques need to be developed so that further analysis of biological data can be accurately undertaken. In this paper, an innovative missing value imputation algorithm called collateral missing value estimation (CMVE) is presented which uses multiple covariance-based imputation matrices for the final prediction of missing values. The matrices are computed and optimized using least square regression and linear programming methods. RESULTS: The new CMVE algorithm has been compared with existing estimation techniques including Bayesian principal component analysis imputation (BPCA), least square impute (LSImpute) and K-nearest neighbour (KNN). All these methods were rigorously tested to estimate missing values in three separate non-time series (ovarian cancer based) and one time series (yeast sporulation) dataset. Each method was quantitatively analyzed using the normalized root mean square (NRMS) error measure, covering a wide range of randomly introduced missing value probabilities from 0.01 to 0.2. Experiments were also undertaken on the yeast dataset, which comprised 1.7% actual missing values, to test the hypothesis that CMVE performed better not only for randomly occurring but also for a real distribution of missing values. The results confirmed that CMVE consistently demonstrated superior and robust estimation capability of missing values compared with other methods for both series types of data, for the same order of computational complexity. A concise theoretical framework has also been formulated to validate the improved performance of the CMVE algorithm. AVAILABILITY: The CMVE software is available upon request from the authors.

Algorithms↗

PubMed1986

Limits to the relationship among recombination, disequilibrium and epistasis in two-locus models.

I determine limits to the equilibrium relationship among epistasis, recombination and disequilibrium in two-locus, two-allele models using linear programming techniques. I show that when allele frequencies are one-half at each locus, the symmetric model is the fitness pattern that generates the most disequilibrium for the smallest level of epistasis. When allele frequencies deviate from one-half much larger levels of epistasis are required to generate similar levels of disequilibrium. I determine the level of epistasis required to generate observed significant levels of disequilibrium in natural populations. The overall implication is that disequilibrium will be large at equilibrium only between strongly interacting, closely linked loci.

Alleles↗

PubMed1999

Improving the efficiency of artificial selection: more selection pressure with less inbreeding.

The use of population genetic variability in present-day selection schemes can be improved to reduce inbreeding rate and inbreeding depression without impairing genetic progress. We performed an experiment with Drosophila melanogaster to test mate selection, an optimizing method that uses linear programming to maximize the selection differential applied while at the same time respecting a restriction on the increase in inbreeding expected in the next generation. Previous studies about mate selection used computer simulation on simple additive genetic models, and no experiment with a real character in a real population had been carried out. After six selection generations, the optimized lines showed an increase in cumulated phenotypic selection differential of 10.76%, and at the same time, a reduction of 19.91 and 60.47% in inbreeding coefficient mean and variance, respectively. The increased selection pressure would bring greater selection response, and in fact, the observed change in the selected trait was on average 31.03% greater in the optimized lines. These improvements in the selection scheme were not made at the expense of the long-term expectations of genetic variability in the population, as these expectations were very similar for both mate selection and conventionally selected lines in our experiment.

Animals↗

PubMed1981

Disequilibrium, selection, and recombination: limits in two-locus, two-allele models.

All possible combinations of equilibria and fitnesses in two-locus, two-allele, deterministic, discrete-generation selection models are enumerated. This knowledge is used to obtain limits (which can be calculated to arbitrary precision) to the relationships among disequilibrium, selection and recombination for fixed values of allele frequencies. In all cases, the inequality magnitude of rD less than s/10 holds, where r is recombination and D is disequilibrium, and all selection coefficients lie between 1 - s and 1 + s times that of the double heterozygote. Linear programming techniques are used to observed nonzero values of D reported in the literature. One conclusion is that the failure to observe nonzero values of D is not surprising.

Alleles↗

PubMedDate not supplied

The efficiency of Scottish acute hospitals: an application of data envelopment analysis.

Measurement of the efficiency of health services would aid the promotion of a better allocation of health care resources. Economic analysis suggests a number of ways of defining and measuring efficiency. However, this rarely informs measures used in health service management. This paper looks at the potential for the use in the United Kingdom's National Health Service of the linear programming based method of data envelopment analysis (DEA). DEA is applied to data from 75 UK acute hospitals. The results demonstrate the capacity of DEA to produce a user-friendly array of results, based on sound theoretical underpinnings. These range from the measurement of relative efficiencies to quantified suggestions as to how hospitals may improve efficiency, by examining both their own efficiency and that of comparable units. Information is provided both about individual hospitals and the sample as a whole. DEA is also able to distinguish between hospitals demonstrating differing returns to scale. Our findings suggest that, although still very much under development, DEA is usable and, given the weakness of current means of measuring efficiency in the National Health Service, that DEA has a strong claim for further consideration.

Data Interpretation, Statistical↗

PubMed1981

Amino acid requirements of growing mice: arginine, lysine, tryptophan and phenylalanine.

Linear programmed diets designed to maximize the use of proteins and to minimize the use of free (1-) amino acids, and containing five dietary levels of each amino acid under test, were fed to weanling crossbred Carworth Farms No. 1 x Swiss mice in 14-day growth trials. Arginine dietary levels were 0.1, 0.2, 0.3, 0.4 and 0.7%; lysine: 0.2, 0.3, 0.4, 0.5 and 1.0%; tryptophan: 0.03, 0.07, 0.10, 0.13 and 0.17%; and phenylalanine: 0.10, 0.25, 0.40, 0.55 and 0.89%. Growth, feed consumption and regression-adjusted growth rates indicated the following minimum requirements: arginine less than 0.1% and probably zero, lysine 0.4%, tryptophan 0.1% and phenylalanine 0.4%. The AIN '76 reference diet was included in each amino acid test and resulted in superior growth and feed utilization. It was postulated that the greater content of free amino acids in our diets may have affected the efficiency of feed utilization adversely.

Amino Acids, Essential↗

PubMed1982

Nutritional value of feather-meal protein for chicks.

Ileal absorption of nitrogen was determined for feather meal (FM) samples, using magnesium ferrite as a marker. Diets containing 15% FM were balanced by linear programming, using two nitrogen absorption values for FM: 55%, as found, or 85%, an average value for standard feeds. When nitrogen absorption of FM was calculated as 55%, the growth of chicks from one to three weeks of age was similar to that of the control chicks. Depression of growth occurred when the diet composition was calculated using 85% nitrogen absorption for FM. The official method of pepsin digestibility in vitro, using 0.2% pepsin, did not reflect the nutritive value of FM protein. Results similar to those of nitrogen absorption in vivo were obtained with 0.002% pepsin. The total cystine content of FM and the rate of its liberation by pancreatin may also seve as an indication of the nutritive value of FM protein.

Amino Acids↗

PubMed1978

A simple method for the computation of first neighbour frequencies of DNAs from CD spectra.

A procedure for the computation of the first neighbour frequencies of DNA's is presented. This procedure is based on the first neighbour approximation of Gray and Tinoco. We show that the knowledge of all the ten elementary CD signals attached to the ten double stranded first neighbour configurations is not necessary. One can obtain the ten frequencies of an unknown DNA with the use of eight elementary CD signals corresponding to eight linearly independent polymer sequences. These signals can be extracted very simply from any eight or more CD spectra of double stranded DNA's of known frequencies. The ten frequencies of a DNA are obtained by least square fit of its CD spectrum with these elementary signals. One advantage of this procedure is that it does not necessitate linear programming, it can be used with CD data digitalized using a large number of wavelengths, thus permitting an accurate resolution of the CD spectra. Under favorable case, the ten frequencies of a DNA (not used as input data) can be determined with an average absolute error < 2%. We have also observed that certain satellite DNA's, those of Drosophila virilis and Callinectes sapidus have CD spectra compatible with those of DNA's of quasi random sequence; these satellite DNA's should adopt also the B-form in solution.

Animals↗

PubMed2002

Sampling error can significantly affect measured hospital financial performance of surgeons and resulting operating room time allocations.

UNLABELLED: Hospitals with limited operating room (OR) hours, those with intensive care unit or ward beds that are always full, or those that have no incremental revenue for many patients need to choose which surgeons get the resources. Although such decisions are based on internal financial reports, whether the reports are statistically valid is not known. Random error may affect surgeons' measured financial performance and, thus, what cases the anesthesiologists get to do and which patients get to receive care. We tested whether one fiscal year of surgeon-specific financial data is sufficient for accurate financial accounting. We obtained accounting data for all outpatient or same-day-admit surgery cases during one fiscal year at an academic medical center. Linear programming was used to find the mix of surgeons' OR time allocations that would maximize the contribution margin or minimize variable costs. Confidence intervals were calculated on these end points by using Fieller's theorem and Monte-Carlo simulation. The 95% confidence intervals for increases in contribution margins or reductions in variable costs were 4.3% to 10.8% and 6.0% to 8.9%, respectively. As many as 22% of surgeons would have had OR time reduced because of sampling error. We recommend that physicians ask for and OR managers get confidence intervals of end points of financial analyses when making decisions based on them. IMPLICATIONS: The common approach of using one fiscal year of perioperative accounting data can be insufficient to prevent random error from influencing important management decisions. When accounting data are used for hospital and operating room management decision making, confidence intervals should be calculated for the key financial variables (e.g., variable cost per hour of operating room time).

Costs and Cost Analysis↗

PubMed1989

Evaluating managerial efficiency of Veterans Administration medical centers using Data Envelopment Analysis.

This study applied the methodology of Data Envelopment Analysis (DEA) to the set of VA medical centers to evaluate their relative managerial efficiencies. Each VAMC was viewed as a producer of multiple outputs and a consumer of multiple inputs. DEA uses linear programming to identify resources that were underutilized and services that were inefficiently produced. Managerial strategies based on the dual variables were constructed to indicate the manner in which inefficient VAMCs may be made efficient. The analysis showed that relative inefficiency existed in about one third of the VAMCs nationwide. Elimination of this inefficiency would save the VA over $300 million annually on personnel, equipment, drugs, and supplies, without reducing the level of services provided. A subsequent analysis of co-variance revealed that VAMCs affiliated with a university were generally less efficient than those without such an affiliation. A similar finding was obtained for larger VAMCs relative to smaller medical centers. In neither case, however, should these results be construed to imply that VAMCs should terminate their university affiliations or that VAMCs should be made smaller since factors other than relative efficiency are clearly as or more important in such decisions.

Cost Control↗

PubMedDate not supplied

Equilibrium analysis for the forces in the human spinal column and its musculature.

The equations of equilibrium are set up for the thoracic and lumbar spine and involve body weight, external load, muscle forces, and intervertebral reactions. These equations are solved using a linear programming technique that minimizes the total force in the system. The solution gives numeric values for the muscle forces and intervertebral reactions. The results for a subject in progressive forward flexion and in lateral bend are presented. Also examined are the effects of three different orthotic devices on the muscle forces of a patient with a scoliotic spine.

Biomechanical Phenomena↗

PubMed2003

From individual control to majority rule: extending transactional models of reproductive skew in animal societies.

Transactional concession models of social evolution explain the reproductive skew within groups by assuming that a dominant individual completely controls the allocation of reproduction to other group members. The models predict when the dominant will benefit from donating parcels of reproduction to other members in return for peaceful cooperation. Using linear programming methods, we present a 'majority-rules' model in which the summed actions of all society members, each with equal power, completely determine the reproductive share of any single member. The majority-rules model predicts that, despite the diffusion of power, a 'virtual dominant' (a dominant lacking special behavioural power) will emerge and that the reproductive skew will be exactly that predicted if the virtual dominant were to control completely the group's reproductive partitioning. The virtual dominant is the individual to which group members have the maximum average genetic relatedness. This result greatly broadens the applicability of transactional models of reproductive skew to social groups of any size, such as large-colony eusocial insects, and explains why queens in such colonies can achieve reproductive domination without any behavioural enforcement. Moreover, the majority-rules model unifies transactional-skew theory with models of worker policing and even generates a new theory for the cooperation among somatic cells in a multicellular organism.

Animals↗

PubMed2004

Genome-scale in silico models of E. coli have multiple equivalent phenotypic states: assessment of correlated reaction subsets that comprise network states.

The constraint-based analysis of genome-scale metabolic and regulatory networks has been successful in predicting phenotypes and useful for analyzing high-throughput data sets. Within this modeling framework, linear optimization has been used to study genome-scale metabolic models, resulting in the enumeration of single optimal solutions describing the best use of the network to support growth. Here mixed-integer linear programming was used to calculate and study a subset of the alternate optimal solutions for a genome-scale metabolic model of Escherichia coli (iJR904) under a wide variety of environmental conditions. Analysis of the calculated sets of optimal solutions found that: (1) only a small subset of reactions in the network have variable fluxes across optima; (2) sets of reactions that are always used together in optimal solutions, correlated reaction sets, showed moderate agreement with the currently known transcriptional regulatory structure in E. coli and available expression data, and (3) reactions that are used under certain environmental conditions can provide clues about network regulatory needs. In addition, calculation of suboptimal flux distributions, using flux variability analysis, identified reactions which are used under significantly more environmental conditions suboptimally than optimally. Together these results demonstrate the utilization of reactions in genome-scale models under a variety of different growth conditions.

Aerobiosis↗