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PubMed2004

An efficient algorithm for detecting frequent subgraphs in biological networks.

MOTIVATION: With rapidly increasing amount of network and interaction data in molecular biology, the problem of effectively analyzing this data is an important one. Graph theoretic formalisms, commonly used for these analysis tasks, often lead to computationally hard problems due to their relation with subgraph isomorphism. RESULTS: This paper presents an innovative new algorithm for detecting frequently occurring patterns and modules in biological networks. Using an innovative graph simplification technique, which is ideally suited to biological networks, our algorithm renders these problems computationally tractable. Indeed, we show experimentally that our algorithm can extract frequently occurring patterns in metabolic pathways extracted from the KEGG database within seconds. The proposed model and algorithm are applicable to a variety of biological networks either directly or with minor modifications. AVAILABILITY: Implementation of the proposed algorithms in the C programming language is available as open source at http://www.cs.purdue.edu/homes/koyuturk/pathway/

Algorithms↗

PubMed2005

A grid layout algorithm for automatic drawing of biochemical networks.

MOTIVATION: Visualization is indispensable in the research of complex biochemical networks. Available graph layout algorithms are not adequate for satisfactorily drawing such networks. New methods are required to visualize automatically the topological architectures and facilitate the understanding of the functions of the networks. RESULTS: We propose a novel layout algorithm to draw complex biochemical networks. A network is modeled as a system of interacting nodes on squared grids. A discrete cost function between each node pair is designed based on the topological relation and the geometric positions of the two nodes. The layouts are produced by minimizing the total cost. We design a fast algorithm to minimize the discrete cost function, by which candidate layouts can be produced efficiently. A simulated annealing procedure is used to choose better candidates. Our algorithm demonstrates its ability to exhibit cluster structures clearly in relatively compact layout areas without any prior knowledge. We developed Windows software to implement the algorithm for CADLIVE. AVAILABILITY: All materials can be freely downloaded from http://kurata21.bio.kyutech.ac.jp/grid/grid_layout.htm; http://www.cadlive.jp/ SUPPLEMENTARY INFORMATION: http://kurata21.bio.kyutech.ac.jp/grid/grid_layout.htm; http://www.cadlive.jp/

Algorithms↗

PubMed2006

GEL: a novel genotype calling algorithm using empirical likelihood.

MOTIVATION: Preliminary results on the data produced using the Affymetrix large-scale genotyping platforms show that it is necessary to construct improved genotype calling algorithms. There is evidence that some of the existing algorithms lead to an increased error rate in heterozygous genotypes, and a disproportionately large rate of heterozygotes with missing genotypes. Non-random errors and missing data can lead to an increase in the number of false discoveries in genetic association studies. Therefore, the factors that need to be evaluated in assessing the performance of an algorithm are the missing data (call) and error rates, but also the heterozygous proportions in missing data and errors. RESULTS: We introduce a novel genotype calling algorithm (GEL) for the Affymetrix GeneChip arrays. The algorithm uses likelihood calculations that are based on distributions inferred from the observed data. A key ingredient in accurate genotype calling is weighting the information that comes from each probe quartet according to the quality/reliability of the data in the quartet, and prior information on the performance of the quartet. AVAILABILITY: The GEL software is implemented in R and is available by request from the corresponding author at nicolae@galton.uchicago.edu.

Algorithms↗

PubMed2006

An iterative refinement algorithm for consistency based multiple structural alignment methods.

MOTIVATION: Multiple STructural Alignment (MSTA) provides valuable information for solving problems such as fold recognition. The consistency-based approach tries to find conflict-free subsets of alignments from a pre-computed all-to-all Pairwise Alignment Library (PAL). If large proportions of conflicts exist in the library, consistency can be hard to get. On the other hand, multiple structural superposition has been used in many MSTA methods to refine alignments. However, multiple structural superposition is dependent on alignments, and a superposition generated based on erroneous alignments is not guaranteed to be the optimal superposition. Correcting errors after making errors is not as good as avoiding errors from the beginning. Hence it is important to refine the pairwise library to reduce the number of conflicts before any consistency-based assembly. RESULTS: We present an algorithm, Iterative Refinement of Induced Structural alignment (IRIS), to refine the PAL. A new measurement for the consistency of a library is also proposed. Experiments show that our algorithm can greatly improve T-COFFEE performance for less consistent pairwise alignment libraries. The final multiple alignment outperforms most state-of-the-art MSTA algorithms at assembling 15 transglycosidases. Results on three other benchmarks showed that the algorithm consistently improves multiple alignment performance. AVAILABILITY: The C++ code of the algorithm is available upon request.

Algorithms↗

PubMed2006

MUSA: a parameter free algorithm for the identification of biologically significant motifs.

MOTIVATION: The ability to identify complex motifs, i.e. non-contiguous nucleotide sequences, is a key feature of modern motif finders. Addressing this problem is extremely important, not only because these motifs can accurately model biological phenomena but because its extraction is highly dependent upon the appropriate selection of numerous search parameters. Currently available combinatorial algorithms have proved to be highly efficient in exhaustively enumerating motifs (including complex motifs), which fulfill certain extraction criteria. However, one major problem with these methods is the large number of parameters that need to be specified. RESULTS: We propose a new algorithm, MUSA (Motif finding using an UnSupervised Approach), that can be used either to autonomously find over-represented complex motifs or to estimate search parameters for modern motif finders. This method relies on a biclustering algorithm that operates on a matrix of co-occurrences of small motifs. The performance of this method is independent of the composite structure of the motifs being sought, making few assumptions about their characteristics. The MUSA algorithm was applied to two datasets involving the bacterium Pseudomonas putida KT2440. The first one was composed of 70 sigma(54)-dependent promoter sequences and the second dataset included 54 promoter sequences of up-regulated genes in response to phenol, as suggested by quantitative proteomics. The results obtained indicate that this approach is very effective at identifying complex motifs of biological significance. AVAILABILITY: The MUSA algorithm is available upon request from the authors, and will be made available via a Web based interface.

Algorithms↗

PubMed1995

Management of vaginal discharge in women treated at a Jamaican sexually transmitted disease clinic: use of diagnostic algorithms versus laboratory testing.

The management of cervical infections is difficult in developing countries because laboratory facilities for diagnosing these infections are seldom available; therefore, syndrome-based management has been recommended by the World Health Organization (WHO). However, such alternative approaches need to be evaluated in real field settings. We used algorithms (flowcharts) for syndromic management of abnormal vaginal discharge to treat 752 women who presented at a Jamaican sexually transmitted disease (STD) clinic. Laboratory testing revealed cervical infection (gonococcal and/or chlamydial) in 34% of these women; trichomoniasis was documented for 25%; and at least one STD was documented for 54% of the women. Use of a clinical algorithm for diagnosing cervical infection was 73% sensitive (95% CI, 67-78) and 55% specific (95% CI, 49-62) when compared with laboratory testing. The risk-assessment-inclusive flowchart developed by WHO was 84% sensitive (95% CI, 80-89) and 40% specific (95% CI, 34-46) for diagnosing cervical infection. Positive predictive values for diagnosing cervical infection with use of the algorithms ranged from 42% to 43%, and negative predictive values ranged from 78% to 81%. The sensitivity of the algorithms for diagnosing trichomoniasis ranged from 85% to 88%. To treat as many infected women as possible, the most sensitive algorithm was selected for routine use in Jamaican STD clinics.

Adult↗

PubMed2003

Comparative evaluation of three computerized algorithms for prediction of antiretroviral susceptibility from HIV type 1 genotype.

OBJECTIVES: To compare three methods for using HIV-1 genotype to predict antiretroviral drug susceptibility. METHODS: We applied three genotypic interpretation algorithms to 478 reverse transcriptase (RT) and 410 protease sequences for which phenotypic data were available. Sequences were obtained from clinical practice and from published sequences in the Stanford HIV-1 RT and Protease Sequence Database. The genotypic interpretation algorithms included: Stanford HIVdb program (HIVdb), the Visible Genetics/Bayer Diagnostics Guidelines 6.0 (VGI) and a genotypic interpretation program (AntiRetroScan, ARS) developed at the University of Siena, Italy. Genotypic interpretations were normalized to a three-level output: susceptible, intermediate and resistant. Discordances were defined as differences between genotype and phenotype for the same virus isolate. Discordances for which an isolate was considered susceptible by one test but resistant by another test were considered major discordances. RESULTS: The frequency of major discordances between genotype and phenotype was 10.6, 13.7 and 15.7% for ARS, VGI and HIVdb, respectively (P < 0.0001 for ARS versus HIVdb and for ARS versus VGI; P = 0.002 for VGI versus HIVdb). The correlation between genotype and phenotype was highest for non-nucleoside RT inhibitors and lowest for nucleoside RT inhibitors. Half of the major discordances involved stavudine, didanosine and zalcitabine. The concordance among the three genotypic algorithms was high, with weighted Kappa values ranging between 0.76 and 0.84 for the pairwise comparisons between each of the algorithms. CONCLUSIONS: Genotype interpretation algorithms correctly predict phenotype in 85-90% of cases, but the rate of concordance is not uniformly distributed among different drugs. These data provide insight into the potential additional benefit derived from phenotyping.

Algorithms↗

PubMed2003

Prediction of acute renal failure after cardiac surgery: retrospective cross-validation of a clinical algorithm.

BACKGROUND: Acute renal failure (ARF) after cardiac surgery is associated with high costs and a poor prognosis. Based on the results of a large US study, an algorithm has been developed for predicting ARF from pre-operative risk factors. The aim of this study was to cross-validate this algorithm in a patient population from Europe, and to assess its usefulness as a clinical tool. METHODS: All coronary bypass and valvular surgery patients from a 5-year period were included. Data on pre-operative risk factors for all patients who developed dialysis-dependent ARF and for a random sample of patients without ARF were retrospectively obtained from hospital databases and medical records. For each patient, a risk score for ARF was calculated on the basis of the algorithm. The sensitivity, specificity, positive and negative predictive values and area under receiver operating characteristic (ROC) curve of the score's ability to predict ARF were estimated. RESULTS: 2037 patients were included. The risk of ARF was 1.9%, and the area under the ROC curve 0.71. For a risk score of 6 or higher, the sensitivity was 0.53, the specificity 0.71, the positive predictive value 0.03 and the negative predictive value 0.99. CONCLUSIONS: The validity of the algorithm was confirmed in a population differing in several aspects from the US populations where it was developed. Although it is useful for estimating the risk of ARF in groups of patients, the low risk of ARF limits the algorithm's ability to predict the outcome for individual patients.

Acute Kidney Injury↗

PubMed1996

A stepwise algorithm for finding minimum evolution trees.

A stepwise algorithm for reconstructing minimum evolution (ME) trees from evolutionary distance data is proposed. In each step, a taxon that potentially has a neighbor (another taxon connected to it with a single interior node) is first chosen and then its true neighbor searched iteratively. For m taxa, at most (m-1)!/2 trees are examined and the tree with the minimum sum of branch lengths (S) is chosen as the final tree. This algorithm provides simple strategies for restricting the tree space searched and allows us to implement efficient ways of dynamically computing the ordinary least squares estimates of S for the topologies examined. Using computer simulation, we found that the efficiency of the ME method in recovering the correct tree is similar to that of the neighbor-joining method (Saitou and Nei 1987). A more exhaustive search is unlikely to improve the efficiency of the ME method in finding the correct tree because the correct tree is almost always included in the tree space searched with this stepwise algorithm. The new algorithm finds trees for which S values may not be significantly different from that of the ME tree if the correct tree contains very small interior branches or if the pairwise distance estimates have large sampling errors. These topologies form a set of plausible alternatives to the ME tree and can be compared with each other using statistical tests based on the minimum evolution principle. The new algorithm makes it possible to use the ME method for large data sets.

Algorithms↗

PubMed1998

A genetic algorithm for maximum-likelihood phylogeny inference using nucleotide sequence data.

Phylogeny reconstruction is a difficult computational problem, because the number of possible solutions increases with the number of included taxa. For example, for only 14 taxa, there are more than seven trillion possible unrooted phylogenetic trees. For this reason, phylogenetic inference methods commonly use clustering algorithms (e.g., the neighbor-joining method) or heuristic search strategies to minimize the amount of time spent evaluating nonoptimal trees. Even heuristic searches can be painfully slow, especially when computationally intensive optimality criteria such as maximum likelihood are used. I describe here a different approach to heuristic searching (using a genetic algorithm) that can tremendously reduce the time required for maximum-likelihood phylogenetic inference, especially for data sets involving large numbers of taxa. Genetic algorithms are simulations of natural selection in which individuals are encoded solutions to the problem of interest. Here, labeled phylogenetic trees are the individuals, and differential reproduction is effected by allowing the number of offspring produced by each individual to be proportional to that individual's rank likelihood score. Natural selection increases the average likelihood in the evolving population of phylogenetic trees, and the genetic algorithm is allowed to proceed until the likelihood of the best individual ceases to improve over time. An example is presented involving rbcL sequence data for 55 taxa of green plants. The genetic algorithm described here required only 6% of the computational effort required by a conventional heuristic search using tree bisection/reconnection (TBR) branch swapping to obtain the same maximum-likelihood topology.

Algorithms↗

PubMed1995

A simple protein folding algorithm using a binary code and secondary structure constraints.

We describe an algorithm to predict tertiary structures of small proteins. In contrast to most current folding algorithms, it uses very few energy parameters. Given the secondary structural elements in the sequence--alpha-helices and beta-strands--the algorithm searches the remaining conformational space of a simplified real-space representation of chains to find a minimum energy of an exceedingly simple potential function. The potential is based only on a single type of favorable interaction between hydrophobic residues, an unfavorable excluded volume term of spatial overlaps and, for sheet proteins, an interstrand hydrogen bond interaction. Where appropriate, the known disulfide bonds are constrained by a square-law potential. Conformations are searched by a genetic algorithm. The model predicts reasonably well the known tertiary folds of seven out of the 10 small proteins we consider. We draw two conclusions. First, for the proteins we tested, this exceedingly simple potential function is no worse than others having hundreds of energy parameters in finding the right general tertiary structures. Second, despite its simplicity, the potential function is not the weak link in this algorithm. Differences between our predicted structures and the correct targets can be ascribed to shortcomings in our search strategy. This potential function may be useful for testing other conformational search strategies.

Algorithms↗

PubMed2004

Unanticipated difficult airway in anesthetized patients: prospective validation of a management algorithm.

BACKGROUND: Management strategies conceived to improve patient safety in anesthesia have rarely been assessed prospectively. The authors undertook a prospective evaluation of a predefined algorithm for unanticipated difficult airway management. METHODS: After a 2-month period of training in airway management, 41 anesthesiologists were asked to follow a predefined algorithm for management in the case of an unanticipated difficult airway. Two different scenarios were distinguished: "cannot intubate" and "cannot ventilate." The gum elastic bougie and the Intubating Laryngeal Mask Airway (ILMA) were proposed as the first and second steps in the case of impossible laryngoscope-assisted tracheal intubation, respectively. In the case of impossible ventilation or difficult ventilation, the IMLA was recommended, followed by percutaneous transtracheal jet ventilation. The patient's details, adherence rate to the algorithm, efficacy, and complications of airway management processes were recorded. RESULTS: Impossible ventilation never occurred during the 18-month study. One hundred cases of unexpected difficult airway were recorded (0.9%) among 11,257 intubations. Deviation from the algorithm was recorded in three cases, and two patients were wakened before any alternative intubation technique attempt. All remaining patients were successfully ventilated with either the facemask (89 of 95) or the ILMA (6 of 95). Six difficult-ventilation patients required the ILMA before completion of the first intubation step. Eighty patients were intubated with the gum elastic bougie, and 13 required a blind intubation through the ILMA. Two patients ventilated with the ILMA were never intubated. CONCLUSION: When applied in accordance with a predefined algorithm, the gum elastic bougie and the ILMA are effective to solve most problems occurring during unexpected difficult airway management.

Adult↗

PubMed2000

Simple algorithm derived from a geno-/phenotypic database to predict HIV-1 protease inhibitor resistance.

BACKGROUND: Resistance against protease inhibitors (PI) can either be analysed genotypically or phenotypically. However, the interpretation of genotypic data is difficult, particularly for PI, because of the unknown contributions of several mutations to resistance and cross-resistance. OBJECTIVE: Development of an algorithm to predict PI phenotype from genotypic data. METHODS: Recombinant viruses containing patient-derived protease genes were analysed for sensitivity to indinavir, saquinavir, ritonavir and nelfinavir. Drug resistance-associated mutations were determined by direct sequencing. geno- and phenotypic data were compared for 119 samples from 97 HIV-1 infected patients. RESULTS: Samples with one or two mutations in the gene for the protease were phenotypically sensitive in 74.3%, whereas 83.6% of samples with five or more mutations were resistant against all PI tested. Some mutations (361, 63P, 71V/T, 771) were frequent both in sensitive and resistant samples, whereas others (241, 30N, 461/L, 48V, 54V, 82A/F/T/S, 84V, 90M) were predominantly present in resistant samples. Therefore, the presence or absence of a single drug resistance-associated mutation predicted phenotypic PI resistance with high sensitivity (96.5-100%) but low specificity (13.3-57.4%). A more specific algorithm was obtained by taking into account the total number of drug resistance-associated mutations in the gene for the protease and restricting these to certain key positions for the PI. The algorithm was subsequently validated by analysis of 72 independent samples. CONCLUSION: With an optimized algorithm, phenotypic PI resistance can be predicted by viral genotype with good sensitivity (89.1-93.0%) and specificity (82.6-93.3%). The reliability and relevance of this algorithm should be further evaluated in clinical practice.

Acquired Immunodeficiency Syndrome↗

PubMed1997

A digital filterbank hearing aid: predicting user preference and performance for two signal processing algorithms.

OBJECTIVE: In a series of experiments with a wearable binaural digital hearing aid, two hearing aid processing algorithms were compared. Both algorithms provided individual frequency shaping via a seven-band filterbank with compression limiting in the high-frequency channel. They differed in the processing of the low-frequency channel, using dynamic range compression for one (DynEar) and linear processing with compression limiting for the other (LinEar). In a pilot field test we found that LinEar/ DynEar preference based on use time could be predicted from auditory dynamic range data. For the subjects who preferred DynEar, the mean dynamic range was broader for low and mid frequencies and narrower for high frequencies, as compared with the LinEar preference subjects. These groupings were tested as predictors of user preference and performance in a main field test. DESIGN: The main study included 26 hearing aid users with symmetrical sensorineural losses. The algorithms were compared in a one-mo-long blind field test. A data logger function was included for objective recording of the total time each algorithm was used and how the volume controls were used. The preference was based on the time used for each algorithm and on subjective statements. Threshold signal-to-noise ratio (S/N-threshold) for speech was tested, and sound quality ratings were obtained through a questionnaire. We also tested the S/N-thresholds for the subjects' conventional (own) aids. RESULTS: The preference was correctly predicted by the dynamic range data on 12 out of 15 new cases. S/N-thresholds were lower for the preferred fittings compared with the nonpreferred fittings and with the subjects' own aids. In the questionnaire the preferred fittings were rated significantly higher in terms of overall impression and clearness. Because of the systematic way the DynEar-preference subjects adjusted the high-frequency DynEar gain, we speculate that upward spread of masking may have been a factor in preference and performance. Additionally, LinEar-preference subjects' preference and performance might have been influenced by excessive compression ratios with the DynEar processing in these cases. CONCLUSIONS: 1. Preference for DynEar versus LinEar depends on the auditory dynamic range. 2. S/N-thresholds for speech were better for the preferred fittings, which also were rated higher in terms of overall impression of sound quality and clearness.

Adult↗

PubMed2002

Positron emission tomography partial volume correction: estimation and algorithms.

Partial volume effects in positron emission tomography (PET) lead to quantitative under- and over-estimations of the regional concentrations of radioactivity in reconstructed images and corresponding errors in derived functional or parametric images. The limited resolution of PET leads to "tissue-fraction" effects, reflecting underlying tissue heterogeneity, and "spillover" effects between regions. Addressing the former problem in general requires supplementary data, for example, coregistered high-resolution magnetic resonance images, whereas the latter effect can be corrected for with PET data alone if the point-spread function of the tomograph has been characterized. Analysis of otherwise homogeneous region-of-interest data ideally requires a combination of tissue classification and correction for the point-spread function. The formulation of appropriate algorithms for partial volume correction (PVC) is dependent on both the distribution of the signal and the distribution of the underlying noise. A mathematical framework has therefore been developed to accommodate both of these factors and to facilitate the development of new PVC algorithms based on the description of the problem. Several methodologies and algorithms have been proposed and implemented in the literature in order to address these problems. These methods do not, however, explicitly consider the noise model while differing in their underlying assumptions. The general theory for estimation of regional concentrations, associated error estimation, and inhomogeneity tests are presented in a weighted least squares framework. The analysis has been validated using both simulated and real PET data sets. The relations between the current algorithms and those published previously are formulated and compared. The incorporation of tensors into the formulation of the problem has led to the construction of computationally rapid algorithms taking into account both tissue-fraction and spillover effects. The suitability of their application to dynamic and static images is discussed.

Algorithms↗

PubMedDate not supplied

An algorithm for drug waste reduction using pharmacokinetic principles.

When delivering several intravenous drug doses from a single bag, it is generally necessary to throw away any drug that remains in the bag, if the amount is insufficient to deliver the next dose. An algorithm has been developed to allow all of the drug in a bag to be used. Based on standard pharmacokinetic equations, the algorithm calculates the time when the remainder should be given, so that a desired peak serum drug concentration is achieved on the next dose. The algorithm requires as inputs the time limit on the bag, the dosing interval and the size of the dose. This algorithm applies only to drugs that obey single compartment, first-order linear kinetics (e.g. aminoglycosides), but is easily modified for other situations. In conjunction with computer-assisted infusion, use of the algorithm may potentially reduce the cost of aminoglycoside administration by reducing clinical drug waste.

Algorithms↗

PubMedDate not supplied

Retrospective registration of PET and MR brain images: an algorithm and its stereotactic validation.

OBJECTIVE: We present a validation study of an algorithm for retrospective registration of PET and MR brain images. MATERIALS AND METHODS: This algorithm involves two steps. In the first step, the two volumes are reformatted by aligning their interhemispheric fissure planes (midsagittal plane). In the second step, the corresponding planes parallel to the midsagittal plane are further aligned in the reformatted volumes to produce a 3D rigid body registration of the two original volumes. It is an efficient algorithm because both steps are performed in 2D spaces, and in each step only a small number of landmarks are required. A user-friendly system has been implemented to facilitate easy and fast processing of registration and reformatting of image volumes. The accuracy of this algorithm is validated using clinical scans of neurosurgical patients with a stereotaxic frame attached to their skull. The frame-based stereotaxic system provides an effective method for transforming image coordinates from different image volumes into a common coordinate system. This common coordinate system is used for assessing the spatial correspondence of each pixel in the registered image volumes. Validation using the stereotaxic image volumes enables objective estimation of retrospective registration accuracy. RESULTS: Analysis of 11 MR/PET image pairs indicates that our registration method not only is efficient but also provides adequate accuracy for most clinical evaluation of PET studies. CONCLUSION: We have implemented and validated an efficient algorithm for retrospective registration of PET and MR brain images.

Adult↗

PubMedDate not supplied

A fully automatic multimodality image registration algorithm.

OBJECTIVE: A fully automatic multimodality image registration algorithm is presented. The method is primarily designed for 3D registration of MR and PET images of the brain. However, it has also been successfully applied to CT-PET, MR-CT, and MR-SPECT registrations. MATERIALS AND METHODS: The head contour is detected on the MR image using a gradient threshold method. The head region in the MR image is then segmented into a set of connected components using the K-means clustering algorithm. When the two image sets are registered, the segmentation of the MR image indirectly generates a segmentation of the PET image. The best registration is taken to be the one that optimizes the segmentation induced on the PET image. In this article, the K-means minimum variance criterion is used as a cost function, and the optimization is performed using the method of coordinate descent. RESULTS: The algorithm was tested on 80 H2 15O PET and MR image pairs from 10 subjects. Qualitatively correct results were obtained in all cases. With use of external markers visible in both image modalities, the average registration error was estimated to be < 3 mm. CONCLUSION: The algorithm presented in this article requires no user interaction and can be applied to a wide range of registration problems. Quantitative and qualitative evaluations of the algorithm indicate a high degree of accuracy.

Algorithms↗