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PubMed2004

A new algorithm for detecting low-complexity regions in protein sequences.

MOTIVATION: Pair-wise alignment of protein sequences and local similarity searches produce many false positives because of compositionally biased regions, also called low-complexity regions (LCRs), of amino acid residues. Masking and filtering such regions significantly improves the reliability of homology searches and, consequently, functional predictions. Most of the available algorithms are based on a statistical approach. We wished to investigate the structural properties of LCRs in biological sequences and develop an algorithm for filtering them. RESULTS: We present an algorithm for detecting and masking LCRs in protein sequences to improve the quality of database searches. We developed the algorithm based on the complexity analysis of subsequences delimited by a pair of identical, repeating subsequences. Given a protein sequence, the algorithm first computes the suffix tree of the sequence. It then collects repeating subsequences from the tree. Finally, the algorithm iteratively tests whether each subsequence delimited by a pair of repeating subsequences meets a given criteria. Test results with 1000 proteins from 20 families in Pfam show that the repeating subsequences are a good indicator for the low-complexity regions, and the algorithm based on such structural information strongly compete with others. AVAILABILITY: http://bioinfo.knu.ac.kr/research/CARD/ CONTACT: swshin@bioinfo.knu.ac.kr

Algorithms↗

PubMed2006

Evaluating the performance of microarray segmentation algorithms.

MOTIVATION: Although numerous algorithms have been developed for microarray segmentation, extensive comparisons between the algorithms have acquired far less attention. In this study, we evaluate the performance of nine microarray segmentation algorithms. Using both simulated and real microarray experiments, we overcome the challenges in performance evaluation, arising from the lack of ground-truth information. The usage of simulated experiments allows us to analyze the segmentation accuracy on a single pixel level as is commonly done in traditional image processing studies. With real experiments, we indirectly measure the segmentation performance, identify significant differences between the algorithms, and study the characteristics of the resulting gene expression data. RESULTS: Overall, our results show clear differences between the algorithms. The results demonstrate how the segmentation performance depends on the image quality, which algorithms operate on significantly different performance levels, and how the selection of a segmentation algorithm affects the identification of differentially expressed genes. AVAILABILITY: Supplementary results and the microarray images used in this study are available at the companion web site http://www.cs.tut.fi/sgn/csb/spotseg/

Algorithms↗

PubMed2006

SNiPer-HD: improved genotype calling accuracy by an expectation-maximization algorithm for high-density SNP arrays.

MOTIVATION: The technology to genotype single nucleotide polymorphisms (SNPs) at extremely high densities provides for hypothesis-free genome-wide scans for common polymorphisms associated with complex disease. However, we find that some errors introduced by commonly employed genotyping algorithms may lead to inflation of false associations between markers and phenotype. RESULTS: We have developed a novel SNP genotype calling program, SNiPer-High Density (SNiPer-HD), for highly accurate genotype calling across hundreds of thousands of SNPs. The program employs an expectation-maximization (EM) algorithm with parameters based on a training sample set. The algorithm choice allows for highly accurate genotyping for most SNPs. Also, we introduce a quality control metric for each assayed SNP, such that poor-behaving SNPs can be filtered using a metric correlating to genotype class separation in the calling algorithm. SNiPer-HD is superior to the standard dynamic modeling algorithm and is complementary and non-redundant to other algorithms, such as BRLMM. Implementing multiple algorithms together may provide highly accurate genotyping calls, without inflation of false positives due to systematically miss-called SNPs. A reliable and accurate set of SNP genotypes for increasingly dense panels will eliminate some false association signals and false negative signals, allowing for rapid identification of disease susceptibility loci for complex traits. AVAILABILITY: SNiPer-HD is available at TGen's website: http://www.tgen.org/neurogenomics/data.

Algorithms↗

PubMed2005

A simple prediction algorithm for bacteraemia in patients with acute febrile illness.

BACKGROUND: Existing prediction models for the risk of bacteraemia are complex and difficult to use. Physicians are likely to use a model only if it is simple and sensitive. AIM: To develop a simple classification algorithm predicting the risk of bacteraemia. DESIGN: Hospital-based study. METHODS: We enrolled 526 adult consecutive patients with acute febrile illness (40 with bacteraemia) presenting to the emergency department at a community hospital in Okinawa, Japan. Recursive partitioning analysis was used to build the classification algorithm with V-fold cross-validation. We used two clinical scenarios: in the first, laboratory tests were not available; in the second, they were. RESULTS: The two prediction algorithms generated three different risk groups for bacteraemia. In the first scenario, the important variables were chills, pulse, and physician diagnosis of a low-risk site. The low-risk group from this first algorithm included 68% of the total patients; sensitivity was 87.5% and the misclassification rate was 1.4% (5/358). In the second scenario, the important variables were chills, C-reactive protein, and physician diagnosis of a low-risk site. The low-risk group for the second algorithm included 62% of the total patients; sensitivity was 92.5% and misclassification rate 0.9% (3/328). The algorithms had negative predictive values of 98.6% (first scenario) and 99.1% (second). DISCUSSION: This simple and sensitive prediction algorithm may be useful for identifying patients at low risk of bacteraemia. Prospective validation is needed in other settings.

Acute Disease↗

PubMed2001

Efficacy of a simple intraoperative transfusion algorithm for nonerythrocyte component utilization after cardiopulmonary bypass.

BACKGROUND: Abnormal bleeding after cardiopulmonary bypass (CPB) is a common complication of cardiac surgery, with important health and economic consequences. Coagulation test-based algorithms may reduce transfusion of non-erythrocyte allogeneic blood in patients with abnormal bleeding. METHODS: The authors performed a randomized prospective trial comparing allogeneic transfusion practices in 92 adult patients with abnormal bleeding after CPB. Patients with abnormal bleeding were randomized to one of two groups: a control group following individual anesthesiologist's transfusion practices and a protocol group using a transfusion algorithm guided by coagulation tests. RESULTS: Among 836 eligible patients having all types of elective cardiac surgery requiring CPB, 92 patients developed abnormal bleeding after CPB (incidence, 11%). The transfusion algorithm group received less allogeneic fresh frozen plasma in the operating room after CPB (median, 0 units; range, 0-7 units) than the control group (median, 3 units; range, 0-10 units) (P = 0.0002). The median number of platelet units transfused in the operating room after CPB was 4 (range, 0-12) in the algorithm group compared with 6 (range, 0-18) in the control group (P = 0.0001). Intensive care unit (ICU) mediastinal blood loss was significantly less in the algorithm group. Multivariate analysis demonstrated that transfusion algorithm use resulted in reduced ICU blood loss. The control group also had a significantly greater incidence of surgical reoperation of the mediastinum for bleeding (11.8% vs. 0%; P = 0.032). CONCLUSIONS: Use of a coagulation test-based transfusion algorithm in cardiac surgery patients with abnormal bleeding after CPB reduced non-erythrocyte allogeneic transfusions in the operating room and ICU blood loss.

Adult↗

PubMed1995

A reexamination of the NRMP matching algorithm. National Resident Matching Program.

Most graduating medical students in the United States find their first professional appointments through the National Resident Matching Program (NRMP). This service receives rank-order lists of preferences from students and from hospitals, and then generates final assignments of students to hospitals through the use of a specific computerized matching algorithm. The author uses recent findings from the mathematics and economics literatures to demonstrate three difficulties with the NRMP's matching algorithm and the official descriptions thereof. First, the algorithm favors hospitals over students, a feature known to the NRMP since at least 1976, but, in the author's opinion, not made clear in NRMP literature for students. Second, the author argues that the NRMP's justification that its algorithm mimics orderly, noncentralized admission processes is not correct. Institutions operating under non-centralized procedures must typically make more initial offers than there are positions, in the realization that some fraction of their offers will be declined. This arrangement enlarges the choices available to many applicants, and thereby benefits them, whereas the NRMP's algorithm unrealistically assumes that no institution would ever send out any extra offers. Third, the NRMP's algorithm contains incentives for students to misrepresent their true preferences when constructing their rank-order lists. This feature is a substantial disadvantage of the current algorithm and is incorrectly described in literature distributed to students and in published articles from the NRMP.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗

PubMed1993

Algorithms for detecting antibodies to HIV-1: results from a rural Ugandan cohort.

OBJECTIVE: To evaluate an algorithm using two enzyme immunoassays (EIA) for anti-HIV-1 antibodies in a rural African population and to assess alternative simplified algorithms. METHODS: Sera obtained from 7895 individuals in a rural population survey were tested using an algorithm based on two different EIA systems: Recombigen HIV-1 EIA and Wellcozyme HIV-1 Recombinant. Alternative algorithms were assessed using negative or confirmed positive sera. RESULTS: None of the 227 sera classified as unequivocably negative by the two assays were positive by Western blot. Of 192 sera unequivocably positive by both assays, four were seronegative by Western blot. The possibility of technical error cannot be ruled out in three of these. One of the alternative algorithms assessed classified all borderline or discordant assay results as negative had a specificity of 100% and a sensitivity of 98.4%. The cost of this algorithm is one-third that of the conventional algorithm. CONCLUSIONS: Our evaluation suggests that high specificity and sensitivity can be obtained without using Western blot and at a considerable reduction in cost.

Algorithms↗

PubMed1989

A microcomputer algorithm for solving first-order compartmental models involving recycling.

A general algorithm for solving first-order compartmental models including recycling systems has been developed and its implementation on a microcomputer is described. Matrix algebra is used to obtain for any compartmental model an analytical solution, which is expressed as the exponential of a matrix of rate constants. A special technique is used in the algorithm to enable this exponential to be evaluated with a rapidly converging series. Truncation errors incurred in this process are estimated automatically. Thus, in an extreme case, where these errors may be significant, the appropriate action can be taken. Given a particular model, the user enters the model parameters into a rate matrix according to a simple rule. The algorithm then uses this matrix to solve the model, and thus no specialized mathematical knowledge is needed. The algorithm is given in a short BASIC program (60 lines) listed in an appendix. No additional software is required. By running this program on a standard microcomputer, the user can solve models of any complexity: those up to 15 compartments in seconds and those up to 30 compartments within a minute. The algorithm is thus ideally suited to solve kinetic models describing the transport of radionuclides in the environment or the translocation of elements in biological systems such as the metabolic models recommended by the International Commission on Radiological Protection (ICRP). Given the initial amount of material in each compartment at time t = 0, together with its radioactive decay constant, the algorithm gives both the amount in each compartment at any future time t and the number of disintegrations that will have occurred in each compartment up to time t. The computer program, shown in an appendix, could easily be used to calculate disintegrations over any time interval of interest, or to predict the quantities or fractions of an intake expected to be present in any in vivo or excretion compartments of interest. Thus, the algorithm can be useful in both the design and conduct of bioassay and internal dose assessment procedures.

Algorithms↗

PubMed1996

Prospective evaluation of a dose prediction algorithm for intravenous tobramycin in adolescent and adult patients with cystic fibrosis.

The predictive performance of a new algorithm to calculate the initial daily dose of tobramycin in patients with cystic fibrosis (CF) was prospectively evaluated. Twenty-six patients with CF (15 men, 11 women, 18-45 years of age) with an acute exacerbation of their chronic pulmonary infection were treated with intravenous tobramycin. The initial dose was calculated with a previously presented algorithm. This algorithm was derived from correlation analysis performed on the adjusted daily dose guided by the determination of serum concentrations: dose (mg three times daily) = 90 + 2.13 x LBM (kg), where LBM (male) = (1.1 x body weight [BW]) - (128 x BW2/height2) and LBM (female) = (1.07 x BW) - (148 x BW2/height2). The predictive performance of this algorithm was evaluated comparing the calculated initial daily dose with the adjusted daily dose for peak and trough levels of 9-11 mg/L and 1.0 mg/L, respectively. Mean squared error and mean error were determined as reflections of precision and bias. The predictive performance of the algorithm was compared with historical data on the predictive performance of the standard equation to dose of 3.3 mg/kg body weight three times daily. The dose calculated with the algorithm proved to give peak serum concentrations in a narrower range and to have a greater precision, but bias was equal. Applying the algorithm, more patients had initial peak serum concentrations in the pre-determined range of 9-11 mg/L than when using the standard equation, so fewer dose adjustments had to be made.

Adolescent↗

PubMed2003

HIV-1 protease and reverse transcriptase mutation patterns responsible for discordances between genotypic drug resistance interpretation algorithms.

Several rules-based algorithms have been developed to interpret results of HIV-1 genotypic resistance tests. To assess the concordance of these algorithms and to identify sequences causing interalgorithm discordances, we applied four publicly available algorithms to the sequences of isolates from 2,045 individuals in northern California. Drug resistance interpretations were classified as S for susceptible, I for intermediate, and R for resistant. Of 30,675 interpretations (2,045 sequences x 15 drugs), 4.4% were completely discordant, with at least one algorithm assigning an S and another an R; 29.2% were partially discordant, with at least one algorithm assigning an S and another an I, or at least one algorithm assigning an I and another an R; and 66.4% displayed complete concordance, with all four algorithms assigning the same interpretation. Discordances between nucleoside reverse transcriptase inhibitor interpretations usually resulted from several simple, frequently occurring mutational patterns. Discordances between protease inhibitor interpretations resulted from a larger number of more complex mutation patterns. Discordances between nonnucleoside reverse transcriptase inhibitor interpretations were uncommon and resulted from a small number of individual drug resistance mutations. Determining the clinical significance of these mutation patterns responsible for interalgorithm discordances will improve interalgorithm concordance and the accuracy of genotypic resistance interpretation.

Algorithms↗

PubMed2005

Segmentation algorithm for DNA sequences.

A new measure, to quantify the difference between two probability distributions, called the quadratic divergence, has been proposed. Based on the quadratic divergence, a new segmentation algorithm to partition a given genome or DNA sequence into compositionally distinct domains is put forward. The new algorithm has been applied to segment the 24 human chromosome sequences, and the boundaries of isochores for each chromosome were obtained. Compared with the results obtained by using the entropic segmentation algorithm based on the Jensen-Shannon divergence, both algorithms resulted in all identical coordinates of segmentation points. An explanation of the equivalence of the two segmentation algorithms is presented. The new algorithm has a number of advantages. Particularly, it is much simpler and faster than the entropy-based method. Therefore, the new algorithm is more suitable for analyzing long genome sequences, such as human and other newly sequenced eukaryotic genome sequences.

Algorithms↗

PubMed1997

Exact and approximate rebinning algorithms for 3-D PET data.

This paper presents two new rebinning algorithms for the reconstruction of three-dimensional (3-D) positron emission tomography (PET) data. A rebinning algorithm is one that first sorts the 3-D data into an ordinary two-dimensional (2-D) data set containing one sinogram for each transaxial slice to be reconstructed; the 3-D image is then recovered by applying to each slice a 2-D reconstruction method such as filtered-backprojection. This approach allows a significant speedup of 3-D reconstruction, which is particularly useful for applications involving dynamic acquisitions or whole-body imaging. The first new algorithm is obtained by discretizing an exact analytical inversion formula. The second algorithm, called the Fourier rebinning algorithm (FORE), is approximate but allows an efficient implementation based on taking 2-D Fourier transforms of the data. This second algorithm was implemented and applied to data acquired with the new generation of PET systems and also to simulated data for a scanner with an 18 degrees axial aperture. The reconstructed images were compared to those obtained with the 3-D reprojection algorithm (3DRP) which is the standard "exact" 3-D filtered-backprojection method. Results demonstrate that FORE provides a reliable alternative to 3DRP, while at the same time achieving an order of magnitude reduction in processing time.

Algorithms↗

PubMed2000

Comparison of 3-D maximum a posteriori and filtered backprojection algorithms for high-resolution animal imaging with microPET.

We have evaluated the performance of two three-dimensional (3-D) reconstruction algorithms with data acquired from microPET, a high resolution tomograph dedicated to small animal imaging. The first was a linear filtered-backprojection algorithm (FBP) with reprojection of the missing data, and the second was a statistical maximum a posteriori probability algorithm (MAP). The two algorithms were evaluated in terms of their resolution performance, both in phantoms and in vivo. Sixty independent realizations of a phantom simulating the brain of a baby monkey were acquired, each containing three million counts. Each of these realizations was reconstructed independently with both algorithms. The ensemble of the 60 reconstructed realizations was used to estimate the standard deviation as a measure of the noise for each reconstruction algorithm. More detail was recovered in the MAP reconstruction without an increase in noise relative to FBP. Studies in a simple cylindrical compartment phantom demonstrated improved recovery of known activity ratios with MAP. Finally, in vivo studies also demonstrated a clear improvement in spatial resolution using the MAP algorithm. The quantitative accuracy of the MAP reconstruction was also evaluated by comparison with autoradiography and direct well counting of tissue samples and was shown to be superior.

Algorithms↗

PubMed2000

Quasi-exact filtered backprojection algorithm for long-object problem in helical cone-beam tomography.

Exact reconstruction from axially truncated cone-beam projections acquired with a helical vertex path is a challenging problem for which solutions are currently under investigation by some researchers. This paper deals with a difficult class of this problem called the long-object problem. Its purpose is to reconstruct a central region of interest (ROI) of a long object when the helical path extends only a little bit above and below the ROI. By extending the authors' recent approach based on the triangular decomposition of the Grangeat formula, we derive quasi-exact reconstruction algorithms whose overall structure is of filtered backprojection (FBP) style. Unlike the previous similar approaches to the long-object problem, the proposed FBP algorithms do not require additional two circular scans at the ends of the helical path. Furthermore, the algorithms require a significantly smaller detector area and achieve improved image quality even for a large pitch compared with the approximate Feldkamp algorithms. One drawback of the proposed algorithms is the computational time, which is much longer than for the Feldkamp algorithms. We show some simulation results to demonstrate the performances of the proposed algorithms.

Algorithms↗

PubMed2001

An interior point iterative maximum-likelihood reconstruction algorithm incorporating upper and lower bounds with application to SPECT transmission imaging.

The algorithm we consider here is a block-iterative (or ordered subset) version of the interior point algorithm for transmission reconstruction. Our algorithm is an interior point method because each vector of the iterative sequence [x(k)], k = 0, 1, 2, ... satisfies the constraints a(j) < x(j)k < b(j), j = 1, ..., J. Because it is a block-iterative algorithm that reconstructs the transmission attenuation map and places constraints above and below the pixel values of the reconstructed image, we call it the BITAB method. Computer simulations using the three-dimensional mathematical cardiac and torso phantom, reveal that the BITAB algorithm in conjunction with reasonably selected prior upper and lower bounds has the potential to improve the accuracy of the reconstructed attenuation coefficients from truncated fan beam transmission projections. By suitably selecting the bounds, it is possible to restrict the over estimation of coefficients outside the fully sampled region, that results from reconstructing truncated fan beam projections with iterative transmission algorithms such as the maximum-likelihood gradient type algorithm.

Algorithms↗

PubMed2005

An efficient and accurate algorithm for assigning nuclear overhauser effect restraints using a rotamer library ensemble and residual dipolar couplings.

Nuclear Overhauser effect (NOE) distance restraints are the main experimental data from protein nuclear magnetic resonance (NMR) spectroscopy for computing a complete three dimensional solution structure including sidechain conformations. In general, NOE restraints must be assigned before they can be used in a structure determination program. NOE assignment is very time-consuming to do manually, challenging to fully automate, and has become a key bottleneck for high-throughput NMR structure determination. The difficulty in automated NOE assignment is ambiguity: there can be tens of possible different assignments for an NOE peak based solely on its chemical shifts. Previous automated NOE assignment approaches rely on an ensemble of structures, computed from a subset of all the NOEs, to iteratively filter ambiguous assignments. These algorithms are heuristic in nature, provide no guarantees on solution quality or running time, and are slow in practice. In this paper we present an accurate, efficient NOE assignment algorithm. The algorithm first invokes the algorithm in [30, 29] to compute an accurate backbone structure using only two backbone residual dipolar couplings (RDCs) per residue. The algorithm then filters ambiguous NOE assignments by merging an ensemble of intra-residue vectors from a protein rotamer database, together with internuclear vectors from the computed backbone structure. The protein rotamer database was built from ultra-high resolution structures (<1.0 A) in the Protein Data Bank (PDB). The algorithm has been successfully applied to assign more than 1,700 NOE distance restraints with better than 90% accuracy on the protein human ubiquitin using real experimentally-recorded NMR data. The algorithm assigns these NOE restraints in less than one second on a single-processor workstation.

Algorithms↗

PubMed2002

A novel algorithm for cardiac biosignal filtering based on filtered residue method.

In this paper, a new algorithm is presented for the filtering (de-noising) of cardiac bioelectrical signals. The primary target of this algorithm is the class of cardiac action potentials recorded using voltage-sensitive dyes, although the method is also applied to electrocardiographic signals. High periodicity is one of the main features of cardiac biosignals. The proposed algorithm exploits this feature in filtering signals with a minimum amount of distortion. The basic idea is to use signal averaging in time to find the stationary portion of the signal. The residue is found by subtracting the signal average from the corresponding points of the input. After passing through a low-pass filter, the filtered residue (FR) is added back to the signal average to reconstruct the output. The practical implementation of the filter residue algorithm is discussed. Stretching and shrinking operations are the basis for the conversion of quasi-periodic signals into periodic signals, which can then be subjected to the FR algorithm. Various examples are presented, and error estimation is performed to guide the selection of optimal parameters for the algorithm. The ability of the algorithm to reconstruct the variation among beats is demonstrated, and its limitations are discussed.

Action Potentials↗

PubMed2005

An automatic beat detection algorithm for pressure signals.

Beat detection algorithms have many clinical applications including pulse oximetry, cardiac arrhythmia detection, and cardiac output monitoring. Most of these algorithms have been developed by medical device companies and are proprietary. Thus, researchers who wish to investigate pulse contour analysis must rely on manual annotations or develop their own algorithms. We designed an automatic detection algorithm for pressure signals that locates the first peak following each heart beat. This is called the percussion peak in intracranial pressure (ICP) signals and the systolic peak in arterial blood pressure (ABP) and pulse oximetry (SpO2) signals. The algorithm incorporates a filter bank with variable cutoff frequencies, spectral estimates of the heart rate, rank-order nonlinear filters, and decision logic. We prospectively measured the performance of the algorithm compared to expert annotations of ICP, ABP, and SpO2 signals acquired from pediatric intensive care unit patients. The algorithm achieved a sensitivity of 99.36% and positive predictivity of 98.43% on a dataset consisting of 42,539 beats.

Algorithms↗