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PubMed1992

Mathematical characterization of Chaos Game Representation. New algorithms for nucleotide sequence analysis.

Chaos Game Representation (CGR) can recognize patterns in the nucleotide sequences, obtained from databases, of a class of genes using the techniques of fractal structures and by considering DNA sequences as strings composed of four units, G, A, T and C. Such recognition of patterns relies only on visual identification and no mathematical characterization of CGR is known. The present report describes two algorithms that can predict the presence or absence of a stretch of nucleotides in any gene family. The first algorithm can be used to generate DNA sequences represented by any point in the CGR. The second algorithm can simulate known CGR patterns for different gene families by setting the probabilities of occurrence of different di- or trinucleotides by a trial and error process using some guidelines and approximate rules-of-thumb. The validity of the second algorithm has been tested by simulating sequences that can mimic the CGRs of vertebrate non-oncogenes, proto-oncogenes and oncogenes. These algorithms can provide a mathematical basis of the CGR patterns obtained using nucleotide sequences from databases.

Algorithms↗

PubMed1995

A simulation algorithm for ultrasound liver backscattered signals.

In this study, we present a simulation algorithm for the backscattered ultrasound signal from liver tissue. The algorithm simulates backscattered signals from normal liver and three different liver abnormalities. The performance of the algorithm has been tested by statistically comparing the simulated signals with corresponding signals obtained from a previous in vivo study. To verify that the simulated signals can be classified correctly we have applied a classification technique based on an artificial neural network. The acoustic features extracted from the spectrum over a 2.5 MHz bandwidth are the attenuation coefficient and the change of speed of sound with frequency (dispersion). Our results show that the algorithm performs satisfactorily. Further testing of the algorithm is conducted by the use of a data acquisition and analysis system designed by the authors, where several simulated signals are stored in memory chips and classified according to their abnormalities.

Acoustics↗

PubMed1992

Dynamic programming algorithms for biological sequence comparison.

Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.

Algorithms↗

PubMed1990

Hypermedia and randomized algorithms for medical expert systems.

KNET is an environment for constructing probabilistic, knowledge-intensive systems within the axiomatic framework of decision theory. The KNET architecture defines a complete separation between the hypermedia user interface on the one hand, and the representation and management of expert opinion on the other. KNET offers a choice of algorithms for probabilistic inference. We and our coworkers have used KNET to build consultation systems for lymph-node pathology, bone-marrow transplantation therapy, clinical epidemiology, and alarm management in the intensive-care unit. Most important, KNET contains a randomized approximation scheme (RAS) for the difficult and almost certainly intractable problem of Bayesian inference. Our algorithm can, in many circumstances, perform efficient approximate inference in large and richly interconnected models of medical diagnosis. In this article, we describe the architecture of KNET, construct a randomized algorithm for probabilistic inference, and analyze the algorithm's performance. Finally, we characterize our algorithms' empiric behavior and explore its potential for parallel speedups. From design to implementation, then, KNET demonstrates the crucial interaction between theoretical computer science and medical informatics.

Algorithms↗

PubMed1992

BIO-SPEAD: a parallel computing environment to accelerate development of biologic signal processing algorithms.

We have created BIO-SPEAD (pronounced speed), a BIOlogical Signal Processing Environment for Algorithm Development. BIO-SPEAD is designed to accelerate development of complex algorithms which integrate information derived from single or multiple physiologic waveforms. BIO-SPEAD currently performs all of the basic analyses of several arterial blood pressure waveforms, and allows the user to utilize the results of those low-level analyses for development of more complex algorithms. We utilized a parallel programming architecture called the Process Trellis which keeps the different tasks, or processes, within BIO-SPEAD independent of each other. Additionally, we have developed a graphics interface to enable the user to visualize the waveform under analysis, the low-level system analysis, and the internal workings of the algorithm under development. The system has been used for several algorithm development projects and has demonstrated its utility.

Algorithms↗

PubMed1992

Development and validation of a logistic regression-derived algorithm for estimating the incremental probability of coronary artery disease before and after exercise testing.

OBJECTIVES: Our goals were to develop and validate a multivariate algorithm for estimating the incremental probability of the presence of coronary artery disease. BACKGROUND: Multivariate methods, including logistic regression analysis, have been extensively applied to diagnostic exercise testing. However, few previous studies have included both an incremental design and external validation. METHODS: A retrospective collection of clinical, exercise test and catheterization data was performed involving four U.S. referral medical centers. All patients had no prior history of coronary disease and had undergone coronary angiography < or = 3 months after exercise stress testing. An algorithm was developed in one center (590 patients with a 41% prevalence of coronary artery disease) with the use of logistic regression analysis and was validated in the other three centers (1,234 patients, 70% prevalence). The algorithm incorporated pretest variables (age, gender, symptoms, diabetes, cholesterol), exercise electrocardiographic (ECG) variables (mm of ST segment depression, ST slope, peak heart rate, metabolic equivalents [METs], exercise angina) and one thallium variable. Discrimination was measured with receiver operating characteristic curve analysis. Calibration (that is, reliability) was assessed from a comparison of probability estimates and the actual prevalence of disease. RESULTS: The overall incremental receiver operating characteristic curve areas for the validation group were pretest, -0.738 +/- 0.016; postexercise ECG, 0.78 (SE 0.017); and postthallium, 0.82 (SE 0.016); p < 0.01 for both increments. Within the three validation institutions, the institution with a disease prevalence closest to that of the derivation institution had the best incremental receiver operating characteristic curve areas. There was a stepwise incremental improvement in calibration especially from exercise ECG to thallium testing. CONCLUSIONS: An incremental multivariate algorithm derived in one center reliably estimated disease probability in patients from three other centers. The incremental value of testing was best demonstrated when the derivation and validation groups had a similar disease prevalence. This algorithm may be useful in decision making that relates to the diagnosis of coronary disease.

Algorithms↗

PubMed1992

Slope filtered pointwise correlation dimension algorithm and its evaluation with prefibrillation heart rate data.

Various studies have shown that a low variability in heart rate is associated with increased risk of ventricular fibrillation. Low chaotic (correlation) dimension in the heart rate also appears to predict fibrillation risk. However, these results have been based on intergroup comparisons and have not been found useful for predicting when a patient may fibrillate with any degree of sensitivity, specificity, or temporal accuracy. There are two primary limitations in using dimensional analysis to predict imminent fibrillation. The first is that the standard algorithms (for correlation dimension) assume stationarity of the system. The second limitation is that these algorithms require 10,000-50,000 data points to achieve good accuracy. Thus, even if stationarity were not an issue, there would be a lag of 2.4-12 hours to warn of impending fibrillation. An algorithm has been developed to calculate an accurate pointwise correlation dimension of heart rate data. The slope filtered pointwise correlation dimension algorithm requires as few as 1,000 points of data. Using this algorithm, it was found that the correlation dimension dropped from 2.50 +/- 0.81 to 1.07 +/- 0.18 in the minute before fibrillation in conscious pigs with an occluded coronary artery. In clinical studies, Holter tapes from patients that had suffered fatal fibrillation were also analyzed along with healthy controls and nonfibrillation ventricular patients. The fibrillation patients all had excursions of low dimension (less than 1.5), while the majority of the others did not. In the minutes before fibrillation, the correlation dimension dropped to a steady range of 0.8-1.3. Drops in the slope filtered pointwise correlation dimension appear to predict fibrillation in animals and patients.

Algorithms↗

PubMed1997

A new electrocardiographic algorithm using retrograde P waves for differentiating atrioventricular node reentrant tachycardia from atrioventricular reciprocating tachycardia mediated by concealed accessory pathway.

OBJECTIVES: The purpose of this study was to use an electrocardiographic (ECG) algorithm, derived from the results of radiofrequency ablation, to discriminate atrioventricular node reentrant tachycardia (AVNRT) from atrioventricular reciprocating tachycardia (AVRT) and to localize a concealed accessory pathway, prospectively. BACKGROUND: Information about ECG criteria for differentiating AVNRT from AVRT is limited and has not been confirmed by surgical or catheter ablation. METHODS: Four hundred six ECGs (obtained from 406 different patients) that demonstrated narrow QRS complex (< 0.12 s) supraventricular tachycardia with an RP' interval less than the P'R interval or pseudo r' wave in lead V1 or pseudo S wave in inferior leads, or both, were examined, and the results were confirmed by radiofrequency catheter ablation. The initial 226 ECGs were analyzed to develop a stepwise algorithm, and the subsequent 180 ECGs were prospectively evaluated by the new algorithm. RESULTS: The presence of a pseudo r' wave in lead V1 or a pseudo S wave in leads II, III, aVF indicated anterior-type AVNRT with an accuracy of 100%. With the difference of RP' intervals in leads V1 and III > 20 ms, posterior-type AVNRT could be differentiated from AVRT utilizing a posteroseptal pathway with a sensitivity of 71% (95% confidence interval [CI] 55% to 89%), a specificity of 87% (95% CI 67% to 97%) and a positive predictive value of 75% (95% CI 56% to 91%). According to the polarity of retrograde P waves in leads V1, II, III, aVF and I during AVRT, the concealed accessory pathway could be localized to one of the nine regions on the atrioventricular annuli with an accuracy of 75% (for a right midseptal pathway) to 93.8% (for a left posterior pathway). Overall, the new algorithm had an accuracy of 97.8% in discriminating AVNRT from AVRT and 88.1% in localizing a concealed accessory pathway, prospectively. Prediction was incorrect in only 15 patients (9.1%). CONCLUSIONS: The new ECG algorithm derived from the analysis of retrograde P waves during tachycardia could provide a criterion for differential diagnosis between AVNRT and AVRT and for predicting the location of concealed accessory pathways.

Adolescent↗

PubMedDate not supplied

A second-generation computer-based edge detection algorithm for short-axis, two-dimensional echocardiographic images: accuracy and improvement in interobserver variability.

The present study tested the hypothesis that a second-generation endocardial edge detection algorithm that used a priori endocardial and epicardial information would improve accuracy and reduce the variability of border definition. Five nonexpert observers utilized the version 2 algorithm on 20 cycles of two-dimensional short-axis images (five excellent, seven good, and eight poor quality studies stored digitally from a previously reported project). Manually defined areas by five recognized experts on these 20 cardiac cycles were considered to be "true areas." Areas defined by the experts with version 1 of the algorithm were also used for comparison. Regression of the version 2 areas with mean, manually defined excellent quality areas yielded a similar correlation (r = 0.985) to that reported between the manual and the version 1 areas (r = 0.986). For all 20 cycles in the series, however, the correlation between version 2 and the manually defined areas was lower (r = 0.952) than that of the same correlation with version 1 areas (r = 0.980). For all studies the interobserver variability (percent area difference) was +/- 14.4% for manually defined borders, +/- 11.1% for version 1-defined borders, and +/- 7.7% for version 2-defined borders. No difference in variability was observed for excellent quality studies (+/- 5.3% versus 5.2%) between version 1 and version 2 areas. However, the version 2 algorithm significantly reduced interobserver variability for good and poor quality studies (+/- 8.4% to 7.6%, p less than 0.025, and 16.3% to 9.1%, p less than 0.05, respectively). We concluded that: the version 2 algorithm provided accuracy and significantly reduced the variability of area measurement in good and poor quality studies and that epicardial information was important to the improvement by providing wall thickness information to assist in filling areas of dropout and avoidance of intracavitary structures.

Algorithms↗

PubMed1997

Application of a genetic algorithm in the conformational analysis of methylene-acetal-linked thymine dimers in DNA: comparison with distance geometry calculations.

The three-dimensional spatial structure of a methylene-acetal-linked thymine dimer present in a 10 basepair (bp) sense-antisense DNA duplex was studied with a genetic algorithm designed to interpret NOE distance restraints. Trial solutions were represented by torsion angles. This means that bond angles for the dimer trial structures are kept fixed during the genetic algorithm optimization. Bond angle values were extracted from a 10 bp sense-antisense duplex model that was subjected to energy minimization by means of a modified AMBER force field. A set of 63 proton-proton distance restraints defining the methylene-acetal-linked thymine dimer was available. The genetic algorithm minimizes the difference between distances in the trial structures and distance restraints. A large conformational search space could be covered in the genetic algorithm optimization by allowing a wide range of torsion angles. The genetic algorithm optimization in all cases led to one family of structures. This family of the methylene-acetal-linked thymine dimer in the duplex differs from the family that was suggested from distance geometry calculations. It is demonstrated that the bond angle geometry around the methylene-acetal linkage plays an important role in the optimization.

Algorithms↗

PubMed1994

The effect of an intraoperative treatment algorithm on physicians' transfusion practice in cardiac surgery.

BACKGROUND: Inappropriate transfusion in cardiac surgery may, in part, be due to empiric transfusion therapy instituted in the absence of timely laboratory data. Therefore, the effect of a transfusion decision algorithm based on intraoperative coagulation monitoring of physicians' transfusion practice and the transfusion outcome was evaluated. STUDY DESIGN AND METHODS: In a randomized, controlled trial, cardiac surgical patients determined to have microvascular bleeding at the cessation of cardiopulmonary bypass were assigned to algorithm (A) or standard (S) therapy. Group A was treated with plasma and platelet therapy according to a transfusion algorithm based on on-site coagulation data available within 4 minutes. For Group S, the use of laboratory-based data and the decision to transfuse blood components were at physician discretion. RESULTS: Sixty-six patients were entered into the study (Group A, n = 30; Group S, n = 36). Other than the fact that there were significantly more female patients in Group S than in Group A, no differences between cohorts in regard to perioperative risk factors for blood transfusion needs were identified. Therefore, gender was factored in as a covariate in the statistical analysis. Group A patients received fewer hemostatic blood component units (p = 0.008) and had fewer total donor exposures (p = 0.007) during the entire hospitalization period. Linear regression analysis of the differences in slopes in Groups A and S for the relationships between the red cell volume lost and the red cell volume transfused (p < 0.03), non-red cell units transfused (p < 0.0001), and total number of blood components transfused (p < 0.0001) demonstrated that physicians' transfusion practice was significantly altered by the use of a transfusion algorithm with on-site coagulation data, independent of surgical blood losses. CONCLUSION: The use of algorithms by transfusion decision makers can serve as an effective physician education intervention.

Adult↗

PubMed1991

An algorithm for the DNA sequence generation from k-tuple word contents of the minimal number of random fragments.

An algorithm is described for generation of the long sequence written in a four letter alphabet from the constituent k-tuple words in the minimal number of separate, randomly defined fragments of the starting sequence. It is primarily intended for use in sequencing by hybridization (SBH) process- a potential method for sequencing human genome DNA (Drmanac et al., Genomics 4, pp. 114-128, 1989). The algorithm is based on the formerly defined rules and informative entities of the linear sequence. The algorithm requires neither knowledge on the number of appearances of a given k-tuple in sequence fragments, nor the information on which k-tuple words are on the ends of a fragment. It operates with the mixed content of k-tuples of the various lengths. The concept of the algorithm enables operations with the k-tuple sets containing false positive and false negative k-tuples. The content of the false k-tuples primarily affects the completeness of the generated sequence, and its correctness in the specific cases only. The algorithm can be used for the optimization of SBH parameters in the simulation experiments, as well as for the sequence generation in the real SBH experiments on the genomic DNA.

Algorithms↗

PubMed1992

Evaluation of a 3D reconstruction algorithm for multi-slice PET scanners.

A fully 3D reconstruction algorithm based on filtered backprojection was evaluated for the reconstruction of data obtained with multi-slice positron emission tomography (PET) scanners which have had the septa removed. This algorithm uses forward-projection through the reconstructed images of a 2D subset of the data to complete the 3D dataset thus satisfying the condition of shift invariance. This is followed by 3D filtered backprojection. Axial sampling was doubled by combining adjacent polar angles, thus improving reconstructed axial resolution. The algorithm was tested using real and simulated datasets and gave high quality reconstructions without artifacts over a wide range of imaging conditions. Events are placed accurately throughout the imaging volume as determined by measurements with a MRI/PET registration phantom. The forward-projection step leads to degradation in image resolution due to insufficient axial and transaxial sampling. This effect is amplified if multiple iterations of the algorithm are used, with little decrease in image noise. Changing the filter employed in the initial 2D reconstruction can be used to alter the noise and resolution characteristics of the 3D images. This algorithm has proved very robust at reconstructing 3D PET data and is relatively fast. Those small problems which exist can be attributed to detector sampling problems, especially in the axial direction, which is a consequence of the geometry of these scanners, which are designed primarily for 2D data acquisition.

Algorithms↗

PubMed1996

Prediction of HIV peptide epitopes by a novel algorithm.

Identification of promiscuous or multideterminant T cell epitopes is essential for HIV vaccine development, however, current methods for T cell epitope identification are both cost intensive and labor intensive. We have developed a computer-driven algorithm, named EpiMer, which searches protein amino acid sequences for putative MHC class I- and/or class II-restricted T cell epitopes. This algorithm identifies peptides that contain multiple MHC-binding motifs from protein sequences. To evaluate the predictive power of EpiMer, the amino acid sequences of the HIV-1 proteins nef, gp160, gag p55, and tat were searched for regions of MHC-binding motif clustering. We assessed the algorithm's predictive power by comparing the EpiMer-predicted peptide epitopes to T cell epitopes that have been published in the literature. The EpiMer method of T cell epitope identification was compared to the standard method of synthesizing short, overlapping peptides and testing them for immunogenicity (overlapping peptide method), and to an alternate algorithm that has been used to identify putative T cell epitopes from primary structure (AMPHI). For the four HIV-1 proteins analyzed, the in vitro testing of EpiMer peptides for immunogenicity would have required the synthesis of fewer total peptides than either AMPHI or the overlapping peptide method. The EpiMer algorithm proved to be more efficient and more sensitive per amino acid than both the overlapping peptide method and AMPHI. The EpiMer predictions for these four HIV proteins are described. Since EpiMer-predicted peptides have the potential to bind to multiple MHC alleles, they are strong candidates for inclusion in a synthetic HIV vaccine.

Algorithms↗

PubMed1996

An algorithm for finding maximal common subtopologies in a set of protein structures.

For the comparison and analysis of protein structures, it is of interest to find maximal common substructures in a given set of proteins. This question is also relevant for motif definition and structure classification. In this paper we describe first a new suitable representation of the secondary structure topology of a protein by an undirected labeled graph. Based on this representation we developed a new fast algorithm that finds all common subtopologies in a set of protein structures. Our method is based on the algorithm by Bron and Kerbosch (1973), which enumerates all maximal cliques in a graph. The main improvement of our algorithm is to restrict the search process to cliques that represent connected substructures. This restriction reduces the number of cliques to be considered during the search process and the size of the search tree drastically. Thus we are able to handle large proteins. Experiments show the efficiency and superiority of our algorithm in comparison with other existing algorithms basing on graph-theoretical methods.

Algorithms↗

PubMed1995

Cost-reducing treatment algorithms for antineoplastic drug-induced nausea and vomiting.

A treatment algorithm and preprinted order form developed to reduce the cost of treating antineoplastic drug-induced nausea and vomiting are described. A team including pharmacists, oncologists, and oncology nurses developed a treatment algorithm to reduce the cost of antiemetic therapy for patients receiving antineoplastic therapy at a 719-bed academic medical center. The algorithm incorporated the following concepts: matching antiemetic therapy with the emetogenic potential of the antineoplastic regimen, reducing ondansetron dosages, increasing the ratio of oral to intravenous therapy, and treating delayed-onset nausea and vomiting without using serotonin-receptor antagonists. To help physicians learn and use the treatment algorithm, it was incorporated into an order form for both antineoplastic and antiemetic drugs. Separate order forms were created for pediatric and adult patients. A comparison of outcome data before and after implementation of the practice guidelines showed that the patient outcomes were at least as good after implementation as before. More than a year after the guidelines were implemented, more than 85% of antiemetic regimens prescribed for antineoplastic drug-induced nausea and vomiting were in compliance with the guidelines. A cost avoidance of nearly $205,000 was realized in the first year. Collaboration with oncologists at the start of the care plan was a key element in its success. An antiemetic treatment algorithm, integrated with a preprinted physician order form, was well accepted and has reduced expenses for antiemetic therapy.

Adult↗

PubMed1994

An algorithm for identifying regions of a DNA sequence that satisfy a content requirement.

We present a dynamic programming algorithm for identifying regions of a DNA sequence that meet a user-specified compositional requirement. Applications of the algorithm include finding C + G-rich regions, locating TA + CG-deficient regions, identifying CpG islands, and finding regions rich in periodical three-base patterns. The algorithm has an advantage over the simple window method in that the algorithm shows the exact location of each identified region. The algorithm has been implemented as a portable C program called LCP (Local Content Program). LCP is extremely efficient in computer time and memory; it instantly locates all regions of a long DNA sequence meeting a given requirement. The LCP program was used to analyze the rabbit alpha-like globin gene cluster sequence.

Algorithms↗

PubMed1996

A polynomial-time algorithm for a class of protein threading problems.

This paper presents an algorithm for constructing an optimal alignment between a three-dimensional protein structure template and an amino acid sequence. A protein structure template is given as a sequence of amino acid residue positions in three-dimensional space, along with an array of physical properties attached to each position; these residue positions are sequentially grouped into a series of core secondary structures (central helices and beta sheets). In addition to match scores and gap penalties, as in a traditional sequence-sequence alignment problem, the quality of a structure-sequence alignment is also determined by interaction preferences among amino acids aligned with structure positions that are spatially close (we call these 'long-range interactions'). Although it is known that constructing such a structure-sequence alignment in the most general form is NP-hard, our algorithm runs in polynomial time when restricted to structures with a 'modest' number of long-range amino acid interactions. In the current work, long-range interactions are limited to interactions between amino acids from different core secondary structures. Dividing the series of core secondary structures into two subseries creates a cut set of long-range interactions. If we use N, M and C to represent the size of an amino acid sequence, the size of a structure template, and the maximum cut size of long-range interactions, respectively, the algorithm finds an optimal structure-sequence alignment in O(21C NM) time, a polynomial function of N and M when C = O(log(N + M)). When running on structure-sequence alignment problems without long-range intersections, i.e. C = 0, the algorithm achieves the same asymptotic computational complexity of the Smith-Waterman sequence-sequence alignment algorithm.

Algorithms↗