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PubMed2001

Exact algorithms for computing pairwise alignments and 3-medians from structure-annotated sequences (extended abstract).

Given the problem of mutation saturation in ancient molecular sequences, there is great interest in inferring phylogenies from higher-order types of molecular data that change more slowly, such as genomic organization and the secondary and tertiary structures of ribosomal RNA and proteins. In this paper, we define edit distances based on two representations of RNA secondary structure, arc annotation and hierarchical string annotation, and give algorithms for computing these distances on pairs of annotated sequences, aligning pairs of annotated sequences, and computing 3-median annotated sequences from triples of annotated sequences. The 3-median algorithms can be used as part of a well-known iterative heuristic for inferring phylogenies. All given algorithms are adapted from algorithms for computing longest common annotated subsequences of pairs of annotated sequences.

Algorithms↗

PubMed2001

A new algorithm for analysis of within-host HIV-1 evolution.

A new algorithm for inferring the evolution of within-host viral sequences is presented. A sequential-linking approach is developed so that a longitudinal phylogenetic tree can be reconstructed from sequential molecular data that are obtained at different time points from the same host. The algorithm employs a codon-based model, which uses a Markov process to describe substitutions between codons, to calculate nonsynonymous and synonymous substitution rates and to distinguish positive selection and neutral evolution. The algorithm is applied to a data set of the V3 region of the HIV-1 envelope genes sequenced at different years after the infection of a single patient. The results suggest that this algorithm may provide a more realistic description of viral evolution than traditional evolutionary models, because it accounts for both neutral and adaptive evolution, and reconstructs a longitudinal phylogenetic tree that describes the dynamic process of viral evolution.

Algorithms↗

PubMed2002

Hierarchical genetic algorithm for near optimal feedforward neural network design.

In this paper, we propose a genetic algorithm based design procedure for a multi layer feed forward neural network. A hierarchical genetic algorithm is used to evolve both the neural networks topology and weighting parameters. Compared with traditional genetic algorithm based designs for neural networks, the hierarchical approach addresses several deficiencies, including a feasibility check highlighted in literature. A multi objective cost function is used herein to optimize the performance and topology of the evolved neural network simultaneously. In the prediction of Mackey Glass chaotic time series, the networks designed by the proposed approach prove to be competitive, or even superior, to traditional learning algorithms for the multi layer Perceptron networks and radial basis function networks. Based upon the chosen cost function, a linear weight combination decision making approach has been applied to derive an approximated Pareto optimal solution set. Therefore, designing a set of neural networks can be considered as solving a two objective optimization problem.

Algorithms↗

PubMed2003

A robust subspace algorithm for principal component analysis.

We present a noise robust PCA algorithm which is an extension of the Oja subspace algorithm and allows tuning the noise sensitivity. We derive a loss function which is minimized by this algorithm and interpret it in a noisy PCA setting. Results on the local stability analysis of this algorithm are given and it is shown that the locally stable equilibria are those which minimize the loss function.

Algorithms↗

PubMed2005

Protein side-chain packing problem: a maximum edge-weight clique algorithmic approach.

"Protein Side-chain Packing" has an ever-increasing application in the field of bio-informatics, dating from the early methods of homology modeling to protein design and to the protein docking. However, this problem is computationally known to be NP-hard. In this regard, we have developed a novel approach to solve this problem using the notion of a maximum edge-weight clique. Our approach is based on efficient reduction of protein side-chain packing problem to a graph and then solving the reduced graph to find the maximum clique by applying an efficient clique finding algorithm developed by our co-authors. Since our approach is based on deterministic algorithms in contrast to the various existing algorithms based on heuristic approaches, our algorithm guarantees of finding an optimal solution. We have tested this approach to predict the side-chain conformations of a set of proteins and have compared the results with other existing methods. We have found that our results are favorably comparable or better than the results produced by the existing methods. As our test set contains a protein of 494 residues, we have obtained considerable improvement in terms of size of the proteins and in terms of the efficiency and the accuracy of prediction.

Algorithms↗

PubMed2005

A robust algorithm for ratio estimation in two-color microarray experiments.

The reliability of the algorithms for ratio estimation in two-color microarray image analysis is very important, as these ratios build up the primary source of information for the subsequent analytical procedures (normalization, clustering, classification, etc). Although various algorithms already exist, there is still a need to develop procedures having higher levels of accuracy and robustness. We present a statistical procedure for the detection and removal of aberrant pixels in two-color microarray images. It is based on a linear regression approach, assuming reasonably high level of correlation between the two color channels. This procedure ensures more robust ratio estimation for the spots in both linear regression and traditional segmentation algorithms. The developed algorithms have been evaluated using simulated artificial images and experimental images of different designs. A demonstration version of the software can be downloaded from http://bioinfo.curie.fr/projects/maia/.

Algorithms↗

PubMed2006

Efficient algorithms and software for detection of full-length LTR retrotransposons.

LTR retrotransposons constitute one of the most abundant classes of repetitive elements in eukaryotic genomes. In this paper, we present a new algorithm for detection of full-length LTR retrotransposons in genomic sequences. The algorithm identifies regions in a genomic sequence that show structural characteristics of LTR retrotransposons. Three key components distinguish our algorithm from that of current software--(i) a novel method that preprocesses the entire genomic sequence in linear time and produces high quality pairs of LTR candidates in run-time that is constant per pair, (ii) a thorough alignment-based evaluation of candidate pairs to ensure high quality prediction, and (iii) a robust parameter set encompassing both structural constraints and quality controls providing users with a high degree of flexibility. We implemented our algorithm into a software program called LTR_par, which can be run on both serial and parallel computers. Validation of our software against the yeast genome indicates superior results in both quality and performance when compared to existing software. Additional validations are presented on rice BACs and chimpanzee genome.

Algorithms↗

PubMed2006

Coexpressionfinder: a new algorithm for finding groups of coexpressed genes.

RESULTS: A new algorithm is developed which is intended to find groups of genes whose expression values change in a concordant manner in a series of experiments with DNA arrays. This algorithm is named as CoexpressionFinder. It can find more complete and internally coordinated groups of gene expression vectors than hierarchical clustering. Also, it finds more genes having coordinated expression. The algorithm's design allows parallel execution. AVAILABILITY: The algorithm is implemented as a Java application which is freely available at: http://www.bioinformatics.ru/cf/index.jsp and http://bioinformatics.ru/cf/index.jsp.

Algorithms↗

PubMed2002

Quantification of distention in CT colonography: development and validation of three computer algorithms.

Three bowel distention-measuring algorithms for use at computed tomographic (CT) colonography were developed, validated in phantoms, and applied to a human CT colonographic data set. The three algorithms are the cross-sectional area method, the moving spheres method, and the segmental volume method. Each algorithm effectively quantified distention, but accuracy varied between methods. Clinical feasibility was demonstrated. Depending on the desired spatial resolution and accuracy, each algorithm can quantitatively depict colonic diameter in CT colonography.

Algorithms↗

PubMed2002

Breast cancer detection: evaluation of a mass-detection algorithm for computer-aided diagnosis -- experience in 263 patients.

PURPOSE: To evaluate the performance of a computer-aided diagnosis (CAD) mass-detection algorithm in marking preoperative masses. MATERIALS AND METHODS: Digitized mammograms were processed with an adaptive enhancement filter followed by a local border refinement stage. Features were then extracted from each detected structure and used to identify potential masses. The performance of the algorithm was evaluated in independent cases obtained from 263 patients from two institutions. Each case contained one or more pathologically proved breast masses. Contralateral mammograms obtained in the same patients that did not contain a visible lesion were used to estimate the CAD marker rate for the algorithm. The tradeoff between detection sensitivity and the number of CAD marks was analyzed in this study. RESULTS: Malignant masses were detected with the computer in 87% (135 of 156), 83% (130 of 156), and 77% (120 of 156) of the malignant cases at CAD marker rates of 1.5, 1.0, and 0.5 marks per mammogram, respectively. The difference between malignant mass-detection performance in subsets of cases collected at each institution was found to be less than 1%. The detection accuracy for benign masses was lower than that for malignant masses. CONCLUSION: This mass-detection algorithm had a high sensitivity for detection of malignant masses. It may be useful as a second opinion in mammographic interpretation.

Algorithms↗

PubMed2005

CT images of abdomen and pelvis: effect of nonlinear three-dimensional optimized reconstruction algorithm on image quality and lesion characteristics.

The purpose of this study was to retrospectively assess the effect of a postprocessing nonlinear three-dimensional optimized reconstruction algorithm on image quality and lesion characteristics in abdominal and pelvic computed tomographic (CT) images. Institutional review board approved the HIPAA-compliant study protocol; informed consent was waived. Abdominal and pelvic CT images (40 patients; male-female ratio, 20:20; age range, 28-86 years) at 5-mm (n = 20) and 2-mm (n = 20) section thicknesses were postprocessed with the algorithm at three noise reduction levels. Image noise at the level of porta hepatis and acetabulum was evaluated with a five-point scale (1, no or minimal noise; 5, unacceptable noise), and presence and number of lesions and conspicuity were assessed. Statistical analysis was performed (Wilcoxon signed rank test, analysis of variance). Significant noise reduction was noted at all three levels with the algorithm (P < .05). Reduction in image contrast was noted with only one noise reduction level (P < .0001). The algorithm improves image noise without affecting lesion conspicuity and detection on low-dose abdominal and pelvic CT images.

Adult↗

PubMed1999

Multinodular disease: anatomic localization at thin-section CT--multireader evaluation of a simple algorithm.

PURPOSE: To evaluate the interobserver variability and accuracy of an algorithm for anatomic localization of small nodules evident on thin-section computed tomographic (CT) images of the lungs. MATERIALS AND METHODS: Four experienced chest radiologists independently evaluated thin-section CT images in 58 patients by using an algorithm and a standard score sheet. Nodules were placed into four possible anatomic locations or categories: perilymphatic, random, associated with small airways disease, or centrilobular. Algorithm accuracy was assessed by comparing the localization by the observers to that expected for each specific disease in the study group on the basis of reports in the literature. Interobserver variability was assessed by placing cases into one of three groups: (a) complete concordance, (b) triple concordance, and (c) discordant. RESULTS: All observers agreed in 79% (46 of 58) of the cases with regard to nodule localization; three of the four concurred in an additional 17% (10 of 58). The observers were correct in 218 (94%) of 232 localizations in the 58 cases. There were no apparent differences in the number of either discordant or incorrect localizations between the observers. The most noteworthy source of error and of disagreement between observers was the confusion of perilymphatic and small airways disease-associated nodules in a small number of cases. CONCLUSION: The proposed algorithm is reproducible and accurate in the majority of cases and facilitates nodule localization at thin-section CT.

Adult↗

PubMed2001

Intraarterial chemotherapy for brain tumors by using a spatial dose fractionation algorithm and pulsatile delivery.

PURPOSE: To evaluate the cause of complications in intraarterial chemotherapy for brain tumors and validate a dosage algorithm based on arterial territory. MATERIALS AND METHODS: Four hundred sixty-two procedures were performed in 113 patients. Technique included pulsatile infusion of a chemotherapeutic agent. Dosage was calculated per hemisphere and divided per arterial territory according to a spatial dose fractionation algorithm based on the vascular territories of major cerebral arteries: middle cerebral artery, 60%; anterior cerebral artery, 20%; posterior cerebral artery, 15%; and perforator arteries, 5%. Hospital charts of all patients were retrospectively reviewed for complications, with specific attention given to the angiograms to determine a cause. Then, subgroup analysis of the chemotherapy protocol with the largest patient population was performed to evaluate predictors of complications. RESULTS: Six (1.3%) complications were asymptomatic; 12 (2.6%), transient neurologic; three (0.6%), permanent minor neurologic; three (0.6%), permanent major neurologic; and 32 (7.0%), seizures. In the subgroup analysis, the hemispheric dose administered according to the algorithm was strongly predictive of seizure and neurologic deficit. CONCLUSION: Neurotoxicity of intraarterial cerebral chemotherapy can be minimized by using pulsatile injection and the described spatial dose fractionation algorithm.

Adolescent↗

PubMed2005

Constraining compartmental models using multiple voltage recordings and genetic algorithms.

Compartmental models with many nonlinearly and nonhomogeneous distributions of voltage-gated conductances are routinely used to investigate the physiology of complex neurons. However, the number of loosely constrained parameters makes manually constructing the desired model a daunting if not impossible task. Recently, progress has been made using automated parameter search methods, such as genetic algorithms (GAs). However, these methods have been applied to somatically recorded action potentials using relatively simple target functions. Using a genetic minimization algorithm and a reduced compartmental model based on a previously published model of layer 5 neocortical pyramidal neurons we compared the efficacy of five cost functions (based on the waveform of the membrane potential, the interspike interval, trajectory density, and their combinations) to constrain the model. When the model was constrained using somatic recordings only, a combined cost function was found to be the most effective. This combined cost function was then applied to investigate the contribution of dendritic and axonal recordings to the ability of the GA to constrain the model. The more recording locations from the dendrite and the axon that were added to the data set the better was the genetic minimization algorithm able to constrain the compartmental model. Based on these simulations we propose an experimental scheme that, in combination with a genetic minimization algorithm, may be used to constrain compartmental models of neurons.

Action Potentials↗

PubMed2002

Algorithms for cytoplasm segmentation of fluorescence labelled cells.

Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre-processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical analysis of a number of shape descriptive features. Objects that have features that differ to that of correctly segmented single cells can be further processed by a splitting step. By statistical analysis we therefore get a feedback system for separation of clustered cells. After the segmentation is completed, the quality of the final segmentation is evaluated. By training the algorithm on a representative set of training images, the algorithm is made fully automatic for subsequent images created under similar conditions. Automatic cytoplasm segmentation was tested on CHO-cells stained with calcein. The fully automatic method showed between 89% and 97% correct segmentation as compared to manual segmentation.

Algorithms↗

PubMed2004

A Canadian clinical practice algorithm for the management of patients with nonvariceal upper gastrointestinal bleeding.

AIM: To use current evidence-based recommendations to provide a user-friendly clinical algorithm for the management of upper gastrointestinal bleeding, adapted to the Canadian environment. METHODS: A multidisciplinary consensus group of 25 participants representing 11 national societies used a seven-step approach to develop recommendations according to accepted standards. Sources of data included narrative and systematic reviews as well as published and new meta-analyses. A small writing subgroup subsequently created the algorithm. RESULTS: Recommendations emphasize appropriate initial resuscitation of the patient and a multidisciplinary approach to clinical risk stratification that determines the need for early endoscopy. Early endoscopy allows safe and prompt discharge of selected patients classified as low risk. Endoscopic hemostasis is reserved for patients with high-risk endoscopic lesions. Although monotherapy with injection or thermal coagulation is effective, the combination is superior to either treatment alone. High-dose intravenous proton-pump inhibition is recommended in patients who have undergone successful endoscopic therapy. Routine second-look endoscopy is not recommended. Patients with upper gastrointestinal bleeding secondary to ulcer disease should be tested and treated for Helicobacter pylori infection. CONCLUSIONS: This algorithm should facilitate appropriate risk stratification, use of endoscopic therapy and the appropriate utilization of proton-pump inhibition to optimize the care of patients with upper gastrointestinal bleeding. The algorithm should be customized to the resources of individual medical centres. Its application should be studied with appropriate outcomes recorded and validation performed.

Algorithms↗

PubMed2002

Evaluation of adolescent statural growth in health and disease: reliability of assessment from height measurement series and development of an automated algorithm.

OBJECTIVES: The precise evaluation of adolescent growth spurt is necessary for numerous clinical research studies of growth disorders and treatments. The objectives of our study were: (1) to evaluate the reliability of clinicians' 'manual' evaluation of the adolescent growth spurt from a collected series of height data, and (2) to construct an automated algorithm to determine the duration of the two phases of growth in health and disease (spurt and final slow growth) independent of clinical pubertal stages. METHODS: One hundred and seventy-four growth curves of normally growing, GH-deficient and Turner's syndrome subjects were presented twice to 2 experienced clinicians. Disagreement between evaluations and clinicians were settled to obtain a 'consensual gold standard' evaluation versus which the algorithm was assessed. Kappa statistics and Bland-Altman analyses were used to evaluate the reliability and agreement of the evaluations. RESULTS: The reliability of 'manual' evaluation of adolescent growth spurt from collected series of height data appeared to be poor. Conversely, the developed algorithm is perfectly reliable and satisfactorily valid. Discrepancies with the clinical consensual gold standard were always fewer than the discrepancies between the expert clinicians, and were observed in similarly difficult curves. CONCLUSION: The developed algorithm may be useful for diverse clinical and biological research applications in children with growth disorders. This study also confirms the value of a comprehensive investigation of growth during adolescence independent of clinical staging.

Adolescent↗

PubMed2002

Backward Haplotype Transmission Association (BHTA) algorithm - a fast multiple-marker screening method.

The mapping of complex traits is one of the most important and central areas of human genetics today. Recent attention has been focused on genome scans using a large number of marker loci. Because complex traits are typically caused by multiple genes, the common approaches of mapping them by testing markers one after another fail to capture the substantial information of interactions among disease loci. Here we propose a backward haplotype transmission association (BHTA) algorithm to address this problem. The algorithm can administer a screening on any disease model when case-parent trio data are available. It identifies the important subset of an original larger marker set by eliminating the markers of least significance, one at a time, after a complete evaluation of its importance. In contrast with the existing methods, three major advantages emerge from this approach. First, it can be applied flexibly to arbitrary markers, regardless of their locations. Second, it takes into account haplotype information; it is more powerful in detecting the multifactorial traits in the presence of haplotypic association. Finally, the proposed method can potentially prove to be more efficient in future genomewide scans, in terms of greater accuracy of gene detection and substantially reduced number of tests required in scans. We illustrate the performance of the algorithm with several examples, including one real data set with 31 markers for a study on the Gilles de la Tourette syndrome. Detailed theoretical justifications are also included, which explains why the algorithm is likely to select the 'correct' markers.

Algorithms↗