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PubMed2007

Support vector machine based training of multilayer feedforward neural networks as optimized by particle swarm algorithm: application in QSAR studies of bioactivity of organic compounds.

Multilayer feedforward neural networks (MLFNNs) are important modeling techniques widely used in QSAR studies for their ability to represent nonlinear relationships between descriptors and activity. However, the problems of overfitting and premature convergence to local optima still pose great challenges in the practice of MLFNNs. To circumvent these problems, a support vector machine (SVM) based training algorithm for MLFNNs has been developed with the incorporation of particle swarm optimization (PSO). The introduction of the SVM based training mechanism imparts the developed algorithm with inherent capacity for combating the overfitting problem. Moreover, with the implementation of PSO for searching the optimal network weights, the SVM based learning algorithm shows relatively high efficiency in converging to the optima. The proposed algorithm has been evaluated using the Hansch data set. Application to QSAR studies of the activity of COX-2 inhibitors is also demonstrated. The results reveal that this technique provides superior performance to backpropagation (BP) and PSO training neural networks.

Algorithms↗

PubMed2004

Autofocusing in computer microscopy: selecting the optimal focus algorithm.

Autofocusing is a fundamental technology for automated biological and biomedical analyses and is indispensable for routine use of microscopes on a large scale. This article presents a comprehensive comparison study of 18 focus algorithms in which a total of 139,000 microscope images were analyzed. Six samples were used with three observation methods (brightfield, phase contrast, and differential interference contrast (DIC)) under two magnifications (100x and 400x). A ranking methodology is proposed, based on which the 18 focus algorithms are ranked. Image preprocessing was also conducted to extensively reveal the performance and robustness of the focus algorithms. The presented guidelines allow for the selection of the optimal focus algorithm for different microscopy applications.

Algorithms↗

PubMed2006

Richardson-Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution.

Confocal laser scanning microscopy is a powerful and popular technique for 3D imaging of biological specimens. Although confocal microscopy images are much sharper than standard epifluorescence ones, they are still degraded by residual out-of-focus light and by Poisson noise due to photon-limited detection. Several deconvolution methods have been proposed to reduce these degradations, including the Richardson-Lucy iterative algorithm, which computes maximum likelihood estimation adapted to Poisson statistics. As this algorithm tends to amplify noise, regularization constraints based on some prior knowledge on the data have to be applied to stabilize the solution. Here, we propose to combine the Richardson-Lucy algorithm with a regularization constraint based on Total Variation, which suppresses unstable oscillations while preserving object edges. We show on simulated and real images that this constraint improves the deconvolution results as compared with the unregularized Richardson-Lucy algorithm, both visually and quantitatively.

Algorithms↗

PubMed2002

Direct reconstruction of MR images from data acquired on a non-Cartesian grid using an equal-phase-line algorithm.

The equal-phase line (EPL) algorithm is proposed as a means of allowing rapid Fourier transform (FT) reconstruction of MR image data acquired on a non-Cartesian grid. The pixels on the image are grouped according to their positions. The pixels in a group have the same phase in the complex exponential function -exp[j2pi(xu + yv)] and receive the same contribution from a data point. Each group is related to an EPL in the image space. The contribution of a data point can then be distributed to the pixels along the EPLs. The described EPL algorithm enables a decrease of the reconstruction time to about 40% of the direct FT (DrFT) for the non-Cartesian data. A numerical phantom and two sets of in vivo spiral data were used to investigate an optimal number of the EPLs and to measure the reconstruction time. The EPL algorithm runs nearly as fast as the look-up table (LUT) method (Dale et al. IEEE Trans Med Imaging 2001;20:207-217), but it does not require a large memory to store the coefficients in advance, as is required in the LUT method. Thus, the EPL algorithm can be used to reconstruct images up to 512 x 512 pixels in size in a PC of limited memory, and may be more conveniently applied to a multiprocessor system.

Algorithms↗

PubMed2001

k-Space weighted least-squares algorithm for accurate and fast motion extraction from magnetic resonance navigator echoes.

Navigator echoes provide an effective method to monitor physiological motion, allowing motion artifacts to be suppressed by modifying the data acquisition accordingly. The displacement can be measured directly from the navigator phase using an algorithm suggested by Ahn and Cho (IEEE Trans Med Imaging 1987;MI-6:32-36). Although computationally efficient, it is susceptible to noise, particularly contributions from points at the edges of k-space. A k-space weighted least-squares (kLS) algorithm is proposed which fits a straight line to the motion-induced phase shift. The linear fit is weighted strongly to high SNR points near the k-space center and only weakly to the poor SNR points at the edges of k-space. This algorithm was found to be as efficient as Ahn's algorithm but more robust against noise.

Algorithms↗

PubMed1993

Quantitative evaluation of several partial Fourier reconstruction algorithms used in MRI.

Partial Fourier reconstruction algorithms exploit the redundancy in magnetic resonance data sets so that half of the data is calculated during image reconstruction rather than acquired. The conjugate synthesis, Margosian, homodyne detection, Cuppen and POCS algorithms are evaluated using spatial frequency domain analysis to show their characteristics and where limitations may occur. The phase correction used in partial Fourier reconstruction is equivalent to a convolution in the frequency domain and the importance of accurately implementing this convolution is demonstrated. New reconstruction approaches, based on passing the partial data through a phase correcting, finite impulse response (FIR), digital filter are suggested. These FIR and MoFIR algorithms have a speed near that of the Margosian and homodyne detection reconstructions, but with a lower error; close to that of the Cuppen/POCS iterative approaches. Quantitative analysis of the partial Fourier algorithms, tested with three phase estimation techniques, are provided by comparing artificial and clinical data reconstructed using full and partial Fourier techniques.

Algorithms↗

PubMed2004

Removing the effect of SVD algorithmic artifacts present in quantitative MR perfusion studies.

Quantitative cerebral blood flow (CBF) values can be obtained from dynamic susceptibility contrast (DSC) MR perfusion studies using the standard singular value decomposition (sSVD) deconvolution algorithm. Reports in the literature from simulation and in vivo studies suggest that CBF estimates obtained using sSVD deconvolution depend on the arterial-tissue delay (ATD). By contrast, Fourier transform (FT) deconvolution produces CBF estimates that are independent of ATD. The diagnostic reliability of quantitative CBF measurements to define areas of normal tissue flow and tissue at risk is brought into doubt by such gross sensitivity to the specifics of the deconvolution approach. This variation of CBF values with ATD is shown to be an artifact associated with the current implementation of the sSVD deconvolution algorithm. A reformulated version of the SVD deconvolution algorithm (rSVD) is presented and compared to the standard SVD algorithm through simulation and patient case studies.

Algorithms↗

PubMed2006

Automatic algorithm for correcting motion artifacts in time-resolved two-dimensional magnetic resonance angiography using convex projections.

Time-resolved contrast enhanced magnetic resonance angiography (MRA) may suffer from involuntary patient motion. It is noted that while MR signal change associated with motion is large in magnitude and has smooth phase variation in k-phase, signal change associated with vascular enhancement is small in magnitude and has rapid phase variation in k-space. Based upon this observation, a novel projection onto convex sets (POCS) algorithm is developed as an automatic iterative method to remove motion artifacts. The presented POCS algorithm consists of high-pass phase filtering and convex projections in both k-space and image space. Without input of detailed motion knowledge, motion effects are filtered out, while vasculature information is preserved. The proposed method can be effective for a large class of nonrigid motions, including through-plane motion. The algorithm is stable and converges quickly, usually within five iterations. A double-blind evaluation on a set of clinical MRA cases shows that a completely unsupervised version of the algorithm produces significantly better rank scores (P=0.038) when compared to angiograms produced manually by an experienced radiologist.

Algorithms↗

PubMed2006

Comparison of three algorithms for multi-motor unit detection and waveform marking.

Quantitative EMG (QEMG) techniques include automated motor unit action potential (MUAP) detection and marking of clinically useful waveform metrics. Different computer algorithms are available on modern EMG machines to perform these operations rapidly. However, the efficiency and accuracy of available algorithms are rarely directly compared. We have assessed three commercially available algorithms using both synthesized and biologic interference patterns and found differences among algorithms, some of which are clinically significant. Our results point out the importance of assessing for duplicate MUAPs (same waveform detected as two separate waveforms) and accuracy of markings used to determine MUAP metrics.

Action Potentials↗

PubMed2002

A first trimester trisomy 13/trisomy 18 risk algorithm combining fetal nuchal translucency thickness, maternal serum free beta-hCG and PAPP-A.

This study examines 45 cases of trisomy 13 and 59 cases of trisomy 18 and reports an algorithm to identify pregnancies with a fetus affected by trisomy 13 or 18 by a combination of maternal age fetal nuchal translucency (NT) thickness, and maternal serum free beta-hCG and PAPP-A at 11-14 weeks of gestation. In this mixed trisomy group the median MoM NT was increased at 2.819, whilst the median MoMs for free beta-hCG and PAPP-A were reduced at 0.375 and 0.201 respectively. We predict that with the use of the combined trisomy 13 and 18 algorithm and a risk cut-off of 1 in 150 will for a 0.3% false positive rate allow 95% of these chromosomal defects to be identified at 11-14 weeks. Such algorithms will enhance existing first trimester screening algorithms for trisomy 21.

Algorithms↗

PubMed2005

Protein and peptide identification algorithms using MS for use in high-throughput, automated pipelines.

Current proteomics experiments can generate vast quantities of data very quickly, but this has not been matched by data analysis capabilities. Although there have been a number of recent reviews covering various aspects of peptide and protein identification methods using MS, comparisons of which methods are either the most appropriate for, or the most effective at, their proposed tasks are not readily available. As the need for high-throughput, automated peptide and protein identification systems increases, the creators of such pipelines need to be able to choose algorithms that are going to perform well both in terms of accuracy and computational efficiency. This article therefore provides a review of the currently available core algorithms for PMF, database searching using MS/MS, sequence tag searches and de novo sequencing. We also assess the relative performances of a number of these algorithms. As there is limited reporting of such information in the literature, we conclude that there is a need for the adoption of a system of standardised reporting on the performance of new peptide and protein identification algorithms, based upon freely available datasets. We go on to present our initial suggestions for the format and content of these datasets.

Algorithms↗

PubMed2006

Modifications to HEDIS and CSTE algorithms improve case recognition of pediatric asthma.

Our objective was to validate the Council of State and Territorial Epidemiologists (CSTE) definition of "probable" asthma and the Health Plan Employer Data and Information Set (HEDIS) definition of persistent asthma for diagnosis of pediatric asthma, and examine modifications that improve case recognition. CSTE and HEDIS criteria were applied to a cross-sectional study of 3,905 Medicaid children with physician-confirmed diagnosis of asthma/no asthma using a validated survey instrument based upon National Asthma Education and Prevention Program (NAEPP) Guidelines. Modified criteria were applied to another group of 1,458 non-Medicaid children from a managed care organization (MCO). Of 1,852 Medicaid children with physician-confirmed asthma, 906 had persistent asthma. CSTE identified 61% of children with "probable" asthma; HEDIS identified 44% of children with persistent asthma. Correct identification increased with greater disease severity. A modified CSTE increased sensitivity from 0.61 to 0.90, while maintaining high specificity. Three new HEDIS algorithms increased sensitivity from 0.44 to >0.84, with specificity >0.89. When applied prospectively to MCO children, these new algorithms demonstrated improved sensitivity. In conclusion, studies using current CSTE or HEDIS algorithms for case recognition underestimate asthma prevalence and overestimate asthma severity in children. Modified algorithms improve the identification of "probable" and persistent asthma.

Adolescent↗

PubMed1995

Continuous and discontinuous domains: an algorithm for the automatic generation of reliable protein domain definitions.

An algorithm is presented for the fast and accurate definition of protein structural domains from coordinate data without prior knowledge of the number or type of domains. The algorithm explicitly locates domains that comprise one or two continuous segments of protein chain. Domains that include more than two segments are also located. The algorithm was applied to a nonredundant database of 230 protein structures and the results compared to domain definitions obtained from the literature, or by inspection of the coordinates on molecular graphics. For 70% of the proteins, the derived domains agree with the reference definitions, 18% show minor differences and only 12% (28 proteins) show very different definitions. Three screens were applied to identify the derived domains least likely to agree with the subjective definition set. These screens revealed a set of 173 proteins, 97% of which agree well with the subjective definitions. The algorithm represents a practical domain identification tool that can be run routinely on the entire structural database. Adjustment of parameters also allows smaller compact units to be identified in proteins.

Actins↗

PubMed2002

Combining the GOR V algorithm with evolutionary information for protein secondary structure prediction from amino acid sequence.

We have modified and improved the GOR algorithm for the protein secondary structure prediction by using the evolutionary information provided by multiple sequence alignments, adding triplet statistics, and optimizing various parameters. We have expanded the database used to include the 513 non-redundant domains collected recently by Cuff and Barton (Proteins 1999;34:508-519; Proteins 2000;40:502-511). We have introduced a variable size window that allowed us to include sequences as short as 20-30 residues. A significant improvement over the previous versions of GOR algorithm was obtained by combining the PSI-BLAST multiple sequence alignments with the GOR method. The new algorithm will form the basis for the future GOR V release on an online prediction server. The average accuracy of the prediction of secondary structure with multiple sequence alignment and full jack-knife procedure was 73.5%. The accuracy of the prediction increases to 74.2% by limiting the prediction to 375 (of 513) sequences having at least 50 PSI-BLAST alignments. The average accuracy of the prediction of the new improved program without using multiple sequence alignments was 67.5%. This is approximately a 3% improvement over the preceding GOR IV algorithm (Garnier J, Gibrat JF, Robson B. Methods Enzymol 1996;266:540-553; Kloczkowski A, Ting K-L, Jernigan RL, Garnier J. Polymer 2002;43:441-449). We have discussed alternatives to the segment overlap (Sov) coefficient proposed by Zemla et al. (Proteins 1999;34:220-223).

Algorithms↗

PubMed2004

A pharmacophore docking algorithm and its application to the cross-docking of 18 HIV-NNRTI's in their binding pockets.

The docking of small molecules into the binding site of a target protein is an important but difficult step in structure-based drug design. The performance of a docking algorithm is usually evaluated by re-docking ligands into their native binding sites. We have explored the cross-docking of 18 HIV-NNRTIs (non-nucleoside inhibitors of HIV reverse transcriptase) of which the ligand-protein structure has been determined: each of the 18 ligands was docked into each of the 18 binding sites. The docking algorithms studied are an energy-based simulated annealing algorithm and a novel pharmacophore docking algorithm. It turns out that the energy-based docking of the ligands into non-native pockets is far less successful than the docking into their native pockets. The results can be improved by using explicit pharmacophore information, and by docking a ligand into a panel of protein structures and selecting the ligand-protein combination with the lowest interaction energy as the final result.

Algorithms↗

PubMed2005

Clustering algorithms for identifying core atom sets and for assessing the precision of protein structure ensembles.

An important open question in the field of NMR-based biomolecular structure determination is how best to characterize the precision of the resulting ensemble of structures. Typically, the RMSD, as minimized in superimposing the ensemble of structures, is the preferred measure of precision. However, the presence of poorly determined atomic coordinates and multiple "RMSD-stable domains"--locally well-defined regions that are not aligned in global superimpositions--complicate RMSD calculations. In this paper, we present a method, based on a novel, structurally defined order parameter, for identifying a set of core atoms to use in determining superimpositions for RMSD calculations. In addition we present a method for deciding whether to partition that core atom set into "RMSD-stable domains" and, if so, how to determine partitioning of the core atom set. We demonstrate our algorithm and its application in calculating statistically sound RMSD values by applying it to a set of NMR-derived structural ensembles, superimposing each RMSD-stable domain (or the entire core atom set, where appropriate) found in each protein structure under consideration. A parameter calculated by our algorithm using a novel, kurtosis-based criterion, the epsilon-value, is a measure of precision of the superimposition that complements the RMSD. In addition, we compare our algorithm with previously described algorithms for determining core atom sets. The methods presented in this paper for biomolecular structure superimposition are quite general, and have application in many areas of structural bioinformatics and structural biology.

Algorithms↗

PubMed2006

Physicochemical descriptors to discriminate protein-protein interactions in permanent and transient complexes selected by means of machine learning algorithms.

Analyzing protein-protein interactions at the atomic level is critical for our understanding of the principles governing the interactions involved in protein-protein recognition. For this purpose, descriptors explaining the nature of different protein-protein complexes are desirable. In this work, the authors introduced Epic Protein Interface Classification as a framework handling the preparation, processing, and analysis of protein-protein complexes for classification with machine learning algorithms. We applied four different machine learning algorithms: Support Vector Machines, C4.5 Decision Trees, K Nearest Neighbors, and Naïve Bayes algorithm in combination with three feature selection methods, Filter (Relief F), Wrapper, and Genetic Algorithms, to extract discriminating features from the protein-protein complexes. To compare protein-protein complexes to each other, the authors represented the physicochemical characteristics of their interfaces in four different ways, using two different atomic contact vectors, DrugScore pair potential vectors and SFCscore descriptor vectors. We classified two different datasets: (A) 172 protein-protein complexes comprising 96 monomers, forming contacts enforced by the crystallographic packing environment (crystal contacts), and 76 biologically functional homodimer complexes; (B) 345 protein-protein complexes containing 147 permanent complexes and 198 transient complexes. We were able to classify up to 94.8% of the packing enforced/functional and up to 93.6% of the permanent/transient complexes correctly. Furthermore, we were able to extract relevant features from the different protein-protein complexes and introduce an approach for scoring the importance of the extracted features.

Algorithms↗

PubMed2003

Application of the StrOligo algorithm for the automated structure assignment of complex N-linked glycans from glycoproteins using tandem mass spectrometry.

Oligosaccharides associated with proteins are known to give these molecules specific conformations and functions. Analysis of proteins would not be complete without studying the glycans. However, high-throughput techniques in proteomics will soon overwhelm the current capacity of methods if no automation is incorporated into glycomics. New capabilities of the StrOligo algorithm introduced for this purpose (Ethier et al., Rapid Commun. Mass Spectrom., 2002; 16: 1743) will be discussed here. Experimental tandem mass spectra were acquired to test the algorithm using a hybrid quadrupole-time-of-flight (QqTOF) instrument with a matrix-assisted laser desorption/ionization (MALDI) source. The samples were N-linked oligosaccharides from monoclonal antibody IgG, beta interferon and fetuin, detached by enzymatic deglycosylation and labeled at the reducing end. Improvements to the program were made in order to reduce the need for user intervention. StrOligo strips the spectra down to monoisotopic peaks only. The algorithm first builds a relationship tree, accounting for each observed loss of a monosaccharide moiety, and then analyzes the tree and proposes possible structures from combinations of adducts and fragment ion types. A score, which reflects agreement with experimental results, is then given to each proposed structure. The program then decides which combination is the best one and labels relevant peaks in the experimental mass spectrum using a modified nomenclature. The usefulness of the algorithm has been demonstrated by assigning structures to several glycans released from glycoproteins. The analysis was completed in less than 2 minutes for any glycan, which is a substantial improvement over manual interpretation.

Algorithms↗