9,862 research outputs found
GASP: gapped ancestral sequence prediction for proteins
No full textBackground: the prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments.Results: here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy.Conclusions: GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alik
Computational identification and analysis of protein short linear motifs
No full textShort linear motifs (SLiMs) in proteins can act as targets for proteolytic cleavage, sites of post-translational modification, determinants of sub-cellular localization, and mediators of protein-protein interactions. Computational discovery of SLiMs involves assembling a group of proteins postulated to share a potential motif, masking out residues less likely to contain such a motif, down-weighting shared motifs arising through common evolutionary descent, and calculation of statistical probabilities allowing for the multiple testing of all possible motifs. Much of the challenge for motif discovery lies in the assembly and masking of datasets of proteins likely to share motifs, since the motifs are typically short (between 3 and 10 amino acids in length), so that potential signals can be easily swamped by the noise of stochastically recurring motifs. Focusing on disordered regions of proteins, where SLiMs are predominantly found, and masking out non-conserved residues can reduce the level of noise but more work is required to improve the quality of high-throughput experimental datasets (e.g. of physical protein interactions) as input for computational discovery
Combined segregation and linkage analysis of Graves-disease with a thyroid autoantibody diathesis
No full textCombined segregation and linkage analysis is a powerful technique for modeling linkage to diseases whose etiology is more complex than the effect of a well-described single genetic locus and for investigating the influence of single genes on various aspects of the disease phenotype. Graves disease is familial and is associated with human leukocyte antigen (HLA) allele DR3. Probands with Graves disease, as well as close relatives, have raised levels of thyroid autoantibodies. This phenotypic information additional to affection status may be considered by the computer program COMDS for combined segregation and linkage analysis, when normals are classified into diathesis classes of increasing thyroid autoantibody titer. The ordinal model considers the cumulative odds of lying in successive classes, and a single additional parameter is introduced for each gene modeled. Distributional assumptions are avoided by providing estimates of the population frequencies of each class. Evidence for linkage was increased by considering the thyroid autoantibody diathesis and by testing two-locus models. The analysis revealed evidence for linkage to HLA-DR when the strong coupling of the linked locus to allele DR3 was considered (led score of 6.6). Linkage analysis of the residual variation revealed no evidence of linkage to Gm, but a suggestion of linkage to Km
Estimation and efficient computation of the true probability of recurrence of short linear protein sequence motifs in unrelated proteins.
No full textBackground: large datasets of protein interactions provide a rich resource for the discovery of Short Linear Motifs (SLiMs) that recur in unrelated proteins. However, existing methods for estimating the probability of motif recurrence may be biased by the size and composition of the search dataset, such that p-value estimates from different datasets, or from motifs containing different numbers of non-wildcard positions, are not strictly comparable. Here, we develop more exact methods and explore the potential biases of computationally efficient approximations. Results: a widely used heuristic for the calculation of motif over-representation approximates motif probability by assuming that all proteins have the same length and composition. We introduce pv, which calculates the probability exactly. Secondly, the recently introduced SLiMFinder statistic Sig, accounts for multiple testing (across all possible motifs) in motif discovery. However, it approximates the probability of all other possible motifs, occurring with a score of p or less, as being equal to p. Here, we show that the exhaustive calculation of the probability of all possible motif occurrences that are as rare or rarer than the motif of interest, Sig', may be carried out efficiently by grouping motifs of a common probability (i.e. those which have permuted orders of the same residues). Sig'v, which corrects both approximations, is shown to be uniformly distributed in a random dataset when searching for non-ambiguous motifs, indicating that it is a robust significance measure. Conclusions: a method is presented to compute exactly the true probability of a non-ambiguous short protein sequence motif, and the utility of an approximate approach for novel motif discovery across a large number of datasets is demonstrated
The electromagnetic performance of brushless permanent magnet DC motors - with particular reference to noise and vibration.
No full textA comprehensive analytical technique is developed for predicting the instantaneous
magnetic field distribution in radial-field, surface-mounted permanent magnet brushless DC
motors under any load condition and commutation strategy. It is based on a 2-dimensional
analysis in polar coordinates and accounts implicitly for the corresponding stator winding current
waveforms and the effect of stator slot openings. In addition, a 2-dimensional analytical method
for calculating the back-emf waveform is presented, whilst the analytical technique is applied to
the prediction of the cogging torque waveform and the calculation of the self- and
mutual-winding inductances.
Also developed and validated is an analytical model for predicting the steady-state dynamic
performance of a 3-phase brushless DC drive, by exploiting the periodicity in the stator winding
voltage and current waveforms, with due account of the influence of commutation events in the
inverter bridge, the back-emf waveform, current limiting, and commutation timing etc. The
model is developed further to couple with the motion equation of the rotor to enable the transient
and steady-state dynamic performance of brushless DC drives to be predicted.
The effect of end-shields on the vibrational behaviour of stators is investigated by the modem
modal analysis technique, and new formulae for the calculation of the acoustic power radiated
by a cylindrical stator of finite length, using an analytical method, are presented. A technique
which combines the finite element method and Fourier analysis to account for the effects of
end-shields on the acoustic radiation is developed, and the spherical acoustic radiation model of
motors has been improved by the application of finite elements. Finally, a systematic analytical
approach to the estimation and analysis of the acoustic noise from a radial-field, internal rotor,
brushless DC motor is presented
Common Mode Currents in DC Power Routers
No full textThe grid reinforcement and energy redirection needs have led to the emergence of Back-To-Back Voltage Source Converter (BTB-VSC) based dc power routers. This paper investigates the low frequency Common Mode Currents (CMCs) that arise in the system if the employed BTB-VSCs have an un-isolated ac path connected in parallel to their output ports. Simulation results are presented to show a sensitivity analysis of lower order harmonics in CMC with respect to the operating active and reactive power of the dc router, dc link voltage, link resistance, modulation method and pole capacitance. Experimental results are shared to show existance of lower order CMC in 3-wire ac link operating in parallel with the dc power router and these are mitigated using zero sequence controller
Modeling, Control, and Operation of an M-DAB DC-DC Converter for Interconnection of HVDC Grids
No full textFuture high-voltage direct-current (HVDC) networks based on voltage source converters (VSCs) will have different structures (asymmetric monopolar, bipolar, or symmetric monopolar), voltage levels, control, and protection schemes. Therefore, dc-dc converters are needed to interconnect those VSC-HVDC grids and several technical issues on their control and operational systems must be adequately addressed. A dc-dc converter based on a modular-dual active bridge (M-DAB) converter is suggested to reach a desirable interconnection of the HVDC grids and regulate power flow (PF) between them. A dynamic averaged model is proposed for the M-DAB converter and its stability is analyzed using the Lyapunov function. Moreover, a new local controller based on nonlinear control theory is proposed for the M-DAB. The new M-DAB local controller is integrated with the energy management system (EMS), by updating the PF equations, to create a complete control structure. Considering the CIGRE DCS3 HVDC test system and the studied M-DAB, static, dynamic simulation, and experimental studies are conducted and the dc-dc converter and the performance of the designed controllers and the EMS are examined and validated.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid
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