A novel and robust parameter training approach for HMMs under noisy and partial access to states

Cataloged from PDF version of article.This paper proposes a new estimation algorithm for the parameters of an HMM as to best account for the observed data. In this model, in addition to the observation sequence, we have partial and noisy access to the hidden state sequence as side information. This access can be seen as "partial labeling" of the hidden states. Furthermore, we model possible mislabeling in the side information in a joint framework and derive the corresponding EM updates accordingly. In our simulations, we observe that using this side information, we considerably improve the state recognition performance, up to 70%, with respect to the "achievable margin" defined by the baseline algorithms. Moreover, our algorithm is shown to be robust to the training conditions. (C) 2013 Elsevier B.V. All rights reserved

Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data

Summary: Here we present the open-source R/Bioconductor software package BEAT (BS-Seq Epimutation Analysis Toolkit). It implements all bioinformatics steps required for the quantitative high-resolution analysis of DNA methylation patterns from bisulfite sequencing data, including the detection of regional epimutation events, i.e. loss or gain of DNA methylation at CG positions relative to a reference. Using a binomial mixture model, the BEAT package aggregates methylation counts per genomic position, thereby compensating for low coverage, incomplete conversion and sequencing errors. Availability and implementation: BEAT is freely available as part of Bioconductor at www.bioconductor.org/packages/devel/bioc/html/BEAT.html. The package is distributed under the GNU Lesser General Public License 3.0. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Magnetic properties of triethylene glycol coated CoFe2O4 and Mn0.2Co0.8Fe2O4 NP's synthesized by polyol method

AbstractIn this study, we reported on the structural and magnetic properties of TEG-CoFe2O4 and TEG-Mn0.2Co0.8Fe2O4 nanocomposites produced by the glycothermal reaction (polyol). X-ray diffraction (XRD), transmission electron microscopy (TEM) and vibration sample magnetometer (VSM) analysis have been carried out in order to understand the effect of Mn2+ into CoFe2O4 and it was observed that the addition of Mn2+ tends to reduce the crystallite size, increase the ao (cell parameter) and increase the TB. The presence of adsorbed polyol entities on the surface of the CoFe2O4 and Mn0.2Co0.8Fe2O4 NP's was also proven by TG measurements. FT-IR analysis suggested the presence of adsorbed TEG molecules on the surface of CoFe2O4 and Mn0.2Co0.8Fe2O4 NP's

Probing Bottom-up Processing with Multistable Images

The selection of fixation targets involves a combination of top-down and bottom-up processing. The role of bottom-up processing can be enhanced by using multistable stimuli because their constantly changing appearance seems to depend predominantly on stimulusdriven factors. We used this approach to investigate whether visual processing models based on V1 need to be extended to incorporate specific computations attributed to V4. Eye movements of 8 subjects were recorded during free viewing of the Marroquin pattern in which illusory circles appear and disappear. Fixations were concentrated on features arranged in concentric rings within the pattern. Comparison with simulated fixation data demonstrated that the saliency of these features can be predicted with appropriate weighting of lateral connections in existing V1 models

Dizzy-Beats:a Bayesian Evidence analysis tool for systems biology

PublishedJournal ArticleResearch Support, Non-U.S. Gov'tMOTIVATION: Model selection and parameter inference are complex problems of long-standing interest in systems biology. Selecting between competing models arises commonly as underlying biochemical mechanisms are often not fully known, hence alternative models must be considered. Parameter inference yields important information on the extent to which the data and the model constrain parameter values. RESULTS: We report Dizzy-Beats, a graphical Java Bayesian evidence analysis tool implementing nested sampling - an algorithm yielding an estimate of the log of the Bayesian evidence Z and the moments of model parameters, thus addressing two outstanding challenges in systems modelling. A likelihood function based on the L1-norm is adopted as it is generically applicable to replicated time series data. AVAILABILITY AND IMPLEMENTATION: http://sourceforge.net/p/bayesevidence/home/Home/.BBSR

Simple sequence repeat-based assessment of genetic diversity in 'Dimrit' and 'Gemre' grapevine accessions from Turkey

It is widely believed that Turkey has played an important role in the evolution of modern day grapes due to its unique geographical location with close proximity to the regions of grape diversity. Despite this, the rich grape germplasm found in Turkey has not been sufficiently analyzed genetically. In this study, 31 grapevine accessions from 'Dimrit' (or 'Dilmit') and 'Gemre' grape groups were genetically analyzed at eight SSR (microsatellite) loci (VVS2, VVMD5, VVMD7, VVMD24, VVMD27, VVMD28, VrZAG62 and VrZAG79) and for a number of ampeolographic characteristics. These analyses identified sufficient genetic diversity between these two grape groups that, in general, clustered separately in the dendrogram constructed based on the SSR data. However, the ecogeographical distribution and genetic relationship of the genotypes did not show any significant correlation. Two 'Gemre' accessions were determined as genetically identical. In addition, one case of synonym and several cases of homonym genotypes were identified. The results reported here are important first steps towards better characterization of these grape genotypes and would aid future germplasm management and breeding efforts.