Phenotypic and genetic analysis of carcass quality of different breeds’ fatlings

Dissection and quantitative-genetic analysis of carcass quality was performed on 318 fatlings of 5 different pig breeds: German, Dutch and Belgian Landrace, Yorkshire and Hampshire. Significant fixed effects (sex and genotype) and regression effects (age and body weight at slaughter) were fitted in the statistical model. Genetic parameters were estimated using the restricted maximum likelihood (REML) procedure based on an animal model with multivariate analyses. Heritability estimates for carcass traits were moderate to high except for back weight and neck weight. Among most of the carcass quality traits, the midrange strong and very strong positive genetic and phenotypic correlations were established. The traits that were analyzed showed sufficient genetic variation, indicating that their improvement is possible through genetic selection. Genetic variability was stable and expressed and justified further genetic changes in the desired direction

Chromium content in the meat of male Saanen goat kids from Vojvodina (Northern Serbia)

Goats, the earliest ruminant to be domesticated, are traditional sources of meat, milk, fibre, leather, related products of animal origin and as draught and pack animals. Meat is the major product of the goat. Meat quality is the sum of all sensory, nutritive, technological and hygienic-toxicological factors of meat. The aims of this study were to investigate the chromium content of four different muscles (M. psoas major, M. longissimus dorsi, M. semimembranosus and M. triceps brachii) of Saanen goat male kids and to determine whether the chromium contents differed between the muscles. Chromium content was determined using inductively coupled plasma optical emission spectrometry (ICP-OES), after dry ashing mineralisation. The studied muscles did not significantly differ (P >0.05) with respect to chromium content. The chromium content ranged from 0.012 to 0.067 mg/100 g, with an average of 0.026 mg/100 g

Pros and cons of using a computer vision system for color evaluation of meat and meat products

The ability of a computer vision system to evaluate the color of meat and meat products was investigated by a comparison study with color measurements from a traditional colorimeter. Pros and cons of using a computer vision system for color evaluation of meat and meat products were evaluated. Statistical analysis revealed significant differences between the instrumental values in all three dimensions (L*, a*, b*) between the computer vision system and the colorimeter. The computer vision system-generated colors were perceived as being more similar to the sample of the meat products visualized on the monitor, compared to colorimeter-generated colors in all (100%) individual trials performed. The use of the computer vision system is, therefore, considered a superior and less expensive alternative to the traditional method for measuring color of meat and meat products. The disadvantages of the computer vision system are its size, which makes it stationary, and the lack of official manufacturers that can provide ready-to-use systems. This type of computerized system still demands experts for its assembly and utilization

Transcription factor site dependencies in human, mouse and rat genomes

<p>Abstract</p> <p>Background</p> <p>It is known that transcription factors frequently act together to regulate gene expression in eukaryotes. In this paper we describe a computational analysis of transcription factor site dependencies in human, mouse and rat genomes.</p> <p>Results</p> <p>Our approach for quantifying tendencies of transcription factor binding sites to co-occur is based on a binding site scoring function which incorporates dependencies between positions, the use of information about the structural class of each transcription factor (major/minor groove binder), and also considered the possible implications of varying GC content of the sequences. Significant tendencies (dependencies) have been detected by non-parametric statistical methodology (permutation tests). Evaluation of obtained results has been performed in several ways: reports from literature (many of the significant dependencies between transcription factors have previously been confirmed experimentally); dependencies between transcription factors are not biased due to similarities in their DNA-binding sites; the number of dependent transcription factors that belong to the same functional and structural class is significantly higher than would be expected by chance; supporting evidence from GO clustering of targeting genes. Based on dependencies between two transcription factor binding sites (second-order dependencies), it is possible to construct higher-order dependencies (networks). Moreover results about transcription factor binding sites dependencies can be used for prediction of groups of dependent transcription factors on a given promoter sequence. Our results, as well as a scanning tool for predicting groups of dependent transcription factors binding sites are available on the Internet.</p> <p>Conclusion</p> <p>We show that the computational analysis of transcription factor site dependencies is a valuable complement to experimental approaches for discovering transcription regulatory interactions and networks. Scanning promoter sequences with dependent groups of transcription factor binding sites improve the quality of transcription factor predictions.</p

An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs

Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account. However, this remains a challenging task owing to the fact that sequences similar to those of known TFBSs can occur by chance with a relatively high frequency. Here we present a new method for matching sequences to TFBS motifs based on intuitionistic fuzzy sets (IFS) theory, an approach that has been shown to be particularly appropriate for tackling problems that embody a high degree of uncertainty. Results: We propose SCintuit, a new scoring method for measuring sequence-motif affinity based on IFS theory. Unlike existing methods that consider dependencies between positions, SCintuit is designed to prevent overestimation of less conserved positions of TFBSs. For a given pair of bases, SCintuit is computed not only as a function of their combined probability of occurrence, but also taking into account the individual importance of each single base at its corresponding position. We used SCintuit to identify known TFBSs in DNA sequences. Our method provides excellent results when dealing with both synthetic and real data, outperforming the sensitivity and the specificity of two existing methods in all the experiments we performed. Conclusions: The results show that SCintuit improves the prediction quality for TFs of the existing approaches without compromising sensitivity. In addition, we show how SCintuit can be successfully applied to real research problems. In this study the reliability of the IFS theory for motif discovery tasks is proven

A selected bibliography on parameter optimization methods suitable for hybrid computation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68333/2/10.1177_003754976700800610.pd

N-gram analysis of 970 microbial organisms reveals presence of biological language models

<p>Abstract</p> <p>Background</p> <p>It has been suggested previously that genome and proteome sequences show characteristics typical of natural-language texts such as "signature-style" word usage indicative of authors or topics, and that the algorithms originally developed for natural language processing may therefore be applied to genome sequences to draw biologically relevant conclusions. Following this approach of 'biological language modeling', statistical n-gram analysis has been applied for comparative analysis of whole proteome sequences of 44 organisms. It has been shown that a few particular amino acid n-grams are found in abundance in one organism but occurring very rarely in other organisms, thereby serving as genome signatures. At that time proteomes of only 44 organisms were available, thereby limiting the generalization of this hypothesis. Today nearly 1,000 genome sequences and corresponding translated sequences are available, making it feasible to test the existence of biological language models over the evolutionary tree.</p> <p>Results</p> <p>We studied whole proteome sequences of 970 microbial organisms using n-gram frequencies and cross-perplexity employing the Biological Language Modeling Toolkit and Patternix Revelio toolkit. Genus-specific signatures were observed even in a simple unigram distribution. By taking statistical n-gram model of one organism as reference and computing cross-perplexity of all other microbial proteomes with it, cross-perplexity was found to be predictive of branch distance of the phylogenetic tree. For example, a 4-gram model from proteome of <it>Shigellae flexneri 2a</it>, which belongs to the <it>Gammaproteobacteria </it>class showed a self-perplexity of 15.34 while the cross-perplexity of other organisms was in the range of 15.59 to 29.5 and was proportional to their branching distance in the evolutionary tree from <it>S. flexneri</it>. The organisms of this genus, which happen to be pathotypes of <it>E.coli</it>, also have the closest perplexity values with <it>E. coli.</it></p> <p>Conclusion</p> <p>Whole proteome sequences of microbial organisms have been shown to contain particular n-gram sequences in abundance in one organism but occurring very rarely in other organisms, thereby serving as proteome signatures. Further it has also been shown that perplexity, a statistical measure of similarity of n-gram composition, can be used to predict evolutionary distance within a genus in the phylogenetic tree.</p

Cardiopoietic cell therapy for advanced ischemic heart failure: results at 39 weeks of the prospective, randomized, double blind, sham-controlled CHART-1 clinical trial

Cardiopoietic cells, produced through cardiogenic conditioning of patients' mesenchymal stem cells, have shown preliminary efficacy. The Congestive Heart Failure Cardiopoietic Regenerative Therapy (CHART-1) trial aimed to validate cardiopoiesis-based biotherapy in a larger heart failure cohort