Conclusions:
Our approach combines dynamic modeling using differential equations with a stochastic learning framework, thus bridging the gap between biophysical modeling and stochastic inference approaches. Results show that the method can reap the advantages of both worlds, and allows the reconstruction of biophysically accurate dynamic models from noisy data. In addition, the stochastic learning framework used permits the computation of probability distributions over models and model parameters, which holds interesting prospects for experimental design purposes. (Source: BMC Bioinformatics – Latest articles)

Deoxyhypusine synthase, an NAD+-dependent enzyme, catalyzes the first step in the post-translational synthesis of an unusual amino acid, hypusine (N-(4-amino-2-hydroxybutyl)lysine), in the eukaryotic initiation factor 5A precursor protein. Two putative deoxyhypusine synthase (DHS) sequences have been identified in the Leishmania donovani genome, which are present on chromosomes 20: DHSL20 (DHS-like gene from chromosome 20) and DHS34 (DHS from chromosome 34). Although both sequences exhibit an overall conservation of key residues, DHSL20 protein lacks a critical lysine residue, and the recombinant protein showed no DHS activity in vitro. However, DHS34 contains the critical lysine residue, and the recombinant DHS34 effectively catalyzed deoxyhypusine synthesis. Furthermore, in vivo labeling…

This study illustrates the complexity of the EGFR-associated interactome and identifies protein acetylation as a previously unknown regulator of receptor endocytosis and degradation.
PMID: 20029029 [PubMed - in process] (Source: Science Signaling)

(Source: PLoS Computational Biology)

Conclusions:
Employing SPs for predicting enzymatic activity of proteins works well once one utilizes coverage-length criteria. In our analysis, L[greater than or equal to]7 has led to highly accurate results. (Source: BMC Bioinformatics – Latest articles)

Conclusion:
The method offers a promising approach as a lipocalin prediction tool, complementing PROSITE, Pfam and homology modelling methods. (Source: BMC Bioinformatics – Latest articles)div id=medwormpbiMedWorm Message:/i/b Get the very latest Swine Flu news via the MedWorm ba href=http://www.medworm.com/rss/search.php?qu=%2Bswine+%2B%28influenza+flu%29t=Swine+Fluf=infectiousdiseasesr=Anyo=d target =_selfSwine Flu RSS news feed/a/b – updated hourly from thousands of authoritative health and news sources./p/div

Non-coding DNA, particularly intronic DNA, harbors important functional elements that affect gene expression and RNA splicing. Yet, it is unclear which specific non-coding sites are essential for gene function and regulation. To identify functional elements in non-coding DNA, we characterized genetic variation within introns using ethnically diverse human polymorphism data from three public databases, PMT, NIEHS, and Seattle SNPs. We demonstrate that positions within introns corresponding to known functional elements involved in pre-mRNA splicing, including the branch site, splice sites, and polypyrimidine tract show reduced levels of genetic variation. Additionally, we observed regions of reduced genetic variation that are candidates for distance dependent localization sites of functional…

Conclusion:
Based on our results and those discussed in the literature we conclude that the generalised binomial and Stouffer’s Z procedures should be preferred and Z when the number of tests is very small. The more conservative SGM might still be appropriate for meta-analyses when a strong publication bias in favour of significant results is expected to inflate type 2 error. (Source: BMC Bioinformatics – Latest articles)