Combining comparative genomics with de novo motif discovery to identify human transcription factor DNA-binding motifs

BACKGROUND: As more and more genomes are sequenced, comparative genomics approaches provide a methodology for identifying conserved regulatory elements that may be involved in gene regulations. RESULTS: We developed a novel method to combine comparative genomics with de novo motif discovery to identify human transcription factor binding motifs that are overrepresented and conserved in the upstream regions of a set of co-regulated genes. The method is validated by analyzing a well-characterized muscle specific gene set, and the results showed that our approach performed better than the existing programs in terms of sensitivity and prediction rate. CONCLUSION: The newly developed method can be used to extract regulatory signals in co-regulated genes, which can be derived from the microarray clustering analysis

Finding regulatory elements and regulatory motifs: a general probabilistic framework

Over the last two decades a large number of algorithms has been developed for regulatory motif finding. Here we show how many of these algorithms, especially those that model binding specificities of regulatory factors with position specific weight matrices (WMs), naturally arise within a general Bayesian probabilistic framework. We discuss how WMs are constructed from sets of regulatory sites, how sites for a given WM can be discovered by scanning of large sequences, how to cluster WMs, and more generally how to cluster large sets of sites from different WMs into clusters. We discuss how 'regulatory modules', clusters of sites for subsets of WMs, can be found in large intergenic sequences, and we discuss different methods for ab initio motif finding, including expectation maximization (EM) algorithms, and motif sampling algorithms. Finally, we extensively discuss how module finding methods and ab initio motif finding methods can be extended to take phylogenetic relations between the input sequences into account, i.e. we show how motif finding and phylogenetic footprinting can be integrated in a rigorous probabilistic framework. The article is intended for readers with a solid background in applied mathematics, and preferably with some knowledge of general Bayesian probabilistic methods. The main purpose of the article is to elucidate that all these methods are not a disconnected set of individual algorithmic recipes, but that they are just different facets of a single integrated probabilistic theory

Subcutaneous dissociative conscious sedation (sDCS) an alternative method for airway regional blocks: a new approach

<p>Abstract</p> <p>Background</p> <p>Predicted difficult airway is a definite indication for awake intubation and spontaneous ventilation. Airway regional blocks which are commonly used to facilitate awake intubation are sometimes impossible or forbidden. On the other hand deep sedation could be life threatening in the case of compromised airway.</p> <p>The aim of this study is evaluating "Subcutaneous Dissociative Conscious Sedation" (sDCS) as an alternative method to airway regional blocks for awake intubation.</p> <p>Methods</p> <p>In this prospective, non-randomized study, 30 patients with predicted difficult airway (laryngeal tumors), who were scheduled for direct laryngoscopic biopsy (DLB), underwent "Subcutaneous Dissociative Conscious Sedation" (sDCS) exerted by intravenous fentanyl 3-4ug/kg and subcutaneous ketamine 0.6-0.7 mg/kg. The tongue and pharynx were anesthetized with lidocaine spray (4%<b>)</b>. 10 minutes after a subcutaneous injection of ketamine direct laryngoscopy was performed. Extra doses of fentanyl 50-100 ug were administered if the patient wasn't cooperative enough for laryngoscopy.</p> <p>Patients were evaluated for hemodynamic stability (heart rate and blood pressure), oxygen saturation (Spo₂), patient cooperation (obedient to open the mouth for laryngoscopy and the number of tries for laryngoscopy), patient comfort (remaining moveless), hallucination, nystagmus and salivation (need for aspiration before laryngoscopy).</p> <p>Results</p> <p>Direct laryngoscopy was performed successfully in all patients. One patient needed extra fentanyl and then laryngoscopy was performed successfully on the second try. All patients were cooperative enough during laryngoscopy. Hemodynamic changes more than 20% occurred in just one patient. Oxygen desaturation (spo₂< 90%) didn't occur in any patient.</p> <p>Conclusions</p> <p>Subcutaneous Dissociative Conscious Sedation (sDCS) as a new approach to airway is an acceptable and safe method for awake intubation and it can be suggested as a noninvasive substitute of low complication rate for regional airway blocks.</p> <p>Registration ID in IRCT</p> <p>IRCT201012075333N1</p

Theory of Multidimensional Solitons

We review a number of topics germane to higher-dimensional solitons in Bose-Einstein condensates. For dark solitons, we discuss dark band and planar solitons; ring dark solitons and spherical shell solitons; solitary waves in restricted geometries; vortex rings and rarefaction pulses; and multi-component Bose-Einstein condensates. For bright solitons, we discuss instability, stability, and metastability; bright soliton engineering, including pulsed atom lasers; solitons in a thermal bath; soliton-soliton interactions; and bright ring solitons and quantum vortices. A thorough reference list is included.Comment: review paper, to appear as Chapter 5a in "Emergent Nonlinear Phenomena in Bose-Einstein Condensates: Theory and Experiment," edited by P. G. Kevrekidis, D. J. Frantzeskakis, and R. Carretero-Gonzalez (Springer-Verlag

WeederH: an algorithm for finding conserved regulatory motifs and regions in homologous sequences

BACKGROUND: This work addresses the problem of detecting conserved transcription factor binding sites and in general regulatory regions through the analysis of sequences from homologous genes, an approach that is becoming more and more widely used given the ever increasing amount of genomic data available. RESULTS: We present an algorithm that identifies conserved transcription factor binding sites in a given sequence by comparing it to one or more homologs, adapting a framework we previously introduced for the discovery of sites in sequences from co-regulated genes. Differently from the most commonly used methods, the approach we present does not need or compute an alignment of the sequences investigated, nor resorts to descriptors of the binding specificity of known transcription factors. The main novel idea we introduce is a relative measure of conservation, assuming that true functional elements should present a higher level of conservation with respect to the rest of the sequence surrounding them. We present tests where we applied the algorithm to the identification of conserved annotated sites in homologous promoters, as well as in distal regions like enhancers. CONCLUSION: Results of the tests show how the algorithm can provide fast and reliable predictions of conserved transcription factor binding sites regulating the transcription of a gene, with better performances than other available methods for the same task. We also show examples on how the algorithm can be successfully employed when promoter annotations of the genes investigated are missing, or when regulatory sites and regions are located far away from the genes

RNAcontext: A New Method for Learning the Sequence and Structure Binding Preferences of RNA-Binding Proteins

Metazoan genomes encode hundreds of RNA-binding proteins (RBPs). These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures

Two-pion Bose-Einstein correlations in central Pb-Pb collisions at sNN\sqrt{s_{\rm NN}} = 2.76 TeV

The first measurement of two-pion Bose-Einstein correlations in central Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV at the Large Hadron Collider is presented. We observe a growing trend with energy now not only for the longitudinal and the outward but also for the sideward pion source radius. The pion homogeneity volume and the decoupling time are significantly larger than those measured at RHIC.Comment: 17 pages, 5 captioned figures, 1 table, authors from page 12, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/388

Suppression of charged particle production at large transverse momentum in central Pb-Pb collisions at sNN=2.76\sqrt{s_{\rm NN}} = 2.76 TeV

Inclusive transverse momentum spectra of primary charged particles in Pb-Pb collisions at $\sqrt{s_{_{\rm NN}}}$ = 2.76 TeV have been measured by the ALICE Collaboration at the LHC. The data are presented for central and peripheral collisions, corresponding to 0-5% and 70-80% of the hadronic Pb-Pb cross section. The measured charged particle spectra in $|\eta|<0.8$ and $0.3 < p_T < 20$ GeV/$c$ are compared to the expectation in pp collisions at the same $\sqrt{s_{\rm NN}}$, scaled by the number of underlying nucleon-nucleon collisions. The comparison is expressed in terms of the nuclear modification factor $R_{\rm AA}$. The result indicates only weak medium effects ($R_{\rm AA} \approx$ 0.7) in peripheral collisions. In central collisions, $R_{\rm AA}$ reaches a minimum of about 0.14 at $p_{\rm T}=6$-7GeV/$c$ and increases significantly at larger $p_{\rm T}$. The measured suppression of high-$p_{\rm T}$ particles is stronger than that observed at lower collision energies, indicating that a very dense medium is formed in central Pb-Pb collisions at the LHC.Comment: 15 pages, 5 captioned figures, 3 tables, authors from page 10, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/98

GRISOTTO: A greedy approach to improve combinatorial algorithms for motif discovery with prior knowledge

<p>Abstract</p> <p>Background</p> <p>Position-specific priors (PSP) have been used with success to boost EM and Gibbs sampler-based motif discovery algorithms. PSP information has been computed from different sources, including orthologous conservation, DNA duplex stability, and nucleosome positioning. The use of prior information has not yet been used in the context of combinatorial algorithms. Moreover, priors have been used only independently, and the gain of combining priors from different sources has not yet been studied.</p> <p>Results</p> <p>We extend RISOTTO, a combinatorial algorithm for motif discovery, by post-processing its output with a greedy procedure that uses prior information. PSP's from different sources are combined into a scoring criterion that guides the greedy search procedure. The resulting method, called GRISOTTO, was evaluated over 156 yeast TF ChIP-chip sequence-sets commonly used to benchmark prior-based motif discovery algorithms. Results show that GRISOTTO is at least as accurate as other twelve state-of-the-art approaches for the same task, even without combining priors. Furthermore, by considering combined priors, GRISOTTO is considerably more accurate than the state-of-the-art approaches for the same task. We also show that PSP's improve GRISOTTO ability to retrieve motifs from mouse ChiP-seq data, indicating that the proposed algorithm can be applied to data from a different technology and for a higher eukaryote.</p> <p>Conclusions</p> <p>The conclusions of this work are twofold. First, post-processing the output of combinatorial algorithms by incorporating prior information leads to a very efficient and effective motif discovery method. Second, combining priors from different sources is even more beneficial than considering them separately.</p