InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites

Summary: Recent studies have shown that the traditional position weight matrix model is often insufficient for modeling transcription factor binding sites, as intra-motif dependencies play a significant role for an accurate description of binding motifs. Here, we present the Java application InMoDe, a collection of tools for learning, leveraging and visualizing such dependencies of putative higher order. The distinguishing feature of InMoDe is a robust model selection from a class of parsimonious models, taking into account dependencies only if justified by the data while choosing for simplicity otherwise. Availability and Implementation: InMoDe is implemented in Java and is available as command line application, as application with a graphical user-interface, and as an integration into Galaxy on the project website at http://www.jstacs.de/index.php/InMoDe.Peer reviewe

A general approach for discriminative de-novo motif discovery from highthroughput data

De novo motif discovery has been an important challenge of bioinformatics for the past two decades. Since the emergence of high-throughput techniques like ChIP-seq, ChIP-exo and protein-binding microarrays (PBMs), the focus of de novo motif discovery has shifted to runtime and accuracy on large data sets. For this purpose, specialized algorithms have been designed for discovering motifs in ChIP-seq or PBM data. However, none of the existing approaches work perfectly for all three high-throughput techniques. In this article, we propose Dimont, a general approach for fast and accurate de novo motif discovery from high-throughput data. We demonstrate that Dimont yields a higher number of correct motifs from ChIP-seq data than any of the specialized approaches and achieves a higher accuracy for predicting PBM intensities from probe sequence than any of the approaches specifically designed for that purpose. Dimont also reports the expected motifs for several ChIP-exo data sets. Investigating differences between in vitro and in vivo binding, we find that for most transcription factors, the motifs discovered by Dimont are in good accordance between techniques, but we also find notable exceptions. We also observe that modeling intra-motif dependencies may increase accuracy, which indicates that more complex motif models are a worthwhile field of research

VOMBAT: prediction of transcription factor binding sites using variable order Bayesian trees

Variable order Markov models and variable order Bayesian trees have been proposed for the recognition of transcription factor binding sites, and it could be demonstrated that they outperform traditional models, such as position weight matrices, Markov models and Bayesian trees. We develop a web server for the recognition of DNA binding sites based on variable order Markov models and variable order Bayesian trees offering the following functionality: (i) given datasets with annotated binding sites and genomic background sequences, variable order Markov models and variable order Bayesian trees can be trained; (ii) given a set of trained models, putative DNA binding sites can be predicted in a given set of genomic sequences and (iii) given a dataset with annotated binding sites and a dataset with genomic background sequences, cross-validation experiments for different model combinations with different parameter settings can be performed. Several of the offered services are computationally demanding, such as genome-wide predictions of DNA binding sites in mammalian genomes or sets of 10(4)-fold cross-validation experiments for different model combinations based on problem-specific data sets. In order to execute these jobs, and in order to serve multiple users at the same time, the web server is attached to a Linux cluster with 150 processors. VOMBAT is available at

Prognostic Values of Tumor Necrosis Factor/Cachectin, Interleukin-l, Interferon-α, and Interferon-γ in the Serum of Patients with Septic Shock

Serum concentrations of immunoreactive tumor necrosis factor/cachectin (TNF), interleukin-1β (IL-1β), interferon-γ (IFNγ, and interferon-α (IFNα) were prospectively measured in 70 patients with septic shock to determine their evolution and prognostic values. In a univariate analysis, levels of TNF (P = .002) and IL-1β (P = .05) were associated with the patient's outcome, but not IFNα (P = .15) and IFNγ (P = .26). In contrast, in a stepwise logistic regression analysis, the severity of the underlying disease (P = .01), the age of the patient (P = .02), the documentation of infection (nonbacteremic infections vs. bacteremias, P = .03), the urine output (P = .04), and the arterial pH (P = .05) contributed more significantly to prediction of patient outcome than the serum levels of TNF (P = .07). After 10 days, the median concentration of TNF was undetectable <100 pg/ml) in the survivors, whereas it remained elevated (305 pg/ml, P = .002) in the nonsurvivors. Thus, in patients with septic shock due to various gram-negative bacteria, other parameters than the absolute serum concentration of immunoreactive TNF contributed significantly to the prediction of outcom

Assembling highly repetitive Xanthomonas TALomes using Oxford Nanopore sequencing

Background: Most plant-pathogenic Xanthomonas bacteria harbor transcription activator-like effector (TALE) genes, which function as transcriptional activators of host plant genes and support infection. The entire repertoire of up to 29 TALE genes of a Xanthomonas strain is also referred to as TALome. The DNA-binding domain of TALEs is comprised of highly conserved repeats and TALE genes often occur in gene clusters, which precludes the assembly of TALE-carrying Xanthomonas genomes based on standard sequencing approaches. Results: Here, we report the successful assembly of the 5 Mbp genomes of five Xanthomonas strains from Oxford Nanopore Technologies (ONT) sequencing data. For one of these strains, Xanthomonas oryzae pv. oryzae (Xoo) PXO35, we illustrate why Illumina short reads and longer PacBio reads are insufficient to fully resolve the genome. While ONT reads are perfectly suited to yield highly contiguous genomes, they suffer from a specific error profile within homopolymers. To still yield complete and correct TALomes from ONT assemblies, we present a computational correction pipeline specifically tailored to TALE genes, which yields at least comparable accuracy as Illumina-based polishing. We further systematically assess the ONT-based pipeline for its multiplexing capacity and find that, combined with computational correction, the complete TALome of Xoo PXO35 could have been reconstructed from less than 20,000 ONT reads. Conclusions: Our results indicate that multiplexed ONT sequencing combined with a computational correction of TALE genes constitutes a highly capable tool for characterizing the TALomes of huge collections of Xanthomonas strains in the future

Testing a digital level crossing warning system for road traffic users with a naturalistic driving study

The points where roads intersect with railroads, called level-crossings, have traditionally been considered dangerous due to the excessive severity of accidents that have occurred involving all kinds of road vehicles and trains. They are most frequently protected with regular safety systems like barriers of light signals, however numerous level-crossings still remain unprotected. In addition, the maintenance status of level crossings differs strongly across Europe. As a consequence, some level crossings pose serious safety threats to road- and rail users, if the level crossing safety infrastructure does not exist or is not properly maintained and operated. Especially at level crossings in urban areas of municipalities in developing countries in Europe, it is often overly costly or even impossible to protect a high number of level crossings and maintain them on a regular basis. Digitalization, the huge coverage of mobile telecommunications networks and the penetration of smart phones and mobile devices in society offer a starting point for alternative, hi tech safety measures, that promise to be cheap as well as effective. Such a system has been developed and tested in Thessaloniki, where a mobile device elicits an auditory as well as a visual warning whenever the user drives in close proximity and heading to any of the 30 level crossings located in the suburbs of the city. Some trains have also been equipped with Global Navigation Satellite System (GNSS) sensors which record and transmit highly accurate spatiotemporal data, so when they approach the level crossings the mobile users also receive the estimated time of arrival on their smart phones and tablets. Three taxis were equipped with a naturalistic driving platform, consisting of cameras and a GPS sensor, to track the behavior of the drivers whenever they approached level crossings. The equipment was installed taking into consideration both the safety of all passengers and the privacy of customers. Only the drivers and surroundings of the vehicles were recorded, for a prolonged period that lasted more than two months and resulted in more than 1TB of relevant video data for further analysis. During the first month the alert system was not activated, in order to collect baseline data. The safety relevant behavior of the drivers in the context of level crossings before the implementation of the assistance system was compared to their behavior when using the system