CircNetVis: an interactive web application for visualizing interaction networks of circular RNAs.

Analyzing the interactions of circular RNAs (circRNAs) is a crucial step in understanding their functional impacts. While there are numerous visualization tools available for investigating circRNA interaction networks, these tools are typically limited to known circRNAs from specific databases. Moreover, these existing tools usually require complex installation procedures which can be time-consuming and challenging for users. There is a lack of a user-friendly web application that facilitates interactive exploration and visualization of circRNA interaction networks. CircNetVis is an interactive online web application to enhance the analysis of human/mouse circRNA interactions. The tool allows three different input formats of circRNAs including circRNA IDs from CircBase, circRNA coordinates (chromosome, start position, end position), and circRNA sequences in the FASTA format. It integrates multiple interaction networks for visualization and investigation of the interplay between circRNA, microRNAs, mRNAs and RNA binding proteins. CircNetVis also enables users to interactively explore the interactions of unknown circRNAs which are not reported from previous databases. The tool can generate interactive plots and allows users to save results as output files for offline usage. CircNetVis is implemented as a web application using R-shiny and freely available for academic use at https://www.meb.ki.se/shiny/truvu/CircNetVis/ .

Circall: fast and accurate methodology for discovery of circular RNAs from paired-end RNA-sequencing data.

BACKGROUND: Circular RNA (circRNA) is an emerging class of RNA molecules attracting researchers due to its potential for serving as markers for diagnosis, prognosis, or therapeutic targets of cancer, cardiovascular, and autoimmune diseases. Current methods for detection of circRNA from RNA sequencing (RNA-seq) focus mostly on improving mapping quality of reads supporting the back-splicing junction (BSJ) of a circRNA to eliminate false positives (FPs). We show that mapping information alone often cannot predict if a BSJ-supporting read is derived from a true circRNA or not, thus increasing the rate of FP circRNAs. RESULTS: We have developed Circall, a novel circRNA detection method from RNA-seq. Circall controls the FPs using a robust multidimensional local false discovery rate method based on the length and expression of circRNAs. It is computationally highly efficient by using a quasi-mapping algorithm for fast and accurate RNA read alignments. We applied Circall on two simulated datasets and three experimental datasets of human cell-lines. The results show that Circall achieves high sensitivity and precision in the simulated data. In the experimental datasets it performs well against current leading methods. Circall is also substantially faster than the other methods, particularly for large datasets. CONCLUSIONS: With those better performances in the detection of circRNAs and in computational time, Circall facilitates the analyses of circRNAs in large numbers of samples. Circall is implemented in C++ and R, and available for use at https://www.meb.ki.se/sites/biostatwiki/circall and https://github.com/datngu/Circall.

Radical Scavenging Activity of Natural-Based Cassaine Diterpenoid Amides and Amines.

The radical scavenging capacities of four new cassaine diterpenoid amides including 3ß-hydroxydinorerythrosuamide (1), 3ß-acetoxydinorerythrosuamide (2), 3ß-tigloyloxydinorerythrosuamide (3), and 6α-hydroxydinorcassamide (4) present in leaf extract and four new cassaine diterpenoid amines namely erythroformine A (5), erythroformine B (6), 6α-hydroxy-nor-cassamine (7), and nor-erythrosuamine (8) recently identified in the extract of the bark of Erythrophleum fordii were elucidated using density functional theory (DFT) method. Different thermochemical properties characterizing antioxidant potential including bond dissociation enthalpy (BDE), proton affinity (PA), and adiabatic ionization potential (IP) were calculated at the B3LYP/6-311G(d,p) level of theory. Scavenging reaction mechanisms of cassaine diterpenes toward HOO• radical including formal hydrogen transfer (FHT; either hydrogen atom transfer (HAT) or proton coupled electron transfer (PCET)), radical adduct formation (RAF), single electron transfer (SET), and proton transfer (PT) were studied in the gas phase, water, and benzene. The potential energy profiles and kinetic calculations for the FHT and RAF reactions were calculated at 298.15 K. The results showed that all the studied compounds present strong antioxidant activity via HAT mechanism with BDEs varying from 69.4 to 77.9 kcal/mol. While solvents have only a slight effect on HAT and RAF mechanisms, SET and PT reactions are likely to occur in polar media. Among the studied compounds, 3 is the most reactive one both for HAT (H-abstraction at C7, Δ H -11.3 kcal/mol) and for RAF (radical addition at C13 = C15 bond, Δ H -5.2 kcal/mol) reactions. The rate constants of these reactions are also comparable with several referenced antioxidants such as Trolox and ascorbic acid.

Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones.

In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS), that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers' vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features) as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine) contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97.33% that is considerably higher than that of the state-of the art.

Effect of temperature & salt concentration on salt tolerant nitrate-perchlorate reducing bacteria: Nitrate degradation kinetics.

The sustainability of nitrate-contaminated water treatment using ion-exchange processes can be achieved by regenerating the exhausted resin several times. Our previous study shows that the use of multi-cycle bioregeneration of resin enclosed in membrane is an effective and innovative regeneration method. In this research, the effects of two independent factors (temperature and salt concentration) on the biological denitrification rate were studied. The results of this research along with the experimental results of the previous study on the effect of the same factors on nitrate desorption rate from the resin allow the optimization of the bioregeneration process. The results of nitrate denitrification rate study show that the biodegradation rate at different temperature and salt concentration is independent of the initial nitrate concentration. At each specific salt concentration, the nitrate removal rate increased with increasing temperature with the average value of 0.001110 ± 0.0000647 mg-nitrate/mg-VSS.h.°C. However, the effect of different salt concentrations was dependent on the temperature; there is a significant interaction between salt concentration and temperature; within each group of temperatures, the nitrate degradation rate decreased with increasing the salt concentration. The temperature affected the tolerance to salinity and culture was less tolerant to high concentration of salt at low temperature. Evidenced by the difference between the minimum and maximum nitrate degradation rate being greater at lower temperature. At 35 °C, a 32% reduction in the nitrate degradation rate was observed while at 12 °C this reduction was 69%. This is the first published study to examine the interaction of salt concentration and temperature during biological denitrification.

Support measures to estimate the reliability of evolutionary events predicted by reconciliation methods.

The genome content of extant species is derived from that of ancestral genomes, distorted by evolutionary events such as gene duplications, transfers and losses. Reconciliation methods aim at recovering such events and at localizing them in the species history, by comparing gene family trees to species trees. These methods play an important role in studying genome evolution as well as in inferring orthology relationships. A major issue with reconciliation methods is that the reliability of predicted evolutionary events may be questioned for various reasons: Firstly, there may be multiple equally optimal reconciliations for a given species tree-gene tree pair. Secondly, reconciliation methods can be misled by inaccurate gene or species trees. Thirdly, predicted events may fluctuate with method parameters such as the cost or rate of elementary events. For all of these reasons, confidence values for predicted evolutionary events are sorely needed. It was recently suggested that the frequency of each event in the set of all optimal reconciliations could be used as a support measure. We put this proposition to the test here and also consider a variant where the support measure is obtained by additionally accounting for suboptimal reconciliations. Experiments on simulated data show the relevance of event supports computed by both methods, while resorting to suboptimal sampling was shown to be more effective. Unfortunately, we also show that, unlike the majority-rule consensus tree for phylogenies, there is no guarantee that a single reconciliation can contain all events having above 50% support. In this paper, we detail how to rely on the reconciliation graph to efficiently identify the median reconciliation. Such median reconciliation can be found in polynomial time within the potentially exponential set of most parsimonious reconciliations.

Reconciliation and local gene tree rearrangement can be of mutual profit.

BACKGROUND: Reconciliation methods compare gene trees and species trees to recover evolutionary events such as duplications, transfers and losses explaining the history and composition of genomes. It is well-known that gene trees inferred from molecular sequences can be partly erroneous due to incorrect sequence alignments as well as phylogenetic reconstruction artifacts such as long branch attraction. In practice, this leads reconciliation methods to overestimate the number of evolutionary events. Several methods have been proposed to circumvent this problem, by collapsing the unsupported edges and then resolving the obtained multifurcating nodes, or by directly rearranging the binary gene trees. Yet these methods have been defined for models of evolution accounting only for duplications and losses, i.e. can not be applied to handle prokaryotic gene families. RESULTS: We propose a reconciliation method accounting for gene duplications, losses and horizontal transfers, that specifically takes into account the uncertainties in gene trees by rearranging their weakly supported edges. Rearrangements are performed on edges having a low confidence value, and are accepted whenever they improve the reconciliation cost. We prove useful properties on the dynamic programming matrix used to compute reconciliations, which allows to speed-up the tree space exploration when rearrangements are generated by Nearest Neighbor Interchanges (NNI) edit operations. Experiments on synthetic data show that gene trees modified by such NNI rearrangements are closer to the correct simulated trees and lead to better event predictions on average. Experiments on real data demonstrate that the proposed method leads to a decrease in the reconciliation cost and the number of inferred events. Finally on a dataset of 30 k gene families, this reconciliation method shows a ranking of prokaryotic phyla by transfer rates identical to that proposed by a different approach dedicated to transfer detection [BMCBIOINF 11:324, 2010, PNAS 109(13):4962-4967, 2012]. CONCLUSIONS: Prokaryotic gene trees can now be reconciled with their species phylogeny while accounting for the uncertainty of the gene tree. More accurate and more precise reconciliations are obtained with respect to previous parsimony algorithms not accounting for such uncertainties [LNCS 6398:93-108, 2010, BIOINF 28(12): i283-i291, 2012].A software implementing the method is freely available at http://www.atgc-montpellier.fr/Mowgli/.