2,648 research outputs found
Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein
No full textBackground: A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed genes, clustering of genes and regulatory network. On other hand there are only few studies on relation between expression level and composition of nucleotide/protein sequence, using expression data. There is a need to understand why particular genes/proteins express more in particular conditions. In this study, we analyze 3468 genes of Saccharomyces cerevisiae obtained from Holstege et al., ( 1998) to understand the relationship between expression level and amino acid composition. Results: We compute the correlation between expression of a gene and amino acid composition of its protein. It was observed that some residues ( like Ala, Gly, Arg and Val) have significant positive correlation ( r > 0.20) and some other residues ( Like Asp, Leu, Asn and Ser) have negative correlation ( r < - 0.15) with the expression of genes. A significant negative correlation ( r = - 0.18) was also found between length and gene expression. These observations indicate the relationship between percent composition and gene expression level. Thus, attempts have been made to develop a Support Vector Machine ( SVM) based method for predicting the expression level of genes from its protein sequence. In this method the SVM is trained with proteins whose gene expression data is known in a given condition. Then trained SVM is used to predict the gene expression of other proteins of the same organism in the same condition. A correlation coefficient r = 0.70 was obtained between predicted and experimentally determined expression of genes, which improves from r = 0.70 to 0.72 when dipeptide composition was used instead of residue composition. The method was evaluated using 5-fold cross validation test. We also demonstrate that amino acid composition information along with gene expression data can be used for improving the function classification of proteins. Conclusion: There is a correlation between gene expression and amino acid composition that can be used to predict the expression level of genes up to a certain extent. A web server based on the above strategy has been developed for calculating the correlation between amino acid composition and gene expression and prediction of expression level http:// kiwi. postech. ac. kr/ raghava/ lgepred/. This server will allow users to study the evolution from expression data.open1137sciescopu
Classification of early and late stage Liver Hepatocellular Carcinoma patients from their genomics and epigenomics profiles
No full textAbstractBackgroundLiver Hepatocellular Carcinoma (LIHC) is the second major cancer worldwide, responsible for millions of premature deaths every year. Prediction of clinical staging is vital to implement optimal therapeutic strategy and prognostic prediction in cancer patients. However, to date, no method has been developed for predicting stage of LIHC from genomic profile of samples.ResultsIn current study, in silico models have been developed for classifying LIHC patients in early and late stage using RNA expression and DNA methylation data. The Cancer Genome Atlas (TCGA) dataset contains 173 early and 177 late stage samples of LIHC, was extensively analysed to identify differentially expressed RNA transcripts and methylated CpG sites that can discriminate early and late stages of LIHC samples with high precision. Naive Bayes model developed using 51 features that combine 21 CpG methylation sites and 30 RNA transcripts achieved maximum MCC 0.58 with accuracy 78.87% on validation dataset. Further, we also analysed genomics and epigenomics profiles of normal and LIHC samples and developed model to classify LIHC samples with AUROC 0.99. In addition, multiclass models developed for classifying samples in normal, early and late stage of cancer and achieved accuracy of 76.54% and AUROC of 0.86.ConclusionOur study reveals stage prediction of LIHC samples with high accuracy based on genomics and epigenomics profiling is a challenging task in comparison to classification of LIHC and normal samples. Comprehensive analysis, differentially expressed RNA transcripts, methylated CpG sites in LIHC samples and prediction models are available from CancerLSP ( http://webs.iiitd.edu.in/raghava/cancerlsp/).</jats:sec
Feasibility of using Clinical Element Models (CEM) to standardize phenotype variables in the database of genotypes and phenotypes (dbGaP).
No full textThe database of Genotypes and Phenotypes (dbGaP) contains various types of data generated from genome-wide association studies (GWAS). These data can be used to facilitate novel scientific discoveries and to reduce cost and time for exploratory research. However, idiosyncrasies and inconsistencies in phenotype variable names are a major barrier to reusing these data. We addressed these challenges in standardizing phenotype variables by formalizing their descriptions using Clinical Element Models (CEM). Designed to represent clinical data, CEMs were highly expressive and thus were able to represent a majority (77.5%) of the 215 phenotype variable descriptions. However, their high expressivity also made it difficult to directly apply them to research data such as phenotype variables in dbGaP. Our study suggested that simplification of the template models makes it more straightforward to formally represent the key semantics of phenotype variables
B-spline function-based approach for GPS tropospheric tomography
No full textTropospheric tomography is one of the most important techniques to reconstruct three-dimensional (3D) images of the tropospheric water vapor fields using a local GNSS network. In the conventional tropospheric tomography method, called voxel-based tropospheric tomography, the 3D space is divided into many voxels and the amount of water vapor is estimated for each voxel. This method suffers from three disadvantages. First, it needs empirical constraints in order to fix the rank deficiency of the coefficient matrix. Second, the amount of water vapor is assumed to be constant in the 3D space of a voxel despite the large spatial variations of this parameter. Third, the number of unknown parameters is high compared to the number of observations. Therefore, an approach based on mathematical functions, called function-based tropospheric tomography, is presented to overcome these problems. The tropospheric tomography using the voxel-based and function-based approaches is performed using 17 GPS stations. Radiosonde observations and precise point positioning results are used to validate the obtained results. A comparison of the results with the radiosonde data indicates that using the function-based method reduces the mean RMSE by about 0.3 gr/m3. Validation using positioning under different wet conditions shows that in wet weather conditions the difference between the RMSE of the two tropospheric tomography approaches is significant. All the validations show the ability and applicability of the function-based tropospheric tomography approach.Accepted Author ManuscriptMathematical Geodesy and Positionin
Use of global positioning system velocity outputs for determining airspeed measurement error
No full textSeveral methods have been derived since the advent of GPS (Global Positioning System) receivers in aircraft cockpits by which these receivers may be used to calibrate these aircraft’s other instrumentation; in particular the pitot-static system. This paper presents the four most suitable methods, two of which have been developed by the author. These methods are shown with a common symbology, and their strengths, weaknesses, analysis and operational use are compared
Bandwidth correction of Swarm GPS carrier phase observations for improved orbit and gravity field determination
No full textGravity fields derived from GPS tracking of the three Swarm satellites have shown artifacts near the geomagnetic equator, where the carrier phase tracking on the L2 frequency is unable to follow rapid ionospheric path delay changes due to a limited tracking loop bandwidth of only 0.25 Hz in the early years of the mission. Based on the knowledge of the loop filter design, an analytical approach is developed to recover the original L2 signal from the observed carrier phase through inversion of the loop transfer function. Precise orbit determination and gravity field solutions are used to assess the quality of the correction. We show that the a posteriori RMS of the ionosphere-free GPS phase observations for a reduced-dynamic orbit determination can be reduced from 3 to 2 mm while keeping up to 7% more data in the outlier screening compared to uncorrected observations. We also show that artifacts in the kinematic orbit and gravity field solution near the geomagnetic equator can be substantially reduced. The analytical correction is able to mitigate the equatorial artifacts. However, the analytical correction is not as successful compared to the down-weighting of problematic GPS data used in earlier studies. In contrast to the weighting approaches, up to 9–10% more kinematic positions can be retained for the heavily disturbed month March 2015 and also stronger signals for gravity field estimation in the equatorial regions are obtained, as can be seen in the reduced error degree variances of the gravity field estimation. The presented approach may also be applied to other low earth orbit missions, provided that the GPS receivers offer a sufficiently high data rate compared to the tracking loop bandwidth, and provided that the basic loop-filter parameters are known.Astrodynamics & Space Mission
CASSIOPE orbit and attitude determination using commercial off-the-shelf GPS receivers
No full textAs part of the “GPS Attitude, Positioning, and Profiling experiment (GAP)” of the Canadian CASSIOPE science and technology mission, a set of four geodetic GPS receivers connected to independent antennas on the top-panel of the spacecraft can be operated concurrently to collect dual-frequency code and phase measurements on both the L1 and L2 frequencies. The qualification of the commercial off-the-shelf (COTS) GPS receivers is discussed, and flight results of precise orbit and attitude determination are presented. Pseudorange and carrier phase errors amount to roughly 65 cm and 8 mm for the ionosphere-free dual-frequency combination, which compares favorably with other missions using fully qualified space GPS receivers and is mainly limited by choice of simple patch antennas without choke rings. Precise orbit determination of CASSIOPE using GPS observations can achieve decimeter-level accuracy during continued operations but suffers from onboard and mission restrictions that limit the typical data availability to less than 50% of each day and induce regular long-duration gaps of 4–10 h. Based on overlap analyses, daily peak orbit determination errors can, however, be confined to 1 m 3D on 84% of all days, which fulfills the mission needs for science data processing of other instruments. The attitude of CASSIOPE can be determined with a representative precision of about 0.2° in the individual axes using three GAP receivers and antennas. Availability of dual-frequency measurements is particularly beneficial and enables single-epoch ambiguity fixing in about 97% of all epochs. Overall, the GAP experiment demonstrates the feasibility of using COTS-based global navigation satellite system receivers in space and the benefits they can bring for small-scale science missions.</p
Geometry-free undifferenced, single and double differenced analysis of single frequency GPS, EGNOS and GIOVE-A/B measurements
No full textThis paper demonstrates a geometry-free GNSS measurement analysis approach and presents results of single frequency GPS, EGNOS and GIOVE short and zero baseline measurements. The purpose is to separate the different contributions to the measurement noise of pseudo range code and carrier phase observations at the receiver. The influence of multipath on the different combinations of observations is also determined. Quantitative results are presented for the thermal code and phase measurement noise and for the correlation between the observations. Comparison of the results with theoretical approximations confirms the validity of the used approach. Results from field measurements clearly show less thermal noise on the Galileo E1BC observations than on the GPS L1C/A observations due to the new signal modulation. The feasibility of ambiguity resolution with a geometry-free model is also discussed including the significant impact of multipath thereon.Earth Observation and Space SystemsAerospace Engineerin
GPS-based addressing and routing
No full textIn the near future GPS will be widely used, thus allowing a broad variety of location dependent services such as direction giving, navigation, etc. In this document we propose a family of protocols and addressing methods to integrate GPS into the Internet Protocol to enable the creation of location dependent services. The solutions which we present are flexible (scalable) in terms of the target accuracy of the GPS. The main challenge is to integrate the concept of physical location into the current design of the Internet which relies on logical addressing. Two solutions are presented in this draft and a third solution is sketched.Technical report lcsr-tr-26
Analysis and prediction of antibacterial peptides
No full textAbstract Background Antibacterial peptides are important components of the innate immune system, used by the host to protect itself from different types of pathogenic bacteria. Over the last few decades, the search for new drugs and drug targets has prompted an interest in these antibacterial peptides. We analyzed 486 antibacterial peptides, obtained from antimicrobial peptide database APD, in order to understand the preference of amino acid residues at specific positions in these peptides. Results It was observed that certain types of residues are preferred over others in antibacterial peptides, particularly at the N and C terminus. These observations encouraged us to develop a method for predicting antibacterial peptides in proteins from their amino acid sequence. First, the N-terminal residues were used for predicting antibacterial peptides using Artificial Neural Network (ANN), Quantitative Matrices (QM) and Support Vector Machine (SVM), which resulted in an accuracy of 83.63%, 84.78% and 87.85%, respectively. Then, the C-terminal residues were used for developing prediction methods, which resulted in an accuracy of 77.34%, 82.03% and 85.16% using ANN, QM and SVM, respectively. Finally, ANN, QM and SVM models were developed using N and C terminal residues, which achieved an accuracy of 88.17%, 90.37% and 92.11%, respectively. All the models developed in this study were evaluated using five-fold cross validation technique. These models were also tested on an independent or blind dataset. Conclusion Among antibacterial peptides, there is preference for certain residues at N and C termini, which helps to demarcate them from non-antibacterial peptides. Both the termini play a crucial role in imparting the antibacterial property to these peptides. Among the methods developed, SVM shows the best performance in predicting antibacterial peptides followed by QM and ANN, in that order. AntiBP (Antibacterial peptides) will help in discovering efficacious antibacterial peptides, which we hope will prove to be a boon to combat the dreadful antibiotic resistant bacteria. A user friendly web server has also been developed to help the biological community, which is accessible at http://www.imtech.res.in/raghava/antibp/.</p
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