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As the explosive growth of sequence databases continues, both the content of these databases and the best strategies for exploiting them are changing. Remarkable improvements in the performance of microcomputers have put very sophisticated tools within the reach of all investigators. New scoring schemes have improved the sensitivity of searching regimens and the accuracy of alignments.
MOTIVATION: During evolution, functional regions in genomic sequences tend to be more highly conserved than randomly mutating 'junk DNA' so local sequence similarity often indicates biological functionality. This fact can be used to identify functional elements in large eukaryotic DNA sequences by cross-species sequence comparison. In recent years, several gene-prediction methods have been proposed that work by comparing anonymous genomic sequences, for example from human and mouse. The main advantage of these methods is that they are based on simple and generally applicable measures of (local) sequence similarity; unlike standard gene-finding approaches they do not depend on species-specific training data or on the presence of cognate genes in data bases. As all comparative sequence-analysis methods, the new comparative gene-finding approaches critically rely on the quality of the underlying sequence alignments. RESULTS: Herein, we describe a new implementation of the sequence-alignment program DIALIGN that has been developed for alignment of large genomic sequences. We compare our method to the alignment programs PipMaker, WABA and BLAST and we show that local similarities identified by these programs are highly correlated to protein-coding regions. In our test runs, PipMaker was the most sensitive method while DIALIGN was most specific. AVAILABILITY: The program is downloadable from the DIALIGN home page at http://bibiserv.techfak.uni-bielefeld.de/dialign/.
SUMMARY: We have developed U-PRIMER, a primer design program, to compute a minimal primer set (MPS) for any given set of DNA sequences. The U-PRIMER algorithm, which uses automatic variable fixing and automatic redundant constraint elimination to tackle the binary integer programming problem associated with the MPS selection problem. The program has been tested successfully with 32 adipocyte development-related genes and 9 TB-specific genes to obtain their respective MPSs. AVAILABILITY: A free copy of U-PRIMER implemented in C++ programming language is available from http://www.u-vision-biotech.com
A "one-stop shop" for evaluating cardiac disease with magnetic resonance (MR) imaging is progressing toward clinical reality and promises to have a major effect on the care of patients with cardiac disease. T1-weighted conventional spin-echo imaging gated to the cardiac cycle yields good anatomic detail but requires long imaging times and provides only static images of a single cardiac phase. Fast MR imaging with electrocardiographically (ECG) gated, low-flip-angle, segmented k-space gradient-recalled-echo (GRE) sequences provides excellent image quality with sufficiently high temporal resolution to "freeze" cardiac motion. Segmented k-space sequences improve on standard ECG-gated GRE sequences by allowing many cardiac phases, or frames of a cine sequence, to be imaged in a single breath hold with prospective cardiac gating. As commercial implementations of segmented k-space imaging become more widely available, the applications of this technique are expanding from research protocols to include many clinical applications in the heart and great vessels. Such applications include evaluation of vascular anatomy (coronary angiography, aortic disease, aberrant vessels, vascular access), cardiac anatomy (congenital anomalies, right ventricular dysplasia, constrictive pericarditis, valvular function), myocardial perfusion, and myocardial wall motion.
BACKGROUND: We used magnetic resonance (MR) pyelography to compare the value of thick-slab single-shot rapid acquisition with relaxation enhancement (RARE) sequence with that of multislice half-Fourier acquisition single-shot turbo-spin-echo (HASTE) sequence in evaluating the full spectrum of morphologic features in a group of patients with hydronephrosis. METHODS: MR pyelographic images, with the use of thick-slab RARE and multislice HASTE sequences in 90 patients, were evaluated for image quality, presence of hydronephrosis, and level and cause of obstruction. RESULTS: HASTE sequences provided images of better quality than did RARE sequences (p < 0.001). There was no statistically significant difference in demonstrating the presence of hydronephrosis (p = 0.5) and level of obstruction (p = 0.125). Sensitivity, specificity, and accuracy in diagnosing cause of obstruction were 61.7%, 62.5%, and 62%, respectively, for RARE sequences and 80%, 82.5%, and 81%, respectively, for HASTE sequences, with a statistically significant difference (all p < 0.05). CONCLUSION: Multislice HASTE sequence provides better diagnostic information than does thick-slab RARE sequence, particularly in evaluating the cause of obstruction.
MOTIVATION: DNA and protein microarrays have become an established leading-edge technology for large-scale analysis of gene and protein content and activity. Contact-printed microarrays has emerged as a relatively simple and cost effective method of choice but its reliability is especially susceptible to quality of pixel information obtained from digital scans of spotted features in the microarray image. RESULTS: We address the statistical computation requirements for optimizing data acquisition and processing of digital scans. We consider the use of median filters to reduce noise levels in images and top-hat filters to correct for trends in background values. We also consider, as alternative estimators of spot intensity, discs of fixed radius, proportions of histograms and k-means clustering, either with or without a square-root intensity transformation and background subtraction. We identify, using combinatoric procedures, optimal filter and estimator parameters, in achieving consistency among the replicates of a gene on each microarray. Our results, using test data from microarrays of HCMV, indicate that a highly effective approach for improving reliability and quality of microarray data is to apply a 21 by 21 top-hat filter, then estimate spot intensity as the mean of the largest 20% of pixel values in the target region, after a square-root transformation, and corrected for background, by subtracting the mean of the smallest 70% of pixel values. AVAILABILITY: Fortran90 subroutines implementing these methods are available from the authors, or at http://www.bioss.ac.uk/~chris.
Two methods have been developed for protein identification from tandem mass spectra: database searching and de novo sequencing. De novo sequencing identifies peptide directly from tandem mass spectra. Among many proposed algorithms, we evaluated the performance of the five de novo sequencing algorithms, AUDENS, Lutefisk, NovoHMM, PepNovo, and PEAKS. Our evaluation methods are based on calculation of relative sequence distance (RSD), algorithm sensitivity, and spectrum quality. We found that de novo sequencing algorithms have different performance in analyzing QSTAR and LCQ mass spectrometer data, but in general, perform better in analyzing QSTAR data than LCQ data. For the QSTAR data, the performance order of the five algorithms is PEAKS > Lutefisk, PepNovo > AUDENS, NovoHMM. The performance of PEAKS, Lutefisk, and PepNovo strongly depends on the spectrum quality and increases with an increase of spectrum quality. However, AUDENS and NovoHMM are not sensitive to the spectrum quality. Compared with other four algorithms, PEAKS has the best sensitivity and also has the best performance in the entire range of spectrum quality. For the LCQ data, the performance order is NovoHMM > PepNovo, PEAKS > Lutefisk > AUDENS. NovoHMM has the best sensitivity, and its performance is the best in the entire range of spectrum quality. But the overall performance of NovoHMM is not significantly different from the performance of PEAKS and PepNovo. AUDENS does not give a good performance in analyzing either QSTAR and LCQ data.
We examined three parallel data sets with respect to qualities relevant to phylogenetic analysis of 20 exemplar monocotyledons and related dicotyledons. The three data sets represent restriction-site variation in the inverted repeat region of the chloroplast genome, and nucleotide sequence variation in the chloroplast-encoded gene rbcL and in the mitochondrion-encoded gene atpA, the latter of which encodes the alpha-subunit of mitochondrial ATP synthase. The plant mitochondrial genome has been little used in plant systematics, in part because nucleotide sequence evolution in enzyme-encoding genes of this genome is relatively slow. The three data sets were examined in separate and combined analyses, with a focus on patterns of congruence, homoplasy, and data decisiveness. Data decisiveness (described by P. Goloboff) is a measure of robustness of support for most parsimonious trees by a data set in terms of the degree to which those trees are shorter than the average length of all possible trees. Because indecisive data sets require relatively fewer additional steps than decisive ones to be optimized on nonparsimonious trees, they will have a lesser tendency to be incongruent with other data sets. One consequence of this relationship between decisiveness and character incongruence is that if incongruence is used as a criterion of noncombinability, decisive data sets, which provide robust support for relationships, are more likely to be assessed as noncombinable with other data sets than are indecisive data sets, which provide weak support for relationships. For the sampling of taxa in this study, the atpA data set has about half as many cladistically informative nucleotides as the rbcL data set per site examined, and is less homoplastic and more decisive. The rbcL data set, which is the least decisive of the three, exhibits the lowest levels of character incongruence. Whatever the molecular evolutionary cause of this phenomenon, it seems likely that the poorer performance of rbcL than atpA, in terms of data decisiveness, is due to both its higher overall level of homoplasy and the fact that it is performing especially poorly at nonsynonymous sites.
The study addresses whether subjects are able to assess the perceived quality of an image sequence continuously. To this end, a new method for assessing time-varying perceptual image quality is presented by which subjects continuously indicate the perceived strength of image quality by moving a slider along a graphical scale. The slider's position on this scale is sampled every second. In this way, temporal variations in quality can be monitored quantitatively, and a means is provided by which differences between, for example, alternative transmission systems can be analyzed in an informative way. The usability of this method is illustrated by an experiment in which, for a period of 815 s, subjects assessed the quality of still pictures comprising time-varying degrees of sharpness.
The XOAZRP TCF sequence was applied to bleach wheat straw pulp. Following each bleaching stage, the properties of the pulp (viz. kappa number, standard viscosity, borohydride viscosity and brightness) and of the resulting effluents were determined. The performance of the reagents was analyzed through the studies of xylanase treatment and crystallinity and scanning electron microscopy of the pulps. Finally, the pulp was refined at 1000 revolutions in a PFI mill and the mechanical properties of the resulting paper were determined and compared with those of paper from a eucalyptus pulp. Despite its shortcomings, wheat straw pulp can be effectively bleached with the proposed TCF sequence.
OBJECTIVE: To characterize the composition, diversity, and ecological features of the oral bacteriome in pediatric patients with malignancies prior to chemotherapy initiation. METHODS: In this prospective pilot study,supragingival plaque samples were collected from 10 pediatric cancer patients prior to the initiation of chemotherapy. Bacterial genomic DNA was extracted from each sample, and the full-length 16S rRNA gene was amplified and sequenced on the PacBio Sequel II platform using circular consensus sequencing (CCS). Raw CCS reads were quality-filtered and denoised into amplicon sequence variants (ASVs) using DADA2, and taxonomic assignment was performed against the SILVA 138 reference database. Alpha diversity was assessed using the Chao1, Shannon, Simpson, and Faith's phylogenetic diversity (PD whole tree) indices, while beta diversity was evaluated through principal coordinate analysis (PCoA), and non-metric multidimensional scaling (NMDS). Microbial co-occurrence networks were constructed to characterize bacterial interactions, and functional potential was predicted using PICRUSt2, and BugBase. RESULTS: A total of 614,473 high-quality CCS reads were generated, yielding 1,697 ASVs. Alpha diversity analysis revealed substantial inter-individual variation in microbial richness and diversity among the pediatric cancer patients. The bacterial community was dominated by the phyla Firmicutes, Proteobacteria, Bacteroidota, Actinobacteriota. At the genus level, Streptococcus, Prevotella, Neisseria, and Haemophilus were the most abundant taxa. Beta diversity analysis revealed distinct clustering patterns, indicating highly individualized microbial profiles. Co-occurrence network analysis identified several keystone taxa and potential pathogenic associations within the supragingival plaque community. Functional prediction indicated that the dominant metabolic pathways were related to amino acid metabolism, carbohydrate metabolism, and membrane transport. CONCLUSION: These preliminary findings reveal a taxonomically diverse, highly individualized pre-chemotherapy oral bacteriome, providing foundational baseline profiles to guide future longitudinal investigations of chemotherapy-induced dysbiosis and personalized interventions.
So that we might evaluate the ultrafast half-Fourier single-shot turbo spin-echo (HASTE) sequence in T2-weighted MRI of the female pelvis and compare it with the turbo spin-echo (TSE) sequence, we prospectively studied 60 consecutive females with suspected abnormalities of the pelvis. For all MR examinations, we used a 1.5-T superconductive magnet with a phased array coil. The HASTE sequence was applied with TR/effective TE/echo train = infinity/90/64 and a 128 x 256 matrix (acquisition time: .3 sec/slice), conventional TSE imaging with 3,400 to 5,000/132/15 and a 128 x 256 matrix (mean acquisition time: 2 min 4 sec), and high-resolution TSE imaging with 3,400 to 5,000/132/15 and a 300 x 512 matrix (6 min 4 sec). Although the lesion conspicuity for the HASTE sequence was less than that for the high-resolution TSE sequences, artifacts (including ghosting, bowel motion, susceptibility difference, and chemical shift) were negligible on HASTE images of all patients. The lesion conspicuity for the HASTE sequence was significantly better than for the conventional TSE sequence. In spite of the very short acquisition time, the subjective scoring of the overall image quality for the HASTE sequence was significantly higher than for the conventional TSE sequence (P < .01) and were slightly lower than for the high-resolution TSE sequence. Compared with high-resolution TSE, HASTE provided clearer visualization of large leiomyomas and ovarian tumors but slightly poorer visualization of uterine cancer. In occlusion, HASTE sequence generates higher contrast and is free from motion and chemical shift artifact with much higher time efficacy. Because of limited image resolution, the HASTE sequence should be used when the high-resolution TSE imaging is suboptimal.
Recent developments in MRI software and hardware have increased the speed and versatility of cardiac MRI by allowing image acquisition in a single breathhold. Many studies have shown that conventional cardiac MRI is as accurate as echocardiography or cardiac catheterization for diagnosing numerous cardiac conditions. In many cases cardiac MRI is the most accurate diagnostic technique but has not been widely adopted for routine cardiac imaging. One reason why the use of cardiac MRI has been limited is the long examination times required for conventional cardiac MRI. The development of better hardware, such as faster gradient amplifiers and dedicated surface coils, has allowed the implementation of much faster EKG-gated imaging sequences. These can be used in a single breathhold period, with a significant improvement in image quality compared with conventional sequences. Breathhold sequences can provide all the information provided by conventional cardiac MRI in a shorter time and with equal or better accuracy. Breathhold imaging will allow much wider application of MRI to routine cardiac diagnosis.
We report on the development of molecular inversion probe (MIP) genotyping, an efficient technology for large-scale single nucleotide polymorphism (SNP) analysis. This technique uses MIPs to produce inverted sequences, which undergo a unimolecular rearrangement and are then amplified by PCR using common primers and analyzed using universal sequence tag DNA microarrays, resulting in highly specific genotyping. With this technology, multiplex analysis of more than 1,000 probes in a single tube can be done using standard laboratory equipment. Genotypes are generated with a high call rate (95%) and high accuracy (>99%) as determined by independent sequencing.
MOTIVATION: An important challenge in the use of large-scale gene expression data for biological classification occurs when the expression dataset being analyzed involves multiple classes. Key issues that need to be addressed under such circumstances are the efficient selection of good predictive gene groups from datasets that are inherently 'noisy', and the development of new methodologies that can enhance the successful classification of these complex datasets. METHODS: We have applied genetic algorithms (GAs) to the problem of multi-class prediction. A GA-based gene selection scheme is described that automatically determines the members of a predictive gene group, as well as the optimal group size, that maximizes classification success using a maximum likelihood (MLHD) classification method. RESULTS: The GA/MLHD-based approach achieves higher classification accuracies than other published predictive methods on the same multi-class test dataset. It also permits substantial feature reduction in classifier genesets without compromising predictive accuracy. We propose that GA-based algorithms may represent a powerful new tool in the analysis and exploration of complex multi-class gene expression data. AVAILABILITY: Supplementary information, data sets and source codes are available at http://www.omniarray.com/bioinformatics/GA.
MOTIVATION: Protein structure comparison (PSC) has been used widely in studies of structural and functional genomics. However, PSC is computationally expensive and as a result almost all of the PSC methods currently in use look only for the optimal alignment and ignore many alternative alignments that are statistically significant and that may provide insight into protein evolution or folding. RESULTS: We have developed a new PSC method with efficiency to detect potentially viable alternative alignments in all-against-all database comparisons. The efficiency of the new PSC method derives from the ability to directly home in on a limited number of viable and ranked alignment solutions based on intuitively derived SSE (secondary structure element)-matching probabilities.
MOTIVATION: Maximum likelihood-based methods to estimate site by site substitution rate variability in aligned homologous protein sequences rely on the formulation of a phylogenetic tree and generally assume that the patterns of relative variability follow a pre-determined distribution. We present a phylogenetic tree-independent method to estimate the relative variability of individual sites within large datasets of homologous protein sequences. It is based upon two simple assumptions. Firstly that substitutions observed between two closely related sequences are likely, in general, to occur at the most variable sites. Secondly that non-conservative amino acid substitutions tend to occur at more variable sites. Our methodology makes no assumptions regarding the underlying pattern of relative variability between sites. RESULTS: We have compared, using data simulated under a non-gamma distributed model, the performance of this approach to that of a maximum likelihood method that assumes gamma distributed rates. At low mean rates of evolution our method inferred site by site relative substitution rates more accurately than the maximum likelihood approach in the absence of prior assumptions about the relationships between sequences. Our method does not directly account for the effects of mutational saturation, However, we have incorporated an 'ad-hoc' modification that allows the accurate estimation of relative site variability in fast evolving and saturated datasets.
MOTIVATION: The occurrence of false positives and false negatives in a microarray analysis could be easily estimated if the distribution of p-values were approximated and then expressed as a mixture of null and alternative densities. Essentially any distribution of p-values can be expressed as such a mixture by extracting a uniform density from it. RESULTS: The occurrence of false positives and false negatives in a microarray analysis could be easily estimated if the distribution of p-values were approximated and then expressed as a mixture of null and alternative densities. Essentially any distribution of p-values can be expressed as such a mixture by extracting a uniform density from it. AVAILABILITY: An S-plus function library is available from http://www.stjuderesearch.org/statistics.