Peak-to-peak dynamics in food chain models

We show in this paper that the chaotic regimes of many food chain models often enjoy a very peculiar property, known as peak-to-peak dynamics. This means that the maximum (peak) density of the populations of any trophic level can be easily forecasted provided the last two peaks of the same population are known. Moreover, extensive simulation shows that only the last peak is needed if the forecast concerns the population at the top of the food chain and that peaks variability often increases from bottom to top. All these findings bring naturally to the conclusion that top populations should be sampled in order to have higher chances to detect peak-to-peak dynamics. The analysis is carried out by studying ditrophic food chain models with seasonally varying parameters, tritrophic food chain models with constant parameters, and more complex food chain and food web models.     

Peak quantification in surface-enhanced laser desorption/ionization by using mixture models

Surface-enhanced laser desorption/ionization (SELDI) time of flight (TOF) is a mass spectrometry technology for measuring the composition of a sampled protein mixture. A mass spectrum contains peaks corresponding to proteins in the sample. The peak areas are proportional to the measured concentrations of the corresponding proteins. Quantifying peak areas is difficult for existing methods because peak shapes are not constant across a spectrum and because peaks often overlap. We present a new method for quantifying peak areas. Our method decomposes a spectrum into peaks and a baseline using so-called statistical finite mixture models. We illustrate our method in detail on 8 samples from culture media of adipose tissue and globally on 64 samples from serum to compare our method to the standard Ciphergen method. Both methods give similar estimates for singleton peaks, but not for overlapping peaks. The Ciphergen method overestimates the heights of such peaks while our method still gives appropriate estimates. Peak quantification is an important step in pre-processing SELDI-TOF data and improvements therein will pay off in the later biomarker discovery phase.     

Accurate LC Peak Boundary Detection for 16 O/ 18 O Labeled LC-MS Data

In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements.     

Modeling absence seizure dynamics: implications for basic mechanisms and measurement of thalamocortical and corticothalamic latencies

A successful physiologically based continuum model of the corticothalamic system is applied to determine the relative contributions of axonal and intrinsic cellular delays to the waveforms of absence seizures. The predicted period of the absence seizure depends linearly on model parameters describing thalamocortical, corticothalamic, intracortical, and synaptodendritic delays, and these dependences are linked to the seizure mechanism by showing how time intervals between peaks in the waveforms depend on the parameters. Counterintuitively, it is found that a peak in the local field potential recorded in the thalamic relay nuclei can precede the peak in the cortical field that drove it, without violating causality, but rendering naive interpretation of time intervals between peaks invalid. We argue that a thalamocortical loop mechanism for absence seizures is consistent with intrathalamic cellular properties being the leading determinant of the frequency of spike-wave discharges in rat genetic models, with the combination of network and cellular properties providing a natural explanation for the lower frequency of human absence seizures. Finally, our results imply that the seizure frequency is not determined by the fastest thalamocortical and corticothalamic fibers, but rather depends on an effective weighted conduction velocity of all pathways present.     

Improving mass spectrometry peak detection using multiple peak alignment results

Mass spectrometry data are often corrupted by noise. It is very difficult to simultaneously detect low-abundance peaks and reduce false-positive peak detection caused by noise. In this paper, we propose to improve peak detection using an additional constraint: the consistent appearance of similar true peaks across multiple spectra. We observe that false -positive peaks in general do not repeat themselves well across multiple spectra. When we align all the identified peaks (including false-positive ones) from multiple spectra together, those false-positive peaks are not as consistent as true peaks. Thus, we propose to use information from other spectra in order to reduce false-positive peaks. The new method improves the detection of peaks over the traditional single spectrum based peak detection methods. Consequently, the discovery of cancer biomarkers also benefits from this improvement. Source code and additional data are available at: http://www.ece.ust.hk/ approximately eeyu/mspeak.htm.     

The population characteristics of the brown plant hopper, Nilaparvata lugens, in the Philippines

Abstract. 1. Population characteristics of the brown planthopper, Nilaparvata lugens (Stål), were investigated over eight growing seasons on rainfed rice in the Philippines.
2. Three nymphal generation peaks were observed in most seasons. The third peak was not always the largest and peaks varied considerably in size from season to season.
3. Generation peaks were less distinct at a second sampling site within an irrigation system, possibly associated with increased asynchrony of planting and the consequent increased immigration potential.
4. Mortality was highest for eggs and first instar nymphs. Egg to adult survivorship was estimated as 1–12%.     

Signal detection in high-resolution mass spectrometry data

Mass spectrometry data from high-resolution time-of-flight instruments often contain a vast number of noninformative background-ion peaks whose signal is similar to that of peptide peaks. Consequently, seeking peptide signal in these spectra based on a signal-to-noise ratio will remove signal peaks as well as noise. This work characterizes the background as a precursor to seeking peptide-related features. Robust-regression methods are used to estimate distributions for null (background) peak intensities and locations. Defining signal peaks as outliers with respect to these distributions leads to more precision in detecting the isotopic envelope of peaks from low-abundance peptides in high-resolution spectra.     

A 2D NMR study of the internal flexibility of the antifungal peptide stendomycin

A 2-D ¹H NMR study (NOESY, COSY, HOHAHA and ROESY experiments) of the antifungal peptide stendomycin is presented. The variation of the NOESY cross peak intensities is measured as a function of temperature in order to discriminate between constant and fluctuating interproton distances. It is shown that among 71 NOESY cross peaks, only 12 correspond to well defined interproton distances and their correlation time is determined. The other cross peaks cannot be translated accurately in terms of distances owing to internal molecular motions. ¹H}–¹³C nOe measurements confirm the internal mobility of the molecule. Finally a flexibility map of stendomycin can be established. Offprint requests to: J. P. Simorre     

Potential bias in NMR relaxation data introduced by peak intensity analysis and curve fitting methods

We present an evaluation of the accuracy and precision of relaxation rates calculated using a variety of methods, applied to data sets obtained for several very different protein systems. We show that common methods of data evaluation, such as the determination of peak heights and peak volumes, may be subject to bias, giving incorrect values for quantities such as R₁ and R₂. For example, one common method of peak-height determination, using a search routine to obtain the peak-height maximum in successive spectra, may be a source of significant systematic error in the relaxation rate. The alternative use of peak volumes or of a fixed coordinate position for the peak height in successive spectra gives more accurate results, particularly in cases where the signal/noise is low, but these methods have inherent problems of their own. For example, volumes are difficult to quantitate for overlapped peaks. We show that with any method of sampling the peak intensity, the choice of a 2- or 3-parameter equation to fit the exponential relaxation decay curves can dramatically affect both the accuracy and precision of the calculated relaxation rates. In general, a 2-parameter fit of relaxation decay curves is preferable. However, for very low intensity peaks a 3 parameter fit may be more appropriate.     

Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into -values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx.     

Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching

MOTIVATION: A major problem for current peak detection algorithms is that noise in mass spectrometry (MS) spectra gives rise to a high rate of false positives. The false positive rate is especially problematic in detecting peaks with low amplitudes. Usually, various baseline correction algorithms and smoothing methods are applied before attempting peak detection. This approach is very sensitive to the amount of smoothing and aggressiveness of the baseline correction, which contribute to making peak detection results inconsistent between runs, instrumentation and analysis methods. RESULTS: Most peak detection algorithms simply identify peaks based on amplitude, ignoring the additional information present in the shape of the peaks in a spectrum. In our experience, 'true' peaks have characteristic shapes, and providing a shape-matching function that provides a 'goodness of fit' coefficient should provide a more robust peak identification method. Based on these observations, a continuous wavelet transform (CWT)-based peak detection algorithm has been devised that identifies peaks with different scales and amplitudes. By transforming the spectrum into wavelet space, the pattern-matching problem is simplified and in addition provides a powerful technique for identifying and separating the signal from the spike noise and colored noise. This transformation, with the additional information provided by the 2D CWT coefficients can greatly enhance the effective signal-to-noise ratio. Furthermore, with this technique no baseline removal or peak smoothing preprocessing steps are required before peak detection, and this improves the robustness of peak detection under a variety of conditions. The algorithm was evaluated with SELDI-TOF spectra with known polypeptide positions. Comparisons with two other popular algorithms were performed. The results show the CWT-based algorithm can identify both strong and weak peaks while keeping false positive rate low. AVAILABILITY: The algorithm is implemented in R and will be included as an open source module in the Bioconductor project.     

Peak alignment using restricted edit distances

A peak is a pair of real values (x,y), where x is the time when peak of height y is registered. In the peak alignment problem, we are given two sequences of peaks, and our task is to align the sequences allowing some basic edit operations on the peaks. We study an instance of the peak alignment problem that arises in the analysis of Mass Spectrometry data in Systems Biology. There the measurement technique guarantees that two peaks (x,y), (x',y') can only be considered the same if x is close enough to x', and y is close enough to y'. We review some methods to do alignment under such restrictions on matches.     

Anisotropy and anharmonicity of atomic fluctuations in proteins: implications for X-ray analysis

The effects of anisotropy and anharmonicity of the atomic fluctuations on the results of crystallographic refinement of proteins are examined. Atomic distribution functions from a molecular dynamics simulation for lysozyme are introduced into a real-space (electron density) refinement procedure for individual atoms. Several models for the atomic probability distributions are examined. When isotropic, harmonic motion is assumed, the largest discrepancies between the true first moments (means) and second moments (B factors) of the positions calculated from the dynamics and the fitted values occur for probability densities with multiple peaks. The refined mean is at the center of the largest peak, and the refined B factor is slightly larger than that of the largest peak, unless the distance between the peaks is small compared to the peak width. The resulting values are often significantly different from the true first and second moments of the distribution. To improve the results, alternate conformations, rather than anharmonic corrections, should be included.     

石楠和蜡梅茎结冰动力学过程的差热扫描分析

在（0.66 ±0.2）℃/min（0℃~-20℃）的降温速度下,采用高分辨率差热分析法分别对石楠（Photinia serrulata Lindl.）和蜡梅（Chimonanthus praecox（L.）Link）活体幼茎和经过10 min高温煮沸的幼茎在结冰过程中的热力学行为进行分析,并根据茎的形态解剖结构对他们的结冰特征进行研究。结果显示：石楠和蜡梅的活体幼茎在结冰过程中的差热扫描曲线均出现3个放热峰;而经过高温杀死后的茎仅出现1个单放热峰。分析结果表明,2种植物活体幼茎的3个放热峰可能与其木质部、质外体、韧皮部、形成层的结冰、脱水以及髓组织的结冰、脱水过程有关。进一步采用生理盐水浸湿的滤纸进行模拟实验,结果发现差热扫描曲线出现与高温杀死的茎类似的放热峰。实验结果表明,采用高分辨率差热分析法可以探测植物组织结冰过程中的放热强度、结冰温度及其与结冰动力学过程相关的大量细节,适用于植物的结冰动力学分析。     

Auditory brain stem responses to monoaural stimulation registered in symmetrical areas of cat's brain cortex

In five anaesthetized cats (Nembutal 35 mg/kg) with 14 chronically implanted recording epidural electrodes the auditory brain stem responses (ABR) to monoaural stimulation (click) in symmetrical areas of the brain cortex were recorded. Each ABR to acoustic stimulus of sufficient intensity is formed by a complex of alternating five positive (P1-P5) and four negative (N1-N4) peaks; two further small peaks often follow on this complex. The amplitude of ABR peaks N3, P4, N4 and P5 to monoaural stimulation in symmetrical areas of cat's cortex was always higher in records from the hemisphere contralateral to the stimulated ear than in records from the ipsilateral one. The amplitude of P3 ABR peak behaved to the contrary--it was higher on ipsilateral hemisphere. On the other hand the amplitude of ABR peaks P1, N1, P2 and N2 to monoaural stimulation in symmetrical areas of the brain cortex showed no degree of lateralization in our experimental animals. The present findings support indirectly the presumption that each peak of the ABR is generated by a particular acoustic brain stem structure.     

Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms

Background

There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS) studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached.

Results

In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE) peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR) control approach and that the reproducibility of DE peak detection could thereby be increased.

Conclusions

Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.     

The genomic signature of parallel adaptation from shared genetic variation

Parallel adaptation is common and may often occur from shared genetic variation, but the genomic consequences of this process remain poorly understood. We first use individual‐based simulations to demonstrate that comparisons between populations adapted in parallel to similar environments from shared variation reveal a characteristic genomic signature around a selected locus: a low‐divergence valley centred at the locus and flanked by twin peaks of high divergence. This signature is initiated by the hitchhiking of haplotype tracts differing between derived populations in the broader neighbourhood of the selected locus (driving the high‐divergence twin peaks) and shared haplotype tracts in the tight neighbourhood of the locus (driving the low‐divergence valley). This initial hitchhiking signature is reinforced over time because the selected locus acts as a barrier to gene flow from the source to the derived populations, thus promoting divergence by drift in its close neighbourhood. We next empirically confirm the peak‐valley‐peak signature by combining targeted and RAD sequence data at three candidate adaptation genes in multiple marine (source) and freshwater (derived) populations of threespine stickleback. Finally, we use a genome‐wide screen for the peak‐valley‐peak signature to discover additional genome regions involved in parallel marine‐freshwater divergence. Our findings offer a new explanation for heterogeneous genomic divergence and thus challenge the standard view that peaks in population divergence harbour divergently selected loci and that low‐divergence regions result from balancing selection or localized introgression. We anticipate that genome scans for peak‐valley‐peak divergence signatures will promote the discovery of adaptation genes in other organisms.     

Bayesian Peak Picking for NMR Spectra

Protein structure determination is a very important topic in structural genomics,which helps people to understand varieties of biological functions such as protein-protein interactions,protein–DNA interactions and so on.Nowadays,nuclear magnetic resonance(NMR) has often been used to determine the three-dimensional structures of protein in vivo.This study aims to automate the peak picking step,the most important and tricky step in NMR structure determination.We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem.Under the Bayesian framework,the peak picking problem is casted as a variable selection problem.The proposed method can automatically distinguish true peaks from false ones without preprocessing the data.To the best of our knowledge,this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.     

橄榄星室木虱的生活史和种群消长动态的研究

本研究了莆田市延寿村的橄榄星室木虱的生活史和种群消长动态。结果表明,橄榄星室木虱在莆田地区一年发生8代,世代重叠。卵、若虫(1—5龄)、成虫在1年中有6个发生高峰期,以秋梢期为全年雌成虫产卵、若虫发生最高峰,夏梢期是成虫羽化全年最高峰。其田间种群数量消长与橄榄抽梢期有着极为密切的关系,每一次抽梢期都带来一个产卵高峰期和低龄若虫发生高峰期,每一次抽梢都使虫口数量急尉上升,并出现高峰,其间也带来一个很高的种群增长率,待到新梢定型老化(枝梢生长后期)又使种群数量明显下降,而低龄若虫的发生和高峰期的出现,一般比产卵滞后5—10d。