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## A Nonparametric and Rapid Score Calibration Method for Database Search-Based Peptide Identification in Shotgun Proteomics

Peptide-spectrum-match (PSM) scores used in database searching are calibrated to spectrum- or spectrum-peptide-specific null distributions. Some calibration methods rely on specific assumptions and use analytical models (e.g., binomial distributions), whereas other methods utilize exact empirical null distributions. The former may be inaccurate because of unjustified assumptions, while the latter are accurate, albeit computationally exhaustive. Here, we introduce a novel, nonparametric, heuristic PSM score calibration method, called Tailor, which calibrates PSM scores by dividing them with the top 100-quantile of the empirical, spectrum-specific null distributions (i.e., the score with an associated *p*-value of 0.01 at the tail, hence the name) observed during database searching. Tailor does not require any optimization steps or long calculations; it does not rely on any assumptions on the form of the score distribution (i.e., if it is, e.g., binomial); however, it relies on our empirical observation that the mean and the variance of the null distributions are correlated. In our benchmark, we re-calibrated the match scores of XCorr from Crux, HyperScore scores from X!Tandem, and the *p*-values from OMSSA with the Tailor method and obtained more spectrum annotations than with raw scores at any false discovery rate level. Moreover, Tailor provided slightly more annotations than *E*-values of X!Tandem and OMSSA and approached the performance of the computationally exhaustive exact *p*-value method for XCorr on spectrum data sets containing low-resolution fragmentation information (MS2) around 20-150 times faster. On high-resolution MS2 data sets, the Tailor method with XCorr achieved state-of-the-art performance and produced more annotations than the well-calibrated residue-evidence (Res-ev) score around 50-80 times faster.

Graph coloring problem is one of the classical combinatorial optimization problems. This problem consists in finding the minimal number of colors in which it is possible to color vertices of a graph so that any two adjacent vertices are colored in different colors. The graph coloring problem has a wide variety of applications including timetabling problems, processor register allocation problems, frequency assignment problems, data clustering problems, traffic signal phasing problems, maximum clique problem, maximum independent set problem, minimum vertex cover problem and others. In this paper a new efficient heuristic algorithm for the graph coloring problem is presented. The suggested algorithm builds the same coloring of a graph as does the widely used greedy sequential algorithm in which at every step the current vertex is colored into minimal feasible color. Computational experiments show that the presented algorithm performs graph coloring much faster in comparison with the standard greedy algorithm. The speedup reaches 5,6 times for DIMACS graphs.

Fast algorithms for decoding of linear block codes.

Приведено доказательство теоремы об обратном циклотомическом DFT над конечным полем.

The paper describes the method of finite element simulation of shape rolling process based on 2,5D techniques which is due to the number of simplifications, allows to increase the rate of calculation considerably (by comparison with 3D modeling). To verify this technique the comparison of model results with data obtained at the metallurgical plant Trinecke Zelezarny within the special industrial testing was performed. The comparison confirmed the adequacy and effectiveness of the proposed models and computer system developed on their basis.

In this paper we introduce a new pattern-based approach within the Linear Assignment Model with the purpose to design heuristics for a combinatorial optimization problem (COP). We assume that the COP has an additive (separable) objective function and the structure of a feasible (optimal) solution to the COP is predefined by a collection of cells (positions) in an input file. We define a pattern as a collection of positions in an instance problem represented by its input file (matrix). We illustrate the notion of pattern by means of some well known problems in COP among them the Linear Ordering Problem, Cell Formation Problem (CFP) just to mention a couple. The CFP is defined on a Boolean input matrix which rows represent machines and columns - parts. The CFP consists in finding three optimal objects: a block-diagonal collection of rectangles, a rows (machines) permutation, and a columns (parts) permutation such that the grouping efficacy is maximized. The suggested heuristic combines two procedures: the pattern-based procedure to build an initial solution and an improvement procedure to obtain a final solution with high grouping efficacy for the CFP. Our computational experiments with the most popular set of 35 benchmark instances show that our heuristic outperforms all well known heuristics and returns either the best known or improved solutions to the CFP.

One of the key advances in genome assembly that has led to a significant improvement in contig lengths has been improved algorithms for utilization of paired reads (mate-pairs). While in most assemblers, mate-pair information is used in a post-processing step, the recently proposed Paired de Bruijn Graph (PDBG) approach incorporates the mate-pair information directly in the assembly graph structure. However, the PDBG approach faces difficulties when the variation in the insert sizes is high. To address this problem, we first transform mate-pairs into edge-pair histograms that allow one to better estimate the distance between edges in the assembly graph that represent regions linked by multiple mate-pairs. Further, we combine the ideas of mate-pair transformation and PDBGs to construct new data structures for genome assembly: pathsets and pathset graphs.

Papers about natural protection territories

Many environmental stimuli present a quasi-rhythmic structure at different timescales that the brain needs to decompose and integrate. Cortical oscillations have been proposed as instruments of sensory de-multiplexing, i.e., the parallel processing of different frequency streams in sensory signals. Yet their causal role in such a process has never been demonstrated. Here, we used a neural microcircuit model to address whether coupled theta–gamma oscillations, as observed in human auditory cortex, could underpin the multiscale sensory analysis of speech. We show that, in continuous speech, theta oscillations can flexibly track the syllabic rhythm and temporally organize the phoneme-level response of gamma neurons into a code that enables syllable identification. The tracking of slow speech fluctuations by theta oscillations, and its coupling to gamma-spiking activity both appeared as critical features for accurate speech encoding. These results demonstrate that cortical oscillations can be a key instrument of speech de-multiplexing, parsing, and encoding.

Hypoxia of trophoblast cells is an important regulator of normal development of the placenta. However, some pathological states associated with hypoxia, *e.g.* preeclampsia, impair the functions of placental cells. Oxyquinoline derivative inhibits HIF-prolyl hydroxylase by stabilizing HIF-1 transcription complex, thus modeling cell response to hypoxia. In human choriocarcinoma cells BeWo b30 (trophoblast model), oxyquinoline increased the expression of a core hypoxia response genes along with up-regulation of *NOS3*, *PDK1*, and *BNIP3* genes and down-regulation of the *PPARGC1B* gene. These changes in the expression profile attest to activation of the metabolic cell reprogramming mechanisms aimed at reducing oxygen consumption by enabling the switch from aerobic to anaerobic glucose metabolism and the respective decrease in number of mitochondria. The possibility of practical use of the therapeutic properties of oxyquinoline derivatives is discussed.