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1
Content available remote Method for deisotoping based on fuzzy inference systems
Glodek A., Polańska J.
Mathematica Applicanda
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2018
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Vol. 46, no. 1
77--86
EN
Proteins are very significant molecules that can construct the fingerprint of cancer. When dealing with large molecules, such as proteins, the crucial issue is their trustful and precise identification. In the majority of cases, mass spectrometry is used to identify the protein. Processing of data gathered in mass spectrometry experiment consists of several steps, and one of them is deisotoping. It is an essential part of preprocessing because some peaks in the spectrum are not the unique compound, but they are members of an isotopic envelope. There are several existing methods of deisotoping, but none of them is general and can be used in any experimental settings. To manage this, we propose a new algorithm based on fuzzy inference systems. The method was tested on the data provided by Institute of Oncology in Gliwice, that has been gathered in MALDI experiment in two different settings on head and neck cancer tissue samples. The comparison study, done between the developed fuzzy-based algorithm and mMass method revealed that the proposed method was able to identify more consistent with the expert annotation isotopic envelopes.
PL
Praca przedstawia nowy algorytm identyfikacji obwiedni izotopowych w widmach proteomicznych MALDI ToF. W ostatnich latach proteomika wraz z genetyką i transkryptomiką, silnie wspierają diagnostykę chorób nowotworowych. Bardzo ważne jest precyzyjne zidentyfikowanie białek znajdujących się w obszarze raka, gdyż pozwala to zrozumieć proces nowotworzenia oraz zaplanować własciwą terapię. Spektrometia mas, a właściwie technika zwana MALDI ToF (ang. Matrix Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry) jest powszechnie stosowana do pozyskania widm masowych, w których zawarta jest informacja o liczbie jonów o danym stosunku masy do ładunku. Etap przetwarzania wstępnego sygnału wymaga m.in. usunięcia szumu, linii bazowej i normalizacji. Identyfikacja przetwarzania wstępnego, który pozwala na usuniecie redundancji i zredukowanie wymiarowości danych. Istnieje wiele algorytmów identyfikacji obwiedni izotopowej, jednak każdy z nich przeznaczony jest dla innego rodzaju techniki spektrometrii masowej (MALDI, LC-MS, ESI, etc.) bądź dla konkretnego rodzaju cząsteczek. Zaproponowany algorytm oparty jest na teorii systemów rozmytych, a reguły wnioskowania zostały opracowane we współpracy z zespołem ekspertów w dziedzinie spektrometrii masowej. Przetestowany został na danych uzyskanych z Instytutu Onkologii im. Marii Skłodowskiej-Curie w Gliwicach, pochodzących z badań nad rakiem głowy i szyi. Wyniki autorskiego algorytmu do identyfikacji obwiedni izotopowych porównano z jedną z istniejących metod do identyfikacji obwiedni izotopowych.
2
Statystyczna analiza danych proteomicznych
Kawulok J., Polańska J.
Studia Informatica
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2011
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Vol. 32, nr 2A
229-243
PL
Celem prac przedstawionych w niniejszym artykule była konstrukcja narzędzi do analizy danych proteomicznych, które pomogą w wykrywaniu choroby nowotworowej we wczesnym jej stadium. W prezentowanym artykule na początku została przeprowadzona wstępna obróbka widm masowych. Po zamodelowaniu ich za pomocą mieszanin gaussowskich wykorzystano klasyfikator SVM do rozdzielenia grupy z rakiem od grupy kontrolnej. Przedstawione wyniki badań potwierdziły skuteczność wykonanych operacji.
EN
The aim of the work reported in this paper was to develop statistical tools for mass spectra analysis. They would make it possible to detect cancer at its early stages. The main goal was to construct a classifier which would best distinguish people with cancer from a control group. First, the mass spectral signal is pre-processed. Next, the signals are modeled using Gaussian mixtures and they are later classified. The obtained results confirmed the effectiveness of the presented method.
3
Content available Mixture model of NMR - its application to diagnosis and treatment of brain cancer
Binczyk F., Tarnawski R., Polańska J.
Archives of Control Sciences
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2010
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Vol. 20, no. 4
457-472
EN
Nuclear Magnetic Resonance (NMR) is widely used technique in cancer diagnosis and treatment planning. It is employed to search for the high concentration regions of particular metabolites, which are directly related to the concentration of cancer cells. NMR signal maybe be characterized by a set of peaks which are representation of every distinct metabolite. Area under peak must be calculated in order to obtain proper information about metabolite amount. Commercially available software allows for the analysis of one-peak-in-time only. The proposed technique, based on Gaussian Mixture Model (GMM), allows for modeling all-peaks-in-time, and corrects after the neighboring peaks giving more accurate estimates of metabolite concentration. The resulting software processes NMR signal from the very beginning up to the final result, which is given in a form of so called metabolite map.
4
Content available remote The photoluminescent properties of CdS clusters of different size in porous glasses
Rysiakiewicz-Pasek E., Polańska J., Gevelyuk S.A., Doycho I.K., Mak V.T., Zhukov S.A.
Optica Applicata
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2008
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Vol. 38, nr 1
93-100
EN
CdS nanoclusters were formed in the porous glass matrix by sequential chemical deposition from liquid-vapor phase and their chemical content was investigated. The room temperature photoluminescence spectra of specimens excited with a 235 nm wavelength had typical narrow peaks at 400 nm. The peaks can be explained by quantum effects for charge carriers confined inside the small-size (radius of the order of several nanometers) clusters. At the same time the luminescence spectra of the same specimens, but excited with a xenon lamp at 77 K, had peaks at ~700 nm that approximately corresponded to the band gap of the crystalline CdS. The possibility of the crystallites existence follows from the size distribution of voids in the porous glass matrix and is confirmed by the X-ray spectra typical of the wurtzite structure. The peculiarities of the observed luminescence spectra are explained by the energetic diagram of CdS in the configurational space.
5
Content available remote Node assignment problem in Bayesian networks
Polańska J., Borys D., Polański A.
International Journal of Applied Mathematics and Computer Science
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2006
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Vol. 16, no 2
233-240
EN
This paper deals with the problem of searching for the best assignments of random variables to nodes in a Bayesian network (BN) with a given topology. Likelihood functions for the studied BNs are formulated, methods for their maximization are described and, finally, the results of a study concerning the reliability of revealing BNs’ roles are reported. The results of BN node assignments can be applied to problems of the analysis of gene expression profiles.
6
Content available Testing for signatures of natural selection at molecular genes level
Cyran K., Polańska J., Kimmel M.
Journal of Medical Informatics & Technologies
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2004
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Vol. 8
MM31--40
EN
The paper presents the methodology used for detecting the signatures of natural selection at the molecular level from single nucleotide polymorphism data. The results obtained from widely used approach, based on statistical testing departures from neutral evolution model, can be obscured by the presence of alternative hypotheses generating the similar to natural selection results of the tests. These hypotheses include population growth and geographic substructure. Especially for human population these alternatives are of non-negligible importance. In the paper we show how to deal with this problem, both by the analysis of a battery of statistical tests giving indication about the age of the predominant mutations, and by application of non conventional null hypotheses that assume different population scenarios. Since the critical values of the tests are known only for panmicting, constant size population, the second approach demands the intensive computer simulations of coalescence process to obtain analogous critical values for different scenarios used as a null. The methodology with the problem of detecting signatures of natural selection in four genes implicated in human familial cancers has been illustrated.
7
Content available remote The EM Algorithm and Its Implementation for the Estimation of Frequencies of snp-Haplotypes
Polańska J.
International Journal of Applied Mathematics and Computer Science
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2003
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Vol. 13, no 3
419-429
EN
A haplotype analysis is becoming increasingly important in studying complex genetic diseases. Various algorithms and specialized computer software have been developed to statistically estimate haplotype frequencies from marker phenotypes in unrelated individuals. However, currently there are very few empirical reports on the performance of the methods for the recovery of haplotype frequencies. One of the most widely used methods of haplotype reconstruction is the Maximum Likelihood method, employing the Expectation-Maximization (EM) algorithm. The aim of this study is to explore the variability of the EM estimates of the haplotype frequency for real data. We analyzed haplotypes at the BLM, WRN, RECQL and ATM genes with 8-14 biallelic markers per gene in 300 individuals. We also re-analyzed the data presented by Mano et al. (2002). We studied the convergence speed, the shape of the loglikelihood hypersurface, and the existence of local maxima, as well as their relations with heterozygosity, the linkage disequilibrium and departures from the Hardy-Weinberg equilibrium. Our study contributes to determining practical values for algorithm sensitivities.
8
Content available remote A model of dynamics of mutation, genetic drift and recombination in DNA-repeat genetic loci
Polańska J., Kimmel M.
Archives of Control Sciences
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1999
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Vol. 9, no. 1/2
143-157
EN
We present a model of genetic dynamics of a population of chromosomes, involving mutation, drift and recombination at a pair of repeat-DNA sequences. Such sequences, known as microsatellites and VNTR's, are commonly used as markers in studies in forensics, molecular evolution and gene mapping. The model we use has the form of a time-continuous Markov chain. It is further transformed to the form of a differential equation for probability generating functions. This description allows to follow dynamics with a variety of initial conditions. It allows, among other, to model the so called linkage disequilibrium, i.e. the state in which, due to processes like newly arisen mutation, selection, or population admixture, there exists a dependence between alleles at two loci. Recombination gradually dissolves the linkage disequilibrium, with additional contributions from drift and mutation. The model, in its complete form, is rather involved, since it includes all possible occurrences related to three genetic forces: mutation, genetic drift and recombination. However, we find explicit solutions to special cases which allow to understand the dynamics of dissolution of linkage disequilibrium. Other special cases of the model include the previously known relationships involving mutations and genetic drift. Also, we derive equations for the moments of the random variables present in the model. The moments can be used to define distance measures between distributions of alleles.
9
Model matematyczny procesu rekombinacji chromosomów
Polańska J., Kimmel M.
Zeszyty Naukowe. Automatyka / Politechnika Śląska
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1998
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z. 122
167-182
PL
W pracy przedstawiono model matematyczny ewolucji rozkładów alleli dla dwóch genów typu VNTR (Variable Number of Tandem Repeats). W procesie tworzenia modelu uwzględnionio wszystkie możliwe zdarzenia, z jednoczesnym występowaniem trzech oddziaływań genetycznych: mutacji, dryfu genetycznego i rekombinacji. Otrzymane wzory mogą z powodzeniem znaleźć zastosowanie w analizie statystycznej danych eksperymentalnych.
EN
The mathematical model of two-linked microsatellite loci evolution is presented. The described population model is a time-continuous Marcov chain. It is tranformed into differential equations' system of probablity generating function. The obtained model is very complicated because of considering all possible events, and including three genetic processes: mutation, genetic drift, and recombination. Appropriate specification of hypotheses leads to the well-known formulae. The equations could be successfully applied to the stochastic analysis of experimental data.
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