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1

R, König Inke, ed. A statistical approach to genetic epidemiology. 2nd ed. Wiley-VCH, 2010.

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2

Workshop, on the Analysis of Genetic Data to Address Problems of Stock Identity as Related to Management of Marine Mammals (1994 Southwest Fisheries Science Center La Jolla Calif ). Molecular genetics of marine mammals: Incorporating the proceedings of a Workshop on the Analysis of Genetic Data to Address Problems of Stock Identity as Related to Management of Marine Mammals. Society for Marine Mammalogy, 1997.

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3

CMSB 2008 (2008 Rostock, Germany). Computational methods in systems biology: 6th international conference, CMSB 2008, Rostock, Germany, October 12-15, 2008 : proceedings. Springer, 2008.

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4

CMSB 2008 (2008 Rostock, Germany). Computational methods in systems biology: 6th international conference, CMSB 2008, Rostock, Germany, October 12-15, 2008 : proceedings. Springer, 2008.

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5

Pevsner, Jonathan. Bioinformatics and Functional Genomics. John Wiley & Sons, Ltd., 2005.

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6

Puhal'skiy, Vitaliy. Introduction to Genetics. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1019851.

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The textbook outlines the cytological foundations of heredity, the regularities of Mendelian genetics, the chromosomal theory of heredity, the basics of molecular genetics and genetic engineering, the patterns of inheritance during distant hybridization, polyplodia and mutagenesis. Special attention is paid to the heterosis and genetics of populations. A significant part of the data is presented in the form of figures, diagrams, graphs and tables that facilitate the understanding of the material presented.
 Meets the requirements of the federal state educational standards of higher educat
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7

M, Calder, and Gilmore Stephen 1962-, eds. Computational methods in systems biology: International Conference CMSB 2007, Edinburgh, Scotland, September 20-21, 2007 : proceedings. Springer, 2007.

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8

Javier, Cabrera, ed. Exploration and analysis of DNA microarray and protein array data. John Wiley, 2004.

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9

Louxin, Zhang, ed. Sequence comparison: Theory and methods. Springer, 2009.

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10

Degano, Pierpaolo. Computational Methods in Systems Biology: 7th International Conference, CMSB 2009, Bologna, Italy, August 31-September 1, 2009. Proceedings. Springer Berlin Heidelberg, 2009.

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11

1953-, Golding Brian, and Canadian Institute for Advanced Research., eds. Non-neutral evolution: Theories and molecular data. Chapman & Hall, 1994.

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12

Klimenko, Irina, Nikolay Kozlov, Sergey Kostenko, Anastasia Shamustakimova, and Yulian Mavlyutov. Identification and certification of forage grasses (meadow clover, alfalfa, sowing and hop) based on DNA markers. Federal Williams Research Center of Forage Production and Agroecology, 2020. http://dx.doi.org/10.33814/978-5-6043194-9-9.

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A technology has been developed for DNA identification and certification of varieties of meadow clover (Trifolium pratense L.), alfalfa (Medicago varia Mart.), Sowing (M. sativa L.) and hop (M. lupuli-na L.) based on molecular analysis with using SSR and SRAP markers. The recommendations contain a description of the sequence of experiments and protocols for DNA typing procedures. The presented methods were developed by the authors on the basis of their own experimental research and using the data available in the literature. A characteristic of informative primers for each marking system is gi
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13

Pacific Symposium on Biocomputing (2nd 1997 Maui, Hawaii). Pacific Symposium on Biocomputing '97: Maui, Hawaii, USA, 6-9 January 1997. Edited by Altman Russ. World Scientific, 1996.

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14

Adrianus Antonius Cornelis Maria Peijnenburg. Structural plasmid instability in Bacillus subtilis. Achterom, 1988.

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15

Rune, Matthiesen, ed. Mass spectrometry data analysis in proteomics. Humana Press, 2007.

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16

Matthiesen, Rune. Mass spectrometry data analysis in proteomics. Humana Press, 2013.

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17

Gilbert, Lawrence I. Insect Molecular Biology and Biochemistry. Academic Press [Imprint], 2011.

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18

Pontarotti, Pierre. Evolutionary Biology - Concepts, Molecular and Morphological Evolution: 13th Meeting 2009. Springer-Verlag Berlin Heidelberg, 2010.

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19

Rosa, Arboretti, Corain Livio, Mazzaro Dario, and SpringerLink (Online service), eds. Permutation Testing for Isotonic Inference on Association Studies in Genetics. Luigi Salmaso, 2011.

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20

Majoros, William H. Methods for computational gene prediction. Cambridge University Press, 2007.

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21

Bleasby, Alan. EMBOSS administrator's guide: Bioinformatics software management. Cambridge University Press, 2011.

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22

Tyukavin, Aleksandr. Fundamentals of pathology. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1242551.

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The textbook reveals the concepts of health and disease, presents modern ideas about the causes and conditions of the occurrence of actual types of pathology. The importance of molecular genetic factors of heredity and reactivity in the formation of typical pathological processes is shown. The main regularities and features of manifestations of organ and system dysfunction in various types of pathology are described. Special attention is paid to the causes and mechanisms of development of socially significant diseases of the heart and blood vessels, brain, respiratory organs and other vital sy
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23

1935-, Friedmann Theodore, ed. Molecular Genetic Medicine. Academic P., 1993.

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24

Friedmann, Theodore. Molecular Genetic Medicine. Academic Press, 1991.

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25

Friedmann, Theodore. Molecular Genetic Medicine. Academic Press, 1993.

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26

Friedmann, Theodore. Molecular Genetic Medicine. Academic Press, 1992.

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27

Molecular Genetic Medicine. Academic Pr, 1994.

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28

Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology). M.I.T. PRESS, 2001.

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29

Gacesa, Peter, and Dipak P. Ramji. Vectors: Essential Data. John Wiley & Sons, 1995.

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30

Suffredini, Anthony F., and J. Perren Cobb. Genetic and molecular expression patterns in critical illness. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0031.

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Investigators who study RNA, proteins, or metabolites use analytic platforms that simultaneously measure changes in the relative abundance of thousands of molecules in a single biological sample. Over the last decade, the application of these high-throughput, genome-wide platforms to study critical illness and injury has generated huge quantities of data that require specialized computational skills for analysis. These investigations hold promise for improving our understanding of the host response, thereby transforming the practice of intensive care. This chapter summarizes recent technologic
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31

Cutter, Asher D. A Primer of Molecular Population Genetics. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838944.001.0001.

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The study of molecular population genetics seeks to understand the micro-evolutionary principles underlying DNA sequence variation and change. It addresses such questions as: Why do individuals differ as much as they do in their DNA sequences? What are the genomic signatures of adaptations? How often does natural selection dictate changes to DNA and accumulate as differences between species? How does the ebb and flow in the abundance of individuals over time get marked onto chromosomes to record genetic history? The concepts used to answer such questions also apply to analysis of personal geno
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32

Crawford, Michael, and Rohina C. Rubicz. Molecular Genetic Evidence from Contemporary Populations for the Origins of Native North Americans. Edited by Max Friesen and Owen Mason. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199766956.013.4.

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An overview of the current molecular genetic evidence for the origins of North American populations is presented, including specific examples from the authors’ work with the Aleutian Island inhabitants. Shared mitochondrial DNA and Y-chromosome DNA markers among Siberians and Native Americans point to a Pleistocene migration from Siberia into the Americas via Beringia. There was likely a later migration from Siberia to Alaska, based on the analysis of whole-genome sequence data from a Greenland Paleoeskimo that clusters this individual with Siberian populations. Coalescence date estimates for
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33

Divan, Aysha, and Janice A. Royds. 5. Molecular interactions. Oxford University Press, 2016. http://dx.doi.org/10.1093/actrade/9780198723882.003.0005.

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Every nucleated diploid cell in the body, with the exception of B and T cells of the immune system, has the same genome as its originating single fertilized egg. During development, this single cell differentiates into a complex multicellular organism composed of various cells and tissues each carrying out specialized functions. Although each cell contains a genome of data it needs to select the relevant information from this genetic blueprint to fulfil its own specific function. ‘Molecular interactions’ shows that proteins must be produced in the right place and at the right time. This requir
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34

Shivers, Susan J., Andrew E. Dizon, and W. F. Perrin. Molecular Genetics of Marine Mammals: Incorporating the Proceedings of a Workshop on the Analysis of Genetic Data to Address Problems of Stock Identit ... / The Society for Marine Mammalogy). Society for Marine Mammalogy, 1997.

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35

Gu, Xun. Statistical Analysis of Molecular and Genomic Evolution. Oxford University PressOxford, 2024. http://dx.doi.org/10.1093/oso/9780198816515.001.0001.

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Abstract This book introduces up-to-date methods in statistics and bioinformatics for the study of molecular and genome evolution. It first provides a concise overview of molecular evolutionary analysis and phylogenetic inference. The following chapters cover four research themes: evolution of protein functionality and functional divergence (Chapters 3 and 4); effective gene pleiotropy estimation under the genotype-phenotype mapping model of protein evolution (Chapter 5); evolution of genetic robustness after gene duplication (Chapter 6), and the statistical models of transcriptome evolution (
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36

Sætre, Glenn-Peter, and Mark Ravinet. Evolutionary Genetics. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198830917.001.0001.

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Evolutionary genetics is the study of how genetic variation leads to evolutionary change. With the recent explosion in the availability of whole genome sequence data, vast quantities of genetic data are being generated at an ever-increasing pace with the result that programming has become an essential tool for researchers. Most importantly, a thorough understanding of evolutionary principles is essential for making sense of this genetic data. This up-to-date textbook covers all the major components of modern evolutionary genetics, carefully explaining fundamental processes such as mutation, na
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37

Noordenbos, Troy, and Dominique Baeten. Immune mechanisms: innate immunity. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198734444.003.0007.

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Innate immune mechanisms are strongly implied in the pathophysiology of spondyloarthritis (SpA). This chapter discusses available data on the role of the innate immune system in relation to HLA-B27, genetic associations, and the cellular and molecular characteristics of disease target tissue. Regarding the linkage with MCH-class I molecule HLA-B27, the chapter discusses the arthritogenic peptide hypothesis and three popular antigen-independent theories. The genetic architecture of the disease argues against a role for the adaptive immune system and identifies cytokine pathways, such as IL-1, T
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38

From Genes to Genomes: Concepts and Applications of DNA Technology. Wiley & Sons Canada, Limited, John, 2008.

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39

From Genes to Genomes: Concepts and Applications of DNA Technology. John Wiley & Sons, 2002.

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40

Probability models for DNA sequence evolution. Springer, 2002.

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41

Probability models for DNA sequence evolution. 2nd ed. Springer, 2008.

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42

An introduction to risk calculation in genetic counselling. OUP, 1991.

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43

Bioinformatics and functional genomics. Wiley-Liss, 2004.

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44

Bioinformatics and Functional Genomics. 2009.

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45

Bioinformatics and Functional Genomics. Wiley-Interscience, 2015.

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46

Bioinformatics and Functional Genomics. Wiley & Sons Canada, Limited, John, 2005.

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47

Pevsner, Jonathan. Bioinformatics and Functional Genomics. Wiley-Liss, 2004.

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48

Pevsner, Jonathan. Bioinformatics and Functional Genomics. Wiley-Liss, 2003.

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49

Pevsner, Jonathan. Bioinformatics and Functional Genomics. Wiley & Sons, Incorporated, John, 2008.

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50

Pevsner, Jonathan. Bioinformatics and Functional Genomics. Wiley & Sons, Incorporated, John, 2015.

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