Gotowe bibliografie tematyczne / Analysis and molecular identification / Książki

Książki na temat „Analysis and molecular identification”

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Autor: Grafiati
Data publikacji: 4 maja 2024

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1

Anna, Panchenko, i Przytycka Teresa, red. Protein-protein interactions and networks: Identification, computer analysis, and prediction. London: Springer, 2008.

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2

Anna, Panchenko, i Przytycka Teresa, red. Protein-protein interactions and networks: Identification, computer analysis, and prediction. London: Springer, 2008.

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3

Przytycka, Teresa, i Anna Panchenko. Protein-protein interactions and networks: Identification, computer analysis, and prediction. [New York]: Springer, 2010.

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4

Dostal, Stefan. Concise guide to mycobacteria and their molecular differentiation. Würzburg, Germany: Ridom Press, 2003.

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5

Jayprakasha, Guddadarangavvanahally K., Bhimanagouda S. Patil i Federica Pellati, red. Instrumental Methods for the Analysis and Identification of Bioactive Molecules. Washington, DC: American Chemical Society, 2014. http://dx.doi.org/10.1021/bk-2014-1185.

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6

Louis, Edward E. Molecular and morphological analyses of the sportive lemurs (Family Megaladapidae: Genus Lepilemur) reveals 11 previously unrecognized species. Lubbock, TX: Museum of Texas Tech University, 2006.

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7

State University College at Buffalo. Dept. of Art Conservation., red. Molecular studies of asphalt, mummy and Kassel earth pigments: Their characterisation, identification and effect on the drying of traditional oil paint. [S.l: s.n.], 2004.

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8

P, Schlunegger Urs, i Schweizerischer Chemiker-Verband, red. Biologically active molecules: Identification, characterization, and synthesis : proceedings of a Seminar on Chemistry on Biologically Active Compounds and Modern Analytical Methods, Interlaken, September 5-7, 1988. Berlin: Springer-Verlag, 1989.

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9

Klimenko, Irina, Nikolay Kozlov, Sergey Kostenko, Anastasia Shamustakimova i Yulian Mavlyutov. Identification and certification of forage grasses (meadow clover, alfalfa, sowing and hop) based on DNA markers. ru: 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 given, a set of DNA identification markers is proposed, and unique molecular genetic formulas of varieties are drawn up as the basis for a reference genetic passport. Methodological recommendations were prepared with the aim of mastering the technology of DNA certification of forage grasses in practice. Designed for managers and specialists of research and control laboratories, can serve as a textbook for students and postgraduates in specialized specialties.
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10

Gherbawy, Youssuf, i Kerstin Voigt, red. Molecular Identification of Fungi. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-05042-8.

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11

Gherbawy, Youssuf, i Kerstin Voigt. Molecular identification of fungi. Berlin: Springer, 2010.

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12

Lajos, Ferenczy, red. Molecular identification of fungi. Heidelberg: Springer, 2010.

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13

Cheryl, Porter, Townsend Joyce, Institute of Archaeology i institute of Paper Conservation, red. Pigment analysis and identification. Leigh,Worcester: Institute of Paper Conservation, 1995.

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14

Boultwood, Jacqueline, i Carrie Fidler. Molecular Analysis of Cancer. New Jersey: Humana Press, 2001. http://dx.doi.org/10.1385/1592591353.

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15

National Cancer Institute (U.S.), red. Technology for molecular analysis. [Bethesda, Md.]: U.S. Dept. of Health and Human Services, Public Health Service, National Institutes of Health, National Cancer Institute, 2001.

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16

Jacqueline, Boultwood, i Fidler Carrie, red. Molecular analysis of cancer. Totowa, N.J: Humana Press, 2002.

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17

Gaver, Donald Paul. Problems of identification. Monterey, Calif: Naval Postgraduate School, 1986.

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18

Rapley, Ralph, i Stuart Harbron, red. Molecular Analysis and Genome Discovery. Chichester, UK: John Wiley & Sons, Ltd, 2004. http://dx.doi.org/10.1002/0470020202.

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19

Rapley, Ralph, i Stuart Harbron, red. Molecular Analysis and Genome Discovery. Chichester, UK: John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119977438.

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20

Ortutay, Csaba, i Zsuzsanna Ortutay. Molecular Data Analysis Using R. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119165057.

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21

Santos, Claudia Chimisso Dos. Molecular analysis of Fanconi anaemia. Ottawa: National Library of Canada, 1993.

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22

S, Waterman M., red. Mathematical analysis of molecular sequences. Oxford: Pergamon, 1989.

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23

Reed, Vivienne. Molecular analysis of mottled mutants. Oxford: Oxford Brookes University, 1997.

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24

Ralph, Rapley, i Harbron Stuart, red. Molecular analysis and genome discovery. Chichester, West Sussex, England: J. Wiley, 2004.

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25

Molecular analysis and genome discovery. Wyd. 2. Chichester, West Sussex: John Wiley & Sons, 2011.

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26

Ralph, Rapley, i Harbron Stuart, red. Molecular analysis and genome discovery. Chichester, West Sussex, England: J. Wiley, 2004.

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27

Guidelines for process hazards analysis, hazards identification & risk analysis. Wyd. 3. Ontario: Dyadem, 2003.

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28

Hawthorne, Mark R. Fingerprints: Analysis and understanding. Boca Raton: CRC Press, 2008.

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29

Subspace methods for system identification. London: Springer, 2005.

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30

Wang, Qing-Guo. Relay Feedback: Analysis, Identification and Control. London: Springer London, 2003.

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31

N, Banerjee B. Identification & economic analysis of small farmers. Delhi, India: Mittal Publications, 1986.

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32

1958-, Lee Tong Heng, i Lin Chong 1967-, red. Relay feedback: Analysis, identification, and control. London: Springer, 2003.

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33

N, Banerjee B. Identification & economic analysis of small farmers. Delhi, India: Mittal Publications, 1986.

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34

National Mine Health and Safety Academy, red. Accident analysis and problem identification, coal. Beckley, WV: U.S. Dept. of Labor, Mine Safety and Health Administration, National Mine Health and Safety Academy, 1986.

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35

1937-, Hall Lowell H., red. Molecular connectivity in structure-activity analysis. Letchworth, Hertfordshire, England: Research Studies Press, 1986.

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36

Panchenko, Anna, i Teresa M. Przytycka. Protein-Protein Interactions and Networks: Identification, Computer Analysis, and Prediction. Springer London, Limited, 2010.

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37

Przytycka, Teresa, i Anna Panchenko. Protein-protein Interactions and Networks: Identification, Computer Analysis, and Prediction. Springer, 2008.

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38

Elnagdi, Mohamed Hilmy, Kamal Usef Sadek i Ramadan Ahmed Mekheimer. Spectroscopic Identification of Organic Molecules. World Scientific Publishing Co Pte Ltd, 2018.

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39

Techniques of Lipidology: Isolation, Analysis and Identification of Lipids. Wyd. 3. Ottawa, Canada: NewportSomerville, sole distributors worldwide, 2010.

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40

Monis, Paul, Nic Reid, Australian Water Quality Centre i South Australian Water Corporation. Evaluation and Validation of Rapid Molecular Methods for the Detection and Identification of Microorganisms in Water - Standard Operating Procedures. IWA Publishing, 2015.

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41

Arthur, Brown. Molecular analysis of an insertional mutation at the mouse dt locus: the identification of a candidate dt gene. 1993.

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42

Gribskov, Michael, i John Devereux, red. Sequence Analysis Primer. Oxford University Press, 1995. http://dx.doi.org/10.1093/oso/9780195098747.001.0001.

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Computerized sequence analysis is an integral part of biotechnological research, yet many biologists have received no formal training in this important technology. Sequence Analysis Primer offers the beginner the necessary background to enter this vital field and helps more seasoned researchers to fine-tune their approach. It covers basic data manipulation such as homology searches, stem-loop identification, and protein secondary structure prediction, and is compatible with most sequence analysis programs. A detailed example giving steps for characterizing a new gene sequence provides users with hands-on experience when combined with their current software. The book will be invaluable to researchers and students in molecular biology, genetics, biochemistry, microbiology, and biotechnology.
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43

Portwine, Carol Ann. Identification and characterization of Li-Fraumeni syndrome families: Molecular and in vitro analysis and development of an in vivo model. 2002.

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44

Schlunegger, Urs Peter. Biologically Active Molecules: Identification, Characterization and Synthesis : Proceedings of a Seminar on Chemistry of Biologically Active Compound. Springer, 1989.

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45

New approaches to molecular diagnostics: Identification of differentially expressed genes in breast cancer cell lines using cDNA aray hybridization and sequence analysis. Ottawa: National Library of Canada, 1998.

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46

Stallings, Michael C., Ian R. Gizer i Kelly C. Young-Wolff. Genetic Epidemiology and Molecular Genetics. Redaktor Kenneth J. Sher. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199381678.013.002.

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The tools of genetic epidemiology—family, adoption, and twin studies—show convincingly that substance use behavior and substance use disorders are influenced by both genetic and familial and extrafamilial environmental factors. Environmental factors appear to play a more influential role in the early stages of substance use, whereas genetic factors become more important in the development of problem use and substance use disorder. Moreover, some genetic effects are likely conditional on conducive environments; research employing both behavior genetic approaches and measured genes point to important gene–environment interactions that promote substance use and dependence. Consequently, a full understanding of the addiction process requires investigating substance use behavior within its comorbid context. The identification of specific genetic mechanisms underlying these heritable influences is elusive. These findings have prompted the development of new strategies for testing the joint effect of multiple genetic variants in gene-based or gene pathway analyses.
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47

Gherbawy, Youssuf, i Kerstin Voigt. Molecular Identification of Fungi. Springer, 2011.

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48

Gherbawy, Youssuf, i Kerstin Voigt. Molecular Identification of Fungi. Springer Berlin / Heidelberg, 2014.

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49

Gaydon, A. G. Identification of Molecular Spectra. Springer, 2011.

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50

1927-, Nakamura Robert M., i O'Sullivan Michael B, red. Clinical laboratory molecular analysis. Orlando, FL: Grune & Stratton, 1985.

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