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Patrik Vida

Change. 14. Fári, M.G. & Kralovánszky, U.P., (2006). “The founding father of biotechnology: Károly (Karl) Ereky”. International Journal of Horticultural Science, Vol.12 No.1, pp.9–12. 15. Farrell, D., (2005). “Offshoring: Value creation through economic change”. Journal of Management Studies, Vol.42 No.3, pp.675–683. 16. Gerstein, M.B. et al., (2007). “What is a gene, post-ENCODE? History and updated definition.”. Genome research, Vol.17 No.6, pp.669–81. 17. Glick, J.L., (2008). “Biotechnology business models work: Evidence from the

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Tolga Karaköy, Ahmet Demirbaş, Faruk Toklu, Nevcihan Gürsoy, Eylem Tugay Karagöl, Damla Uncuer and Hakan Özkan


Faba bean (Vicia faba L.) is one of the most important legume crop and cultivated nearly all parts of the world. Present study was aimed to investigate the variation in the micro and macronutrients concentration in the Turkish faba bean germplasm. A total of 200 landraces and 3 commercial cultivars were collected from the different geographical regions of Turkey. Study was conducted at the research and experimental area of Department of Crop and Animal Production, Vocational School of Sivas, University of Cumhuriyet, Sivas, Turkey in 2016. Result of this study reflected higher level of diversity for studies nutrients; (N) (5.21-8.15 %), phosphorus (P) (0.1-0.98 %), potassium (K) (0.94-5.6 %), magnesium (mg) (0.32-0.42), calcium (Ca) (0.50-1.50), copper (Cu) (8.13-34.23 mg kg-1), zinc (Zn) (28.42-64.33 mg kg-1), iron (Fe) (44.86-128.53 mg kg-1), and manganese (Mn) (16.56-35.76 mg kg-1). Average concentrations of micro and macronutrients were found higher in the landraces as compared to the commercial cultivars. Principal component analysis grouped the studied germplasm into two groups on the basis of their Zn concentrations. Results from this study expressed the presence of high range of diversity in the Turkish faba bean germplasm for micro and macronutrient elements. Findings of this study will serves as starting point for the development of improved faba bean varieties through conventional and modern breeding technologies and these variations will be helpful for the identification of linked markers through the genome wide association studies and identifying diverse parents for quantitative trait locus (QTL) mapping.

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Cristin Coman, Carmen Cristina Surdu-Bob, Florica Barbuceanu, Ene Vlase and Marius Badulescu

(3):414-421. Surdu-Bob C.C., Coman C., Barbuceanu F., Turcu D., Bercaru N., Badulescu M., 2016. The influence of foreign body surface area on the outcome of chronic osteomyelitis. Medical Engineering and Physics, 38: 870-876. Warnes S.L., Keevil C.W., 2016. Lack of involvement of Fenton chemistry in death of methicillin-resistant and methicillin-sensitive strains of Staphylococcus aureus and destruction of their genomes on wet or dry copper alloy. Appl Environ Microbiol 82:2132-2136.

Open access

Ortansa Csutak, Viorica Corbu, Ileana Stoica and Tatiana Vassu

salmon/red melanin containing Rhodotorula glutinis. African Journal of Biotechnology, 4:164-171. Papaparaskevas D., Christakopoulos P., Kekos D., Maeris B.J, 1992. Optimizing production of extracellular lipase from Rhodotorula glutinis. Biotechnology Letters, 14(5): 397-402. Paul D., Magbanua Z., Arick M., French T., Bridges S.M., Burgess S.C., Lawrence M.L., 2014. Genome sequence of the oleaginous yeast Rhodotorula glutinis ATCC 204091. Genome Announcements, 2(1): e00046-14. Pfaller M.A., Diekema D.J., Mendez M., Kibbler

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Steliana Paula Barbu, Aurel Giura, Daniel Cristina and Călina Petruţa Cornea

in rye (Secalecereale L.). Genome; 42:964-972. 16. Săulescu, N.N., 2001, Romanian Wheat Pool. In: The World Wheat Pool - a history of wheat breeding", (Eds.: A.P. Bonjean and W.J. Angus), Lavoiser Publishing, London, Paris, New York: 333-349 17. Sial, M.A., Arain, M.A., Javed,M.A., Jamali, K.D., 2002, Genetic impact of dwarfing genes (Rht1 and Rht2) for improving grain yield in wheat, Asian J Plant Sci 1:254-256 18. Şerban, G., 2012, Identification of longer coleoptile mutants in an Rht-B1b semi-dwarf wheat population

Open access

Alexandru Bran and Viorel Ion

., Raftis F., Sallet E., Schiex T., Thomas J., Vandecasteele C., Varès D., Vear F., Vautrin S., Crespi M., Mangin B., Burke J.M., Salse J., Muños S., Vincourt P., Rieseberg L.H., Langlade N.B., 2017. The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution. Nature, Jun 1; 546(7656):148-152. Enns H., Dorrell D.G., Hoes J.A., Chubb W.O., 1970. Sunflower Research - A Progress Report. Proc. 4th Int. Sunflower Conf., Memphis, Tennessee, USA, p. 162-167. Golabadi M., Golkar P., Shahsavari M.R., 2015. Genetic

Open access

Tolga Yuret

that have been included in at least 3,000 publications. The keywords are sorted in descending order. “Embryonic stem-cells” has 2.52 YK and “innate human immunity” has 1.57 YK. Table 2 Best 30 performers in terms of YK. embryonic stem-cells; carbon nanotubes; field-effect transistors; graphite; genome-wide association; caenorhabditis-elegans; DNA methylation; living cells; regulatory t-cells; gold nanoparticles; tgf-beta; one-pot synthesis; quantum dots; functionalization; electrodes; acute myeloid-leukemia; long-term potentiation; activated

Open access

Maria Esteva, Ramona L. Walls, Andrew B. Magill, Weijia Xu, Ruizhu Huang, James Carson and Jawon Song

, probes), processes (e.g., sequencing, genome assembly), and data as entities Entities are how we operationalize classes of files in a data model. that relate to specific lifecycle stages of their research projects. Users can register and associate large data that are distributed across storage systems, including similar data instances, with these entities and upload corresponding metadata via web forms or in bulk. Around the different entities, the metadata are used to differentiate the structure and components of the dataset. Once data are registered in IDS

Open access

Liang Hong, Mengqi Luo, Ruixue Wang, Peixin Lu, Wei Lu and Long Lu

of data. For example, as can be seen from the Human Genome Project completed in 2003, one single genome in human DNA occupies 100–150 gigabytes ( Marx, 2013 ; O’Driscoll, Daugelaite, & Sleator, 2013 ). In terms of data size, Big Data in health care exceeded 150 exabytes after 2011 (Wang, Kung, Ting, & Byrd, 2015), and a study showed that data size in health care is estimated to be around 40 ZB in 2020, about 50 times the 2009 figure of 0.8 ZB (O et al., 2013) ( Fig. 1A ). Figure 1A Data explosion in health care In addition, as researchers continue to

Open access

Neil R. Smalheiser and Aaron M. Cohen

utilize our existing resources but also donate their own processed features and similarity metrics (subject to evaluation and space limitations). We have added a Repository of Processed Text and Resources page to the project website that encourages others to donate their processed text and features back to us so that we can integrate them into our suite and host them publicly. This is not unlike the UCSC Genome Browser ( ) where any group can donate tracks, download tracks, or juxtapose their own private custom tracks on public data. Our