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Transcription initiation sites on the soybean mitochondrial genomeAuchincloss, Andrea Helen January 1987 (has links)
No description available.
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Genetic Testing and Counseling Practices for Patients with Retinoblastoma at Cincinnati Children’s Hospital Medical CenterFreeze, Samantha 22 June 2015 (has links)
No description available.
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Pre- and Post-Test Parent Perceptions of Genetic Testing for Children with Autism Spectrum Disorder (ASD)Winslow, Hayley R. 02 August 2017 (has links)
No description available.
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Solving Maximum Number of Run Using Genetic AlgorithmChan, Kelvin January 2008 (has links)
<p> This thesis defends the use of genetic algorithms (GA) to solve the maximum number of
repetitions in a binary string. Repetitions in strings have significant uses in many
different fields, whether it is data-mining, pattern-matching, data compression or
computational biology 14]. Main extended the definition of repetition, he realized that
in some cases output could be reduced because of overlapping repetitions, that are
simply rotations of one another [10]. As a result, he designed the notion of a run to
capture the maximal leftmost repetition that is extended to the right as much as
possible. Franek and Smyth independently computed the same number of maximum
repetition for strings of length five to 35 using an exhaustive search method. Values
greater than 35 were not computed because of the exponential increase in time
required. Using GAs we are able to generate string with very large, if not the maximum,
number of runs for any string length. The ability to generate strings with large runs is an
advantage for learning more about the characteristics of these strings. </p> / Thesis / Master of Science (MSc)
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Red raspberry transformation using agrobacteriumFaria, Maria José Sparça Salles de January 1993 (has links)
No description available.
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The pharmacogenomic era in Asia: Potential roles and challenges for Asian pharmacistsLee, Stephanie, Kwok, R.C.C., Wong, I.C.K., Lui, V.W.Y. 13 February 2017 (has links)
Yes / Personalized medicine through Pharmacogenomics: choosing the right drug, and the right dose, for the right
patients based on patient’s genetic makeup-is gradually being realised in Western countries. Yet, the practice of
pharmacogenomics in Asian countries lags behind that of the West, but the medical needs for pharmacogenomics
are expected to surge as better patient care is demanded in Asia. As next-generation sequencing technology
advances quickly, previous technical challenges for performing pharmacogenomic studies or practices in Asia have
been mostly resolved. What is lacking in Asia is an effective model of community-wide pharmacogenomics. On the
delivery front, pharmacists, the drug and dosing professionals, can potentially be the main healthcare providers
for pharmacogenomic services in Asia. The first large “Genomics for Precision Drug Therapy in the Community
Pharmacy” in Canada, which is close to its completion, has successfully identified community pharmacists as
key contact professionals for smooth facilitation and implementation of pharmacogenomics for personalized
medication. It is anticipated that Asian pharmacists, with appropriate training, can have the capacity to provide expert
pharmacogenomic supports for both physicians and patients in Asia. / The School of Biomedical Sciences Start-up Fund, the Chinese University of Hong Kong, the General Research Fund (#17114814; #17121616), the Theme-based Research Scheme (T12-401/13-R), Research Grant Council, Hong Kong, as well as the Hong Kong Cancer Fund, Hong Kong.
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Machine learning through self generating programsLubbe, H.G, Kotze, B.J. January 2007 (has links)
Published Article / People have tried different ways to make machines intelligent. One option is to use a simulated neural net as a platform for Genetic Algorithms. Neural nets are a combination of neurons in a certain pattern. Neurons in a neural net system are a simulation of neurons in an organism's brain. Genetic Algorithms represent an emulation of evolution in nature. The question arose as to why write a program to simulate neurons if a program can execute the functions a combination of neurons would generate. For this reason a virtual robot indicated in Figure 1 was made "intelligent" by developing a process where the robot creates a program for itself. Although Genetic Algorithms might have been used in the past to generate a program, a new method called Single-Chromosome-Evolution-Algorithms (SCEA) was introduced and compared to Genetic Algorithms operation. Instructions in the program were changed by using either Genetic Algorithms or alternatively with SCEA where only one simulation was needed per generation to be tested by the fitness of the system.
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A case study of people's experiences of genetic investigation for inherited epilepsy : lessons for future service deliveryHammond, Carrie Louise January 2010 (has links)
No description available.
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A study of replicating instabilities in Schizosaccharomyces pombeRoberts, Jacqueline Lucy January 1987 (has links)
No description available.
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HRAS1-selected chromosome mediated gene transfer : molecular insights into tumorigenicity and recombinationHirst, Mark C. January 1988 (has links)
No description available.
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